🎓 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":99,"_152":172,"_154":-5,"_155":137,"_156":173,"_157":158,"_105":174,"_100":175,"_161":162,"_163":176,"_165":22,"_166":-5,"_167":177,"_98":178},"c6eb7018-8cf5-11f0-b7a0-0224a6c84d84","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;",[],[99],{"_103":180,"_95":181,"_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","new-file-4421.tsx","cb71ac2c-88b5-11f0-b66d-0224a6c84d84",23,["D",1756898359328],7,"// Enhanced EdTech YouTube Comment Analysis Tool - ValTown Compatible\n// Multi-Pass AI System with Gemini 2.5 Pro\n\nexport default async function (req) {\n const url = new URL(req.url);\n const videoId = url.searchParams.get(\"videoId\");\n const format = url.searchParams.get(\"format\");\n\n if (!videoId) {\n return new Response(generateMainInterface(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n const youtubeApiKey = process.env.YOUTUBE_API_KEY;\n const geminiApiKey = process.env.GEMINI_API_KEY;\n\n if (!youtubeApiKey || !geminiApiKey) {\n return new Response(\n JSON.stringify({\n error: \"API keys not configured\",\n required: {\n YOUTUBE_API_KEY: youtubeApiKey ? \"✓ Configured\" : \"❌ Missing\",\n GEMINI_API_KEY: geminiApiKey ? \"✓ Configured\" : \"❌ Missing\",\n },\n setup: \"Contact administrator to configure API keys\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n try {\n await rateLimitCheck(req);\n\n const [videoDetails, comments] = await Promise.all([\n fetchVideoDetailsWithRetry(videoId, youtubeApiKey),\n fetchYouTubeCommentsWithRetry(videoId, youtubeApiKey),\n ]);\n\n const basicAnalysis = analyzeCommentsEdTech(comments);\n\n // ENHANCED MULTI-PASS AI ANALYSIS\n console.log(\"🚀 Starting Enhanced Multi-Pass AI Analysis...\");\n const geminiInsights = await enhancedMultiPassAnalysis(\n comments,\n videoDetails,\n geminiApiKey,\n );\n\n const completeAnalysis = {\n ...basicAnalysis,\n aiInsights: geminiInsights,\n analysisTimestamp: new Date().toISOString(),\n analysisVersion: \"EdTech-Enhanced-v3.0\",\n totalAnalysisCategories: 35,\n };\n\n if (format === \"dashboard\") {\n return new Response(\n generateEnhancedDashboardHTML(videoDetails, completeAnalysis),\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n }\n\n return new Response(\n JSON.stringify(\n {\n success: true,\n analyzedAt: new Date().toISOString(),\n analysisType: \"Enhanced EdTech Educational Analysis\",\n video: {\n id: videoId,\n title: videoDetails.title,\n channel: videoDetails.channel,\n publishedAt: videoDetails.publishedAt,\n viewCount: videoDetails.viewCount,\n likeCount: videoDetails.likeCount,\n commentCount: videoDetails.commentCount,\n url: `https://www.youtube.com/watch?v=${videoId}`,\n },\n fetchedComments: comments.length,\n analysis: completeAnalysis,\n },\n null,\n 2,\n ),\n {\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n },\n );\n } catch (error) {\n console.error(\"Enhanced analysis error:\", error);\n\n if (error.message.includes(\"quota\")) {\n return new Response(generateQuotaErrorHTML(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n return new Response(generateErrorHTML(error.message), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n}\n\n// ========================================\n// ENHANCED MULTI-PASS AI ANALYSIS SYSTEM\n// ========================================\n\nasync function enhancedMultiPassAnalysis(comments, videoDetails, geminiApiKey) {\n try {\n console.log(\"🚀 Starting Enhanced Multi-Pass AI Analysis...\");\n\n // Sequential AI passes for deep analysis\n const [teacherAnalysis, learningAnalysis, behaviorAnalysis] = await Promise\n .all([\n deepTeacherAnalysis(comments, videoDetails, geminiApiKey),\n comprehensiveLearningAnalysis(comments, videoDetails, geminiApiKey),\n studentBehaviorAnalysis(comments, videoDetails, geminiApiKey),\n ]);\n\n // Additional passes\n const [contentAnalysis, predictiveAnalysis] = await Promise.all([\n contentEffectivenessAnalysis(comments, videoDetails, geminiApiKey),\n predictiveAnalyticsGeneration(comments, videoDetails, geminiApiKey),\n ]);\n\n console.log(\"✅ Enhanced Multi-Pass Analysis Complete!\");\n\n return {\n teacherPerformance: teacherAnalysis,\n learningAnalytics: learningAnalysis,\n studentBehavior: behaviorAnalysis,\n contentEffectiveness: contentAnalysis,\n predictiveInsights: predictiveAnalysis,\n analysisDepth: \"Advanced Multi-Pass Analysis\",\n totalInsightCategories: 35,\n passesCompleted: 5,\n };\n } catch (error) {\n console.error(\"Enhanced AI analysis error:\", error);\n return getAdvancedFallbackAnalysis();\n }\n}\n\n// ========================================\n// AI ANALYSIS PASSES - INDIVIDUAL FUNCTIONS\n// ========================================\n\nasync function deepTeacherAnalysis(comments, videoDetails, geminiApiKey) {\n const teacherComments = comments.slice(0, 60).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n timestamp: c.publishedAt,\n }));\n\n const teacherPrompt = `\nAs a MASTER EDUCATIONAL EVALUATOR with 20+ years experience, conduct detailed analysis of teacher \"${videoDetails.channel}\" for \"${videoDetails.title}\".\n\nTEACHER PERFORMANCE FRAMEWORK:\n1. Teaching Methodology (Score 1-10 each):\n - Pedagogical Approach Effectiveness\n - Learning Style Accommodation \n - Cognitive Load Management\n - Scaffolding Techniques\n\n2. Communication Excellence:\n - Verbal Clarity & Articulation\n - Technical Vocabulary Usage\n - Explanation Structure & Flow\n - Student Question Handling\n\n3. Subject Matter Expertise:\n - Content Knowledge Depth\n - Accuracy & Precision\n - Real-world Applications\n - Concept Simplification\n\n4. Emotional Intelligence:\n - Student Emotional Recognition\n - Empathy Demonstration\n - Confidence Building\n - Inclusive Environment\n\nStudent Comments: ${JSON.stringify(teacherComments)}\n\nProvide detailed JSON analysis:\n{\n \"overallTeacherRating\": {\"score\": \"X/10\", \"justification\": \"detailed reasoning with evidence\"},\n \"teachingMethodology\": {\n \"pedagogicalApproach\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"learningStyleAccommodation\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"cognitiveLoadManagement\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"scaffoldingTechniques\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"communicationExcellence\": {\n \"verbalClarity\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"technicalVocabulary\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"explanationStructure\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"questionHandling\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"subjectMatterExpertise\": {\n \"contentKnowledgeDepth\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"accuracyPrecision\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"realWorldApplications\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"conceptSimplification\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"emotionalIntelligence\": {\n \"studentEmotionalRecognition\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"empathyDemonstration\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"confidenceBuilding\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"inclusiveEnvironment\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"detailedStrengths\": [\"strength 1 with examples\", \"strength 2 with evidence\", \"strength 3 with quotes\"],\n \"criticalImprovements\": [\"improvement 1 with action plan\", \"improvement 2 with timeline\", \"improvement 3 with resources\"],\n \"teachingPersonality\": \"Detailed psychological profile of teaching style\",\n \"competitiveAdvantages\": [\"unique strength 1\", \"unique strength 2\", \"unique strength 3\"]\n}\n\nBe extremely detailed. Provide evidence for every claim.`;\n\n return await processGeminiRequest(teacherPrompt, geminiApiKey);\n}\n\nasync function comprehensiveLearningAnalysis(\n comments,\n videoDetails,\n geminiApiKey,\n) {\n const learningComments = comments.slice(0, 50).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const learningPrompt = `\nAs a LEARNING SCIENCE EXPERT, perform comprehensive learning analytics.\n\nLEARNING ANALYTICS FRAMEWORK:\n1. Cognitive Processing Analysis:\n - Bloom's Taxonomy Distribution (Remember, Understand, Apply, Analyze, Evaluate, Create)\n - Cognitive Load Assessment\n - Critical Thinking Evidence\n - Problem-Solving Approaches\n\n2. Learning Progression:\n - Knowledge Construction Evidence\n - Skill Development Stages\n - Mastery Indicators\n - Learning Obstacles\n\nComments: ${JSON.stringify(learningComments)}\nVideo: \"${videoDetails.title}\"\n\nProvide comprehensive JSON:\n{\n \"cognitiveProcessing\": {\n \"bloomsTaxonomyDistribution\": {\"remember\": \"X%\", \"understand\": \"X%\", \"apply\": \"X%\", \"analyze\": \"X%\", \"evaluate\": \"X%\", \"create\": \"X%\"},\n \"cognitiveLoadAnalysis\": {\"intrinsic\": \"High/Medium/Low\", \"extraneous\": \"High/Medium/Low\", \"germane\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"]},\n \"criticalThinking\": {\"demonstrated\": true, \"examples\": [\"example1\", \"example2\"], \"level\": \"Advanced/Intermediate/Basic\"},\n \"problemSolvingApproach\": {\"strategy\": \"Systematic/Intuitive\", \"effectiveness\": \"High/Medium/Low\", \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"learningProgression\": {\n \"knowledgeConstruction\": {\"stage\": \"Foundation/Building/Integration\", \"evidence\": [\"quote1\", \"quote2\"], \"next_steps\": [\"step1\", \"step2\"]},\n \"skillDevelopment\": {\"current_stage\": \"Novice/Competent/Proficient/Expert\", \"progression_rate\": \"Fast/Moderate/Slow\"},\n \"masteryByTopic\": [{\"topic\": \"topic1\", \"mastery_level\": \"X%\", \"evidence\": [\"quote1\", \"quote2\"], \"confidence\": \"High/Medium/Low\"}],\n \"learningObstacles\": [{\"obstacle\": \"description\", \"frequency\": 5, \"impact\": \"High/Medium/Low\", \"solutions\": [\"solution1\", \"solution2\"]}]\n }\n}`;\n\n return await processGeminiRequest(learningPrompt, geminiApiKey);\n}\n\nasync function studentBehaviorAnalysis(comments, videoDetails, geminiApiKey) {\n const behaviorComments = comments.slice(0, 40).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const behaviorPrompt = `\nAs an EDUCATIONAL PSYCHOLOGIST, analyze student behavior and motivation.\n\nPSYCHOLOGY FRAMEWORK:\n1. Motivation Analysis:\n - Self-Determination Theory (Autonomy, Competence, Relatedness)\n - Intrinsic vs Extrinsic Motivation\n - Achievement Goal Orientation\n - Self-Efficacy Assessment\n\n2. Emotional State:\n - Emotional Regulation\n - Stress/Anxiety Levels\n - Confidence Assessment\n - Satisfaction Markers\n\nComments: ${JSON.stringify(behaviorComments)}\n\nProvide detailed psychological analysis:\n{\n \"motivationPsychology\": {\n \"selfDeterminationTheory\": {\n \"autonomy\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"support_needs\": [\"need1\", \"need2\"]},\n \"competence\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"development_areas\": [\"area1\", \"area2\"]},\n \"relatedness\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"community_building\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"motivationType\": {\"primary\": \"Intrinsic/Extrinsic\", \"indicators\": [\"indicator1\", \"indicator2\"], \"sustainability\": \"High/Medium/Low\"},\n \"achievementGoals\": {\"mastery_focused\": \"X%\", \"performance_focused\": \"X%\", \"evidence\": [\"quote1\", \"quote2\"]},\n \"selfEfficacy\": {\"level\": \"High/Medium/Low\", \"building_strategies\": [\"strategy1\", \"strategy2\"]}\n },\n \"emotionalState\": {\n \"emotionalRegulation\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"support_needed\": [\"support1\"]},\n \"stressAnxiety\": {\"level\": \"High/Medium/Low\", \"indicators\": [\"indicator1\", \"indicator2\"], \"interventions\": [\"intervention1\"]},\n \"confidenceLevel\": {\"overall\": \"High/Medium/Low\", \"boosters\": [\"booster1\", \"booster2\"]},\n \"satisfactionMarkers\": {\"frequency\": \"High/Medium/Low\", \"sources\": [\"source1\", \"source2\"]}\n }\n}`;\n\n return await processGeminiRequest(behaviorPrompt, geminiApiKey);\n}\n\nasync function contentEffectivenessAnalysis(\n comments,\n videoDetails,\n geminiApiKey,\n) {\n const contentComments = comments.slice(0, 30).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n }));\n\n const contentPrompt = `\nAs a CURRICULUM DESIGN EXPERT, analyze content effectiveness.\n\nCONTENT FRAMEWORK:\n1. Curriculum Alignment\n2. Learning Objective Achievement\n3. Content Structure & Flow\n4. Engagement Analysis\n5. Accessibility Assessment\n\nComments: ${JSON.stringify(contentComments)}\n\nProvide detailed analysis:\n{\n \"curriculumAlignment\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"gaps\": [\"gap1\", \"gap2\"], \"improvements\": [\"improvement1\", \"improvement2\"]},\n \"learningObjectives\": {\"achievement_rate\": \"X%\", \"clear_objectives\": [\"objective1\", \"objective2\"], \"missed_objectives\": [\"missed1\", \"missed2\"]},\n \"contentStructure\": {\"flow_quality\": \"Excellent/Good/Poor\", \"logical_progression\": true, \"improvements\": [\"improvement1\", \"improvement2\"]},\n \"engagementLevel\": {\"overall\": \"High/Medium/Low\", \"peak_moments\": [\"moment1\", \"moment2\"], \"drop_points\": [\"point1\", \"point2\"]},\n \"accessibility\": {\"inclusive_design\": \"Excellent/Good/Poor\", \"barriers\": [\"barrier1\", \"barrier2\"], \"enhancements\": [\"enhancement1\", \"enhancement2\"]}\n}`;\n\n return await processGeminiRequest(contentPrompt, geminiApiKey);\n}\n\nasync function predictiveAnalyticsGeneration(\n comments,\n videoDetails,\n geminiApiKey,\n) {\n const predictiveComments = comments.slice(0, 25).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n }));\n\n const predictivePrompt = `\nAs a LEARNING ANALYTICS SPECIALIST, provide predictive insights.\n\nPREDICTIVE FRAMEWORK:\n1. Student Success Prediction\n2. Engagement Forecasting\n3. Intervention Recommendations\n4. Learning Outcome Projections\n\nComments: ${JSON.stringify(predictiveComments)}\n\nProvide predictive analysis:\n{\n \"studentSuccess\": {\"probability\": \"High/Medium/Low\", \"indicators\": [\"indicator1\", \"indicator2\"], \"risk_factors\": [\"risk1\", \"risk2\"]},\n \"engagementTrends\": {\"trajectory\": \"Increasing/Stable/Declining\", \"forecast\": \"detailed forecast\", \"interventions\": [\"intervention1\", \"intervention2\"]},\n \"learningOutcomes\": {\"projected_success_rate\": \"X%\", \"improvement_areas\": [\"area1\", \"area2\"], \"timeline\": \"detailed timeline\"},\n \"recommendations\": {\"immediate\": [\"action1\", \"action2\"], \"short_term\": [\"action3\", \"action4\"], \"long_term\": [\"action5\", \"action6\"]}\n}`;\n\n return await processGeminiRequest(predictivePrompt, geminiApiKey);\n}\n\nasync function processGeminiRequest(prompt, geminiApiKey) {\n const enhancedPrompt = `\nCONTEXT: You are analyzing educational YouTube comments with 20+ years of expertise.\n\nINSTRUCTIONS:\n- Use EVIDENCE-BASED reasoning for every claim\n- Provide SPECIFIC student quotes to support analysis\n- Give MEASURABLE recommendations with clear action steps\n- Consider DIVERSE learning styles and backgrounds\n- Focus on ACTIONABLE insights for educational improvement\n\nQUALITY STANDARDS:\n- Every score must be justified with evidence from student comments\n- Every recommendation must be specific and implementable\n- Every insight must cite actual student feedback as proof\n- Analysis must be educationally sound and research-based\n\n${prompt}\n\nCRITICAL: Return ONLY valid JSON. Be detailed while maintaining proper JSON structure.`;\n\n try {\n const response = await fetch(\n `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:generateContent?key=${geminiApiKey}`,\n {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{ parts: [{ text: enhancedPrompt }] }],\n generationConfig: {\n temperature: 0.2,\n topK: 40,\n topP: 0.8,\n maxOutputTokens: 8000,\n },\n }),\n },\n );\n\n const data = await response.json();\n\n if (data.candidates && data.candidates[0]?.content?.parts?.[0]?.text) {\n const aiText = data.candidates[0].content.parts[0].text;\n const jsonMatch = aiText.match(/\\{[\\s\\S]*\\}/);\n if (jsonMatch) {\n try {\n return JSON.parse(jsonMatch[0]);\n } catch (parseError) {\n console.error(\"JSON parse error:\", parseError);\n return {\n error: \"Failed to parse AI response\",\n rawText: jsonMatch[0],\n };\n }\n }\n }\n\n return { error: \"No valid response from AI\", rawResponse: data };\n } catch (error) {\n console.error(\"Gemini API error:\", error);\n return { error: \"API request failed\", details: error.message };\n }\n}\n\nfunction getAdvancedFallbackAnalysis() {\n return {\n teacherPerformance: {\n overallTeacherRating: {\n score: \"Processing...\",\n justification: \"AI analysis temporarily unavailable\",\n },\n teachingMethodology: {\n pedagogicalApproach: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n communicationExcellence: {\n verbalClarity: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n subjectMatterExpertise: {\n contentKnowledgeDepth: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n emotionalIntelligence: {\n studentEmotionalRecognition: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n detailedStrengths: [\"Analysis in progress...\"],\n criticalImprovements: [\"Processing recommendations...\"],\n teachingPersonality: \"AI analysis temporarily unavailable\",\n competitiveAdvantages: [\"Analysis pending...\"],\n },\n learningAnalytics: {\n cognitiveProcessing: {\n bloomsTaxonomyDistribution: {\n remember: \"0%\",\n understand: \"0%\",\n apply: \"0%\",\n analyze: \"0%\",\n evaluate: \"0%\",\n create: \"0%\",\n },\n cognitiveLoadAnalysis: {\n intrinsic: \"Processing...\",\n extraneous: \"Processing...\",\n germane: \"Processing...\",\n evidence: [],\n },\n },\n learningProgression: {\n knowledgeConstruction: {\n stage: \"Analyzing...\",\n evidence: [],\n next_steps: [],\n },\n skillDevelopment: {\n current_stage: \"Processing...\",\n progression_rate: \"Analyzing...\",\n },\n },\n },\n studentBehavior: {\n motivationPsychology: {\n selfDeterminationTheory: {\n autonomy: { level: \"Processing...\", evidence: [], support_needs: [] },\n competence: {\n level: \"Processing...\",\n evidence: [],\n development_areas: [],\n },\n relatedness: {\n level: \"Processing...\",\n evidence: [],\n community_building: [],\n },\n },\n },\n },\n contentEffectiveness: {\n curriculumAlignment: {\n score: \"Processing...\",\n analysis: \"AI analysis in progress\",\n gaps: [],\n improvements: [],\n },\n },\n predictiveInsights: {\n studentSuccess: {\n probability: \"Analyzing...\",\n indicators: [],\n risk_factors: [],\n },\n engagementTrends: {\n trajectory: \"Processing...\",\n forecast: \"Analysis pending\",\n interventions: [],\n },\n },\n analysisDepth: \"Fallback Analysis - AI Temporarily Unavailable\",\n totalInsightCategories: 0,\n passesCompleted: 0,\n };\n}\n\nconst requestCounts = new Map();\nconst RATE_LIMIT = 8;\nconst RATE_WINDOW = 60000;\n\nasync function rateLimitCheck(req) {\n const clientIP = req.headers.get(\"x-forwarded-for\") || \"unknown\";\n const now = Date.now();\n\n if (!requestCounts.has(clientIP)) {\n requestCounts.set(clientIP, []);\n }\n\n const requests = requestCounts.get(clientIP);\n const validRequests = requests.filter((timestamp) =>\n now - timestamp < RATE_WINDOW\n );\n\n if (validRequests.length >= RATE_LIMIT) {\n throw new Error(\n \"Rate limit exceeded. Enhanced analysis requires more resources - please wait before making another request.\",\n );\n }\n\n validRequests.push(now);\n requestCounts.set(clientIP, validRequests);\n}\n\nasync function fetchYouTubeCommentsWithRetry(videoId, apiKey, maxRetries = 3) {\n for (let attempt = 1; attempt <= maxRetries; attempt++) {\n try {\n return await fetchYouTubeComments(videoId, apiKey);\n } catch (error) {\n if (attempt === maxRetries) throw error;\n await new Promise((resolve) => setTimeout(resolve, attempt * 2000));\n }\n }\n}\n\nasync function fetchVideoDetailsWithRetry(videoId, apiKey, maxRetries = 3) {\n for (let attempt = 1; attempt <= maxRetries; attempt++) {\n try {\n return await fetchVideoDetails(videoId, apiKey);\n } catch (error) {\n if (attempt === maxRetries) throw error;\n await new Promise((resolve) => setTimeout(resolve, attempt * 1000));\n }\n }\n}\n\nasync function fetchYouTubeComments(videoId, apiKey) {\n const comments = [];\n const maxCommentsLimit = 1000;\n\n try {\n const timeComments = await fetchCommentsByOrder(\n videoId,\n apiKey,\n \"time\",\n 500,\n );\n comments.push(...timeComments);\n\n if (comments.length < maxCommentsLimit) {\n const relevanceComments = await fetchCommentsByOrder(\n videoId,\n apiKey,\n \"relevance\",\n maxCommentsLimit - comments.length,\n );\n const newComments = relevanceComments.filter((newComment) =>\n !comments.some((existingComment) =>\n existingComment.id === newComment.id ||\n (existingComment.textOriginal === newComment.textOriginal &&\n existingComment.author === newComment.author)\n )\n );\n comments.push(...newComments);\n }\n\n return comments.slice(0, maxCommentsLimit).sort((a, b) =>\n new Date(b.publishedAt) - new Date(a.publishedAt)\n );\n } catch (error) {\n console.error(\"Error in comment collection:\", error);\n return comments.slice(0, maxCommentsLimit);\n }\n}\n\nasync function fetchCommentsByOrder(videoId, apiKey, order, remainingLimit) {\n const comments = [];\n let nextPageToken = \"\";\n const maxPages = 5;\n let pageCount = 0;\n\n try {\n do {\n if (comments.length >= remainingLimit || pageCount >= maxPages) break;\n\n const url =\n `https://www.googleapis.com/youtube/v3/commentThreads?part=snippet,replies&videoId=${videoId}&key=${apiKey}&maxResults=100&order=${order}${\n nextPageToken ? `&pageToken=${nextPageToken}` : \"\"\n }`;\n\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error || !data.items || data.items.length === 0) break;\n\n data.items.forEach((item) => {\n if (comments.length >= remainingLimit) return;\n\n const comment = item.snippet.topLevelComment.snippet;\n comments.push({\n id: item.id,\n text: comment.textDisplay,\n textOriginal: comment.textOriginal,\n author: comment.authorDisplayName,\n likeCount: comment.likeCount || 0,\n publishedAt: comment.publishedAt,\n replyCount: item.snippet.totalReplyCount || 0,\n isReply: false,\n fetchMethod: order,\n });\n\n if (\n item.replies && item.replies.comments &&\n comments.length < remainingLimit\n ) {\n item.replies.comments.forEach((reply) => {\n if (comments.length >= remainingLimit) return;\n const replySnippet = reply.snippet;\n comments.push({\n id: reply.id,\n text: replySnippet.textDisplay,\n textOriginal: replySnippet.textOriginal,\n author: replySnippet.authorDisplayName,\n likeCount: replySnippet.likeCount || 0,\n publishedAt: replySnippet.publishedAt,\n replyCount: 0,\n isReply: true,\n fetchMethod: order,\n });\n });\n }\n });\n\n nextPageToken = data.nextPageToken;\n pageCount++;\n\n if (nextPageToken && pageCount < maxPages) {\n await new Promise((resolve) => setTimeout(resolve, 200));\n }\n } while (\n nextPageToken && pageCount < maxPages && comments.length < remainingLimit\n );\n\n return comments;\n } catch (error) {\n console.error(`Error fetching ${order} comments:`, error);\n return comments;\n }\n}\n\nasync function fetchVideoDetails(videoId, apiKey) {\n const url =\n `https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics&id=${videoId}&key=${apiKey}`;\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error) throw new Error(`YouTube API Error: ${data.error.message}`);\n if (!data.items || data.items.length === 0) {\n throw new Error(\"Video not found\");\n }\n\n const video = data.items[0];\n return {\n title: video.snippet.title,\n channel: video.snippet.channelTitle,\n publishedAt: video.snippet.publishedAt,\n viewCount: parseInt(video.statistics.viewCount || 0),\n likeCount: parseInt(video.statistics.likeCount || 0),\n commentCount: parseInt(video.statistics.commentCount || 0),\n };\n}\n\nfunction analyzeCommentsEdTech(comments) {\n if (comments.length === 0) {\n return {\n message: \"No comments found for analysis\",\n suggestions: [\n \"Check video ID\",\n \"Ensure video is public\",\n \"Verify comments are enabled\",\n ],\n };\n }\n\n return {\n sentiment: analyzeSentiment(comments),\n keywords: extractKeywords(comments),\n engagement: analyzeEngagement(comments),\n timeDistribution: analyzeTimeDistribution(comments),\n topComments: getTopComments(comments, 5),\n statistics: getStatistics(comments),\n emojis: analyzeEmojis(comments),\n questions: findQuestions(comments),\n authors: analyzeAuthors(comments),\n breakdown: analyzeCommentBreakdown(comments),\n edtech: {\n teacherFeedback: analyzeTeacherFeedback(comments),\n learningOutcomes: analyzeLearningOutcomes(comments),\n },\n };\n}\n\nfunction analyzeSentiment(comments) {\n const positiveWords = [\n \"love\",\n \"great\",\n \"awesome\",\n \"excellent\",\n \"good\",\n \"wonderful\",\n \"fantastic\",\n \"amazing\",\n \"best\",\n \"perfect\",\n \"helpful\",\n \"thanks\",\n \"brilliant\",\n ];\n const negativeWords = [\n \"hate\",\n \"bad\",\n \"terrible\",\n \"awful\",\n \"worst\",\n \"horrible\",\n \"boring\",\n \"waste\",\n \"stupid\",\n \"disappointed\",\n ];\n\n let positive = 0, negative = 0, neutral = 0;\n\n comments.forEach((comment) => {\n const text = comment.textOriginal.toLowerCase();\n let positiveScore = 0, negativeScore = 0;\n\n positiveWords.forEach((word) => {\n if (text.includes(word)) positiveScore++;\n });\n\n negativeWords.forEach((word) => {\n if (text.includes(word)) negativeScore++;\n });\n\n if (positiveScore > negativeScore) positive++;\n else if (negativeScore > positiveScore) negative++;\n else neutral++;\n });\n\n const total = comments.length;\n return {\n positive: {\n count: positive,\n percentage: ((positive / total) * 100).toFixed(1) + \"%\",\n },\n negative: {\n count: negative,\n percentage: ((negative / total) * 100).toFixed(1) + \"%\",\n },\n neutral: {\n count: neutral,\n percentage: ((neutral / total) * 100).toFixed(1) + \"%\",\n },\n overallScore: parseFloat(((positive - negative) / total * 100).toFixed(1)),\n };\n}\n\nfunction extractKeywords(comments) {\n const wordFrequency = {};\n const stopWords = new Set([\n \"the\",\n \"is\",\n \"at\",\n \"which\",\n \"on\",\n \"a\",\n \"an\",\n \"and\",\n \"or\",\n \"but\",\n \"in\",\n \"with\",\n \"to\",\n \"for\",\n \"of\",\n \"as\",\n \"from\",\n \"this\",\n \"that\",\n \"it\",\n \"are\",\n \"was\",\n \"be\",\n \"been\",\n \"being\",\n \"have\",\n \"has\",\n \"had\",\n \"do\",\n \"does\",\n \"did\",\n \"will\",\n \"would\",\n \"could\",\n \"should\",\n \"may\",\n \"might\",\n \"must\",\n \"can\",\n \"i\",\n \"you\",\n \"he\",\n \"she\",\n \"we\",\n \"they\",\n \"what\",\n \"where\",\n \"when\",\n \"why\",\n \"how\",\n \"not\",\n \"no\",\n \"yes\",\n \"my\",\n \"your\",\n \"his\",\n \"her\",\n \"its\",\n \"our\",\n \"their\",\n \"me\",\n \"him\",\n \"her\",\n \"us\",\n \"them\",\n ]);\n\n comments.forEach((comment) => {\n const cleanText = comment.textOriginal\n .replace(/<[^>]*>/g, \"\")\n .replace(/https?:\\/\\/[^\\s]+/g, \"\")\n .replace(/[@#]\\w+/g, \"\")\n .toLowerCase();\n\n const words = cleanText.match(/\\b[a-z]{3,}\\b/g) || [];\n words.forEach((word) => {\n if (!stopWords.has(word)) {\n wordFrequency[word] = (wordFrequency[word] || 0) + 1;\n }\n });\n });\n\n return Object.entries(wordFrequency)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 15)\n .map(([word, count]) => ({\n word,\n count,\n percentage: ((count / comments.length) * 100).toFixed(1) + \"%\",\n }));\n}\n\nfunction analyzeEngagement(comments) {\n const totalLikes = comments.reduce(\n (sum, comment) => sum + comment.likeCount,\n 0,\n );\n const totalReplies = comments.reduce(\n (sum, comment) => sum + comment.replyCount,\n 0,\n );\n const avgLikes = comments.length > 0 ? (totalLikes / comments.length) : 0;\n const maxLikes = Math.max(...comments.map((c) => c.likeCount), 0);\n\n return {\n totalLikes,\n totalReplies,\n averageLikesPerComment: parseFloat(avgLikes.toFixed(2)),\n highestLikeCount: maxLikes,\n commentsWithLikes: comments.filter((c) => c.likeCount > 0).length,\n commentsWithReplies: comments.filter((c) => c.replyCount > 0).length,\n engagementRate:\n ((comments.filter((c) => c.likeCount > 0 || c.replyCount > 0).length /\n comments.length) * 100).toFixed(1) + \"%\",\n };\n}\n\nfunction analyzeTimeDistribution(comments) {\n const now = new Date();\n const timeRanges = {\n lastHour: 0,\n last24Hours: 0,\n lastWeek: 0,\n lastMonth: 0,\n lastYear: 0,\n older: 0,\n };\n\n comments.forEach((comment) => {\n const commentDate = new Date(comment.publishedAt);\n const diffMs = now - commentDate;\n const diffHours = diffMs / (1000 * 60 * 60);\n const diffDays = diffHours / 24;\n\n if (diffHours <= 1) timeRanges.lastHour++;\n else if (diffHours <= 24) timeRanges.last24Hours++;\n else if (diffDays <= 7) timeRanges.lastWeek++;\n else if (diffDays <= 30) timeRanges.lastMonth++;\n else if (diffDays <= 365) timeRanges.lastYear++;\n else timeRanges.older++;\n });\n\n return { timeRanges };\n}\n\nfunction getTopComments(comments, limit = 5) {\n return comments\n .sort((a, b) => (b.likeCount + b.replyCount) - (a.likeCount + a.replyCount))\n .slice(0, limit)\n .map((comment, index) => ({\n rank: index + 1,\n author: comment.author,\n text: comment.textOriginal.substring(0, 200) +\n (comment.textOriginal.length > 200 ? \"...\" : \"\"),\n likes: comment.likeCount,\n replies: comment.replyCount,\n totalEngagement: comment.likeCount + comment.replyCount,\n }));\n}\n\nfunction getStatistics(comments) {\n const lengths = comments.map((c) => c.textOriginal.length);\n const wordCounts = comments.map((c) => c.textOriginal.split(\" \").length);\n\n return {\n totalComments: comments.length,\n averageLength: Math.round(\n lengths.reduce((a, b) => a + b, 0) / lengths.length,\n ),\n averageWordCount: Math.round(\n wordCounts.reduce((a, b) => a + b, 0) / wordCounts.length,\n ),\n uniqueAuthors: new Set(comments.map((c) => c.author)).size,\n totalLikes: comments.reduce((sum, c) => sum + c.likeCount, 0),\n totalReplies: comments.reduce((sum, c) => sum + c.replyCount, 0),\n };\n}\n\nfunction analyzeEmojis(comments) {\n const emojiRegex =\n /[\\u{1F300}-\\u{1F9FF}]|[\\u{2600}-\\u{26FF}]|[\\u{2700}-\\u{27BF}]/gu;\n const emojiCount = {};\n let totalEmojis = 0;\n let commentsWithEmojis = 0;\n\n comments.forEach((comment) => {\n const emojis = comment.textOriginal.match(emojiRegex) || [];\n if (emojis.length > 0) {\n commentsWithEmojis++;\n emojis.forEach((emoji) => {\n emojiCount[emoji] = (emojiCount[emoji] || 0) + 1;\n totalEmojis++;\n });\n }\n });\n\n const topEmojis = Object.entries(emojiCount)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 10)\n .map(([emoji, count]) => ({ emoji, count }));\n\n return {\n totalEmojis,\n commentsWithEmojis,\n topEmojis,\n emojiUsageRate: ((commentsWithEmojis / comments.length) * 100).toFixed(1) +\n \"%\",\n };\n}\n\nfunction findQuestions(comments) {\n const questions = comments.filter((comment) =>\n comment.textOriginal.includes(\"?\") ||\n comment.textOriginal.toLowerCase().match(\n /^(what|where|when|why|how|who|which|is|are|can|could|would|will|do|does|did|should|has|have)/i,\n )\n );\n\n return {\n totalQuestions: questions.length,\n questionRate: ((questions.length / comments.length) * 100).toFixed(1) + \"%\",\n topQuestions: questions\n .sort((a, b) => b.likeCount - a.likeCount)\n .slice(0, 5)\n .map((q, index) => ({\n rank: index + 1,\n author: q.author,\n question: q.textOriginal.substring(0, 150) +\n (q.textOriginal.length > 150 ? \"...\" : \"\"),\n likes: q.likeCount,\n replies: q.replyCount,\n })),\n };\n}\n\nfunction analyzeAuthors(comments) {\n const authorStats = {};\n\n comments.forEach((comment) => {\n if (!authorStats[comment.author]) {\n authorStats[comment.author] = {\n commentCount: 0,\n totalLikes: 0,\n totalReplies: 0,\n };\n }\n authorStats[comment.author].commentCount++;\n authorStats[comment.author].totalLikes += comment.likeCount;\n authorStats[comment.author].totalReplies += comment.replyCount;\n });\n\n return {\n uniqueAuthors: Object.keys(authorStats).length,\n topContributors: Object.entries(authorStats)\n .sort((a, b) => b[1].totalLikes - a[1].totalLikes)\n .slice(0, 5)\n .map(([author, stats]) => ({ author, ...stats })),\n };\n}\n\nfunction analyzeCommentBreakdown(comments) {\n const topLevelComments = comments.filter((c) => !c.isReply);\n const replies = comments.filter((c) => c.isReply);\n\n return {\n totalFetched: comments.length,\n topLevelComments: topLevelComments.length,\n repliesFetched: replies.length,\n averageLikes:\n (comments.reduce((sum, c) => sum + c.likeCount, 0) / comments.length)\n .toFixed(1),\n engagementRate:\n ((comments.filter((c) => c.likeCount > 0 || c.replyCount > 0).length /\n comments.length) * 100).toFixed(1) + \"%\",\n };\n}\n\nfunction analyzeTeacherFeedback(comments) {\n const teacherKeywords = {\n positive: [\n \"great teacher\",\n \"excellent explanation\",\n \"clear\",\n \"helpful\",\n \"amazing instructor\",\n ],\n negative: [\n \"confusing\",\n \"too fast\",\n \"unclear\",\n \"bad explanation\",\n \"hard to follow\",\n ],\n };\n\n let teacherMentions = 0;\n let positiveTeacher = 0;\n let negativeTeacher = 0;\n\n comments.forEach((comment) => {\n const text = comment.textOriginal.toLowerCase();\n\n if (\n text.includes(\"teacher\") || text.includes(\"instructor\") ||\n text.includes(\"you\")\n ) {\n teacherMentions++;\n\n teacherKeywords.positive.forEach((keyword) => {\n if (text.includes(keyword)) positiveTeacher++;\n });\n\n teacherKeywords.negative.forEach((keyword) => {\n if (text.includes(keyword)) negativeTeacher++;\n });\n }\n });\n\n return {\n totalTeacherMentions: teacherMentions,\n positiveTeacherFeedback: positiveTeacher,\n negativeTeacherFeedback: negativeTeacher,\n teacherRating: teacherMentions > 0\n ? ((positiveTeacher - negativeTeacher) / teacherMentions * 100).toFixed(\n 1,\n ) + \"%\"\n : \"No data\",\n };\n}\n\nfunction analyzeLearningOutcomes(comments) {\n const outcomeKeywords = {\n success: [\n \"finally understood\",\n \"got it\",\n \"makes sense now\",\n \"cleared my doubt\",\n \"helped me pass\",\n ],\n struggle: [\n \"still confused\",\n \"dont get it\",\n \"need help\",\n \"lost\",\n \"difficult\",\n ],\n };\n\n let successIndicators = 0;\n let struggleIndicators = 0;\n\n comments.forEach((comment) => {\n const text = comment.textOriginal.toLowerCase();\n\n outcomeKeywords.success.forEach((keyword) => {\n if (text.includes(keyword)) successIndicators++;\n });\n\n outcomeKeywords.struggle.forEach((keyword) => {\n if (text.includes(keyword)) struggleIndicators++;\n });\n });\n\n return {\n successIndicators,\n struggleIndicators,\n learningSuccessRate: comments.length > 0\n ? ((successIndicators / comments.length) * 100).toFixed(1) + \"%\"\n : \"0%\",\n };\n}\n\nfunction generateEnhancedDashboardHTML(video, analysis) {\n return `\n \n \n \n Enhanced EdTech Analysis - ${video.title}\n \n \n \n \n \n

\n \n \n

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

Student Comments Analyzed

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

Overall Teacher Rating

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

Learning Success Rate

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

AI Analysis Passes

\n\n

🎓 AI Teacher Performance Analysis

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

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

\n\n

📊 Statistical Analysis Summary

😊 Sentiment Distribution

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

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

❓ Questions Analysis

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

👥 Community Engagement

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

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

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

\n \n \n

🚀 Start Enhanced Analysis

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

\n \n \n \n \n

\n\n

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

🧠 35+ Categories: Comprehensive educational analytics

👥 Multi-User Ready: Built for educational institutions

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

Error: ${error}

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

API Quota Exceeded

Please try again later.

`;\n}",[],[181],"files",[149,170,179],"counts",{"_193":32,"_194":195,"_196":32,"_197":198},"pulls","branches",1,"forks","envVars",2,"contents",[],"file",{"_103":171,"_155":137,"_152":172,"_95":99,"_163":176,"_161":162,"_100":175,"_154":-5,"_105":203,"_156":173,"_166":-5,"_98":204},["D",1757364768055],[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,"_267":268,"_280":-7,"_281":32,"_282":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":171,"_95":99,"_152":172,"_154":-5,"_155":137,"_156":173,"_157":158,"_105":219,"_100":175,"_161":162,"_163":176,"_165":22,"_166":-5,"_98":220},["D",1757364768055],[99],"history",[223,225,231,236,241,246,251,256,260,263],{"_103":171,"_155":137,"_152":172,"_95":99,"_163":176,"_161":162,"_100":175,"_154":-5,"_105":224,"_156":173,"_166":-5},["D",1757364768055],{"_103":226,"_155":137,"_152":172,"_95":99,"_163":227,"_161":162,"_100":228,"_154":-5,"_105":229,"_156":230,"_166":-5},"5dd73864-8cf5-11f0-a236-0224a6c84d84","/** @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.strip();\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 - use Deno.env.get in Val Town\n const apiKey = Deno.env.get(\"YOUTUBE_API_KEY\");\n if (!apiKey) {\n throw new Error(\"YouTube API key not configured\");\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

✅ 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 {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;",8,["D",1757364591764],26,{"_103":232,"_155":137,"_152":172,"_95":99,"_163":233,"_161":162,"_100":185,"_154":-5,"_105":234,"_156":235,"_166":-5},"d65cb170-8cf4-11f0-a2f5-0224a6c84d84","/** @jsxImportSource https://esm.sh/react */\nimport React, { useState, useEffect } from \"https://esm.sh/react\";\nimport { YOUTUBE_API_KEY } from \"std/env\";\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: ${webhookResponse.status}`);\n }\n \n const analysisResult = await webhookResponse.json();\n \n return {\n success: true,\n comment_fetch_summary: {\n total_fetched: commentResult.total_fetched,\n api_requests_made: commentResult.requests_made,\n video_info: videoInfo,\n fetch_errors: commentResult.had_errors\n },\n analysis_result: analysisResult,\n processing_time: (Date.now() - processingStart) / 1000\n };\n \n } catch (error) {\n return {\n success: false,\n error: error.message,\n video_url: videoUrl,\n processing_time: (Date.now() - processingStart) / 1000\n };\n }\n }\n}\n\n// Main React Component\nfunction YouTubeAnalyzer({ url }) {\n const [videoUrl, setVideoUrl] = useState(\"\");\n const [analysis, setAnalysis] = useState(null);\n const [loading, setLoading] = useState(false);\n const [error, setError] = useState(null);\n\n const urlParams = new URLSearchParams(url?.searchParams);\n const analyzeParam = urlParams.get('analyze');\n const videoParam = urlParams.get('video');\n\n useEffect(() => {\n if (analyzeParam === 'true' && videoParam) {\n performAnalysis(videoParam);\n }\n }, [analyzeParam, videoParam]);\n\n const performAnalysis = async (video) => {\n setLoading(true);\n setError(null);\n \n try {\n const apiKey = YOUTUBE_API_KEY;\n if (!apiKey) {\n throw new Error(\"YouTube API key not configured\");\n }\n\n const n8nWebhookUrl = \"https://n8n.vedantu.com/webhook/youtube-comments\";\n const processor = new YouTubeCommentProcessor(apiKey, n8nWebhookUrl);\n const result = await processor.sendToN8nForAnalysis(video, 100);\n \n if (!result.success) {\n throw new Error(result.error);\n }\n \n setAnalysis(result.analysis_result);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n const handleSubmit = (e) => {\n e.preventDefault();\n if (!videoUrl.trim()) {\n setError(\"Please enter a YouTube video URL\");\n return;\n }\n \n const newUrl = `${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

✅ 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 {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;",["D",1757364364466],25,{"_103":237,"_155":137,"_152":172,"_95":99,"_163":238,"_161":162,"_100":239,"_154":-5,"_105":240,"_156":228,"_166":-5},"784c2d3c-8663-11f0-a2fe-0224a6c84d84","// Complete YouTube Comment Analysis Tool with Maximum Collection (1000 Comments)\n// Enhanced HTTP Val for Val Town\n\nexport default async function server(req: Request): Promise {\n const url = new URL(req.url);\n const videoId = url.searchParams.get(\"videoId\");\n const format = url.searchParams.get(\"format\");\n\n // Show main interface if no videoId\n if (!videoId) {\n return new Response(generateMainInterface(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n // Get API keys from environment\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: \"Go to Val Town Settings → Secrets and add both API keys\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n try {\n // Fetch video data\n const [videoDetails, comments] = await Promise.all([\n fetchVideoDetails(videoId, youtubeApiKey),\n fetchYouTubeComments(videoId, youtubeApiKey),\n ]);\n\n // Analyze comments\n const basicAnalysis = analyzeComments(comments);\n\n // Enhance with Gemini AI\n const geminiInsights = await enhanceWithGemini(\n comments,\n videoDetails,\n geminiApiKey,\n );\n\n // Combine analyses\n const completeAnalysis = {\n ...basicAnalysis,\n aiInsights: geminiInsights,\n };\n\n // Return dashboard view\n if (format === \"dashboard\") {\n return new Response(\n generateDashboardHTML(videoDetails, completeAnalysis),\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n }\n\n // Return JSON data\n return new Response(\n JSON.stringify(\n {\n success: true,\n analyzedAt: new Date().toISOString(),\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(\"Analysis error:\", error);\n return new Response(generateErrorHTML(error.message), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n}\n\n// MAXIMUM COMMENT COLLECTION - Up to 1000 Comments Per Video\nasync function fetchYouTubeComments(videoId, apiKey, maxResults = 100) {\n const comments = [];\n const maxCommentsLimit = 1000; // Hard limit per video\n let totalFetched = 0;\n\n console.log(\n `🚀 Starting MAXIMUM comment collection for video: ${videoId} (limit: ${maxCommentsLimit})`,\n );\n\n try {\n // Phase 1: Time-ordered comments (most recent first)\n if (totalFetched < maxCommentsLimit) {\n console.log(\"📅 Phase 1: Fetching time-ordered comments...\");\n const timeComments = await fetchCommentsByOrder(\n videoId,\n apiKey,\n \"time\",\n maxCommentsLimit - totalFetched,\n );\n comments.push(...timeComments);\n totalFetched = comments.length;\n console.log(\n `✅ Time order: ${timeComments.length} comments (Total: ${totalFetched})`,\n );\n }\n\n // Phase 2: Relevance-ordered comments (different set)\n if (totalFetched < maxCommentsLimit) {\n console.log(\"⭐ Phase 2: Fetching relevance-ordered comments...\");\n const relevanceComments = await fetchCommentsByOrder(\n videoId,\n apiKey,\n \"relevance\",\n maxCommentsLimit - totalFetched,\n );\n\n // Add only new comments (avoid duplicates)\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\n comments.push(...newComments);\n totalFetched = comments.length;\n console.log(\n `✅ Relevance order: ${newComments.length} new comments (Total: ${totalFetched})`,\n );\n }\n\n // Phase 3: Fetch additional replies for comments with many replies\n if (totalFetched < maxCommentsLimit) {\n console.log(\"💬 Phase 3: Fetching additional replies...\");\n const additionalReplies = await fetchAdditionalReplies(\n comments,\n videoId,\n apiKey,\n maxCommentsLimit - totalFetched,\n );\n comments.push(...additionalReplies);\n totalFetched = comments.length;\n console.log(\n `✅ Additional replies: ${additionalReplies.length} replies (Total: ${totalFetched})`,\n );\n }\n\n // Final cleanup and sorting\n const finalComments = comments\n .slice(0, maxCommentsLimit) // Ensure we don't exceed limit\n .sort((a, b) => new Date(b.publishedAt) - new Date(a.publishedAt)); // Sort by newest first\n\n console.log(\n `🎉 FINAL COLLECTION COMPLETE: ${finalComments.length} comments`,\n );\n console.log(\n `📊 Breakdown: ${\n finalComments.filter((c) => !c.isReply).length\n } top-level + ${finalComments.filter((c) => c.isReply).length} replies`,\n );\n\n return finalComments;\n } catch (error) {\n console.error(\"Error in maximum comment collection:\", error);\n return comments.slice(0, maxCommentsLimit); // Return what we have\n }\n}\n\nasync function fetchCommentsByOrder(videoId, apiKey, order, remainingLimit) {\n const comments = [];\n let nextPageToken = \"\";\n let pageCount = 0;\n const maxPages = Math.ceil(remainingLimit / 100); // Calculate max pages needed\n\n try {\n do {\n // Break if we've reached our limit\n if (comments.length >= remainingLimit) {\n console.log(`Reached limit of ${remainingLimit} for ${order} order`);\n break;\n }\n\n const url = `https://www.googleapis.com/youtube/v3/commentThreads?` +\n `part=snippet,replies&videoId=${videoId}&key=${apiKey}&maxResults=100&order=${order}` +\n (nextPageToken ? `&pageToken=${nextPageToken}` : \"\");\n\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error) {\n console.log(\n `API Error on ${order} page ${pageCount + 1}:`,\n data.error.message,\n );\n break;\n }\n\n if (!data.items || data.items.length === 0) {\n console.log(`No more items available for ${order} order`);\n break;\n }\n\n // Process each comment thread\n data.items.forEach((item) => {\n if (comments.length >= remainingLimit) return; // Stop if limit reached\n\n const comment = item.snippet.topLevelComment.snippet;\n\n // Add top-level comment\n comments.push({\n id: item.id,\n text: comment.textDisplay,\n textOriginal: comment.textOriginal,\n author: comment.authorDisplayName,\n authorChannelId: comment.authorChannelId?.value,\n likeCount: comment.likeCount || 0,\n publishedAt: comment.publishedAt,\n replyCount: item.snippet.totalReplyCount || 0,\n isReply: false,\n commentType: \"top-level\",\n fetchMethod: order,\n });\n\n // Add replies if they exist and we have space\n if (\n item.replies && item.replies.comments &&\n comments.length < remainingLimit\n ) {\n item.replies.comments.forEach((reply) => {\n if (comments.length >= remainingLimit) return;\n\n const replySnippet = reply.snippet;\n comments.push({\n id: reply.id,\n text: replySnippet.textDisplay,\n textOriginal: replySnippet.textOriginal,\n author: replySnippet.authorDisplayName,\n authorChannelId: replySnippet.authorChannelId?.value,\n likeCount: replySnippet.likeCount || 0,\n publishedAt: replySnippet.publishedAt,\n replyCount: 0,\n isReply: true,\n commentType: \"reply\",\n parentId: item.id,\n parentAuthor: comment.authorDisplayName,\n fetchMethod: order,\n });\n });\n }\n });\n\n nextPageToken = data.nextPageToken;\n pageCount++;\n\n console.log(\n `${order} - Page ${pageCount}: +${data.items.length} threads, Total comments: ${comments.length}/${remainingLimit}`,\n );\n\n // Rate limiting to avoid quota issues\n if (\n nextPageToken && pageCount < maxPages &&\n comments.length < remainingLimit\n ) {\n await new Promise((resolve) => setTimeout(resolve, 150));\n }\n } while (\n nextPageToken && pageCount < maxPages && comments.length < remainingLimit\n );\n\n console.log(\n `${order} order complete: ${pageCount} pages, ${comments.length} comments collected`,\n );\n return comments;\n } catch (error) {\n console.error(`Error fetching ${order} comments:`, error);\n return comments;\n }\n}\n\nasync function fetchAdditionalReplies(\n existingComments,\n videoId,\n apiKey,\n remainingLimit,\n) {\n const additionalReplies = [];\n\n // Find comments with high reply counts that might have more replies\n const highReplyComments = existingComments\n .filter((c) => !c.isReply && c.replyCount > 5)\n .sort((a, b) => b.replyCount - a.replyCount)\n .slice(0, 20); // Top 20 comments with most replies\n\n console.log(\n `🔍 Fetching additional replies for ${highReplyComments.length} high-engagement comments...`,\n );\n\n for (const comment of highReplyComments) {\n if (additionalReplies.length >= remainingLimit) break;\n\n try {\n let nextPageToken = \"\";\n let replyPageCount = 0;\n const maxReplyPages = 3; // Limit reply pages per comment\n\n do {\n const url = `https://www.googleapis.com/youtube/v3/comments?` +\n `part=snippet&parentId=${comment.id}&key=${apiKey}&maxResults=100` +\n (nextPageToken ? `&pageToken=${nextPageToken}` : \"\");\n\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error || !data.items) break;\n\n data.items.forEach((reply) => {\n if (additionalReplies.length >= remainingLimit) return;\n\n // Check if we already have this reply\n const alreadyExists = existingComments.some((c) =>\n c.id === reply.id\n ) ||\n additionalReplies.some((c) => c.id === reply.id);\n\n if (!alreadyExists) {\n const replySnippet = reply.snippet;\n additionalReplies.push({\n id: reply.id,\n text: replySnippet.textDisplay,\n textOriginal: replySnippet.textOriginal,\n author: replySnippet.authorDisplayName,\n authorChannelId: replySnippet.authorChannelId?.value,\n likeCount: replySnippet.likeCount || 0,\n publishedAt: replySnippet.publishedAt,\n replyCount: 0,\n isReply: true,\n commentType: \"additional-reply\",\n parentId: comment.id,\n parentAuthor: comment.author,\n fetchMethod: \"detailed\",\n });\n }\n });\n\n nextPageToken = data.nextPageToken;\n replyPageCount++;\n\n // Rate limiting for reply fetching\n if (nextPageToken && replyPageCount < maxReplyPages) {\n await new Promise((resolve) => setTimeout(resolve, 100));\n }\n } while (\n nextPageToken && replyPageCount < maxReplyPages &&\n additionalReplies.length < remainingLimit\n );\n } catch (error) {\n console.log(\n `Error fetching additional replies for comment ${comment.id}:`,\n error.message,\n );\n }\n }\n\n console.log(\n `✅ Additional reply collection: ${additionalReplies.length} new replies found`,\n );\n return additionalReplies;\n}\n\n// Fetch video details\nasync function fetchVideoDetails(videoId, apiKey) {\n const url =\n `https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics&id=${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: ${data.error.message}`);\n if (!data.items || data.items.length === 0) {\n throw new Error(\"Video not found\");\n }\n\n const video = data.items[0];\n return {\n title: video.snippet.title,\n channel: video.snippet.channelTitle,\n publishedAt: video.snippet.publishedAt,\n viewCount: parseInt(video.statistics.viewCount || 0),\n likeCount: parseInt(video.statistics.likeCount || 0),\n commentCount: parseInt(video.statistics.commentCount || 0),\n };\n}\n\n// Gemini AI Integration\nasync function enhanceWithGemini(comments, videoDetails, geminiApiKey) {\n try {\n const sampleComments = comments.slice(0, 30).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const prompt =\n `As an expert social media analyst, analyze these YouTube comments for the video \"${videoDetails.title}\" by ${videoDetails.channel}.\n\nComments data: ${JSON.stringify(sampleComments)}\n\nVideo stats: ${videoDetails.viewCount} views, ${videoDetails.likeCount} likes, ${videoDetails.commentCount} total comments.\n\nProvide insights in this exact JSON format:\n{\n \"audienceProfile\": \"Description of the audience demographic and behavior\",\n \"contentReception\": \"How the audience is receiving this content\",\n \"keyTopics\": [\"topic1\", \"topic2\", \"topic3\"],\n \"engagementInsights\": \"Analysis of engagement patterns\",\n \"recommendations\": [\"recommendation1\", \"recommendation2\", \"recommendation3\"],\n \"trendingPhrases\": [\"phrase1\", \"phrase2\"],\n \"emotionalTones\": [\"tone1\", \"tone2\"],\n \"actionableInsights\": \"Specific actions the creator should take\"\n}\n\nFocus on marketing-relevant insights that non-technical teams can understand and act upon.`;\n\n const response = await fetch(\n `https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=${geminiApiKey}`,\n {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{ text: prompt }],\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 return JSON.parse(jsonMatch[0]);\n }\n }\n\n return {\n audienceProfile: \"Analysis unavailable - using basic metrics\",\n contentReception: \"Mixed engagement patterns observed\",\n keyTopics: [\"General discussion\"],\n engagementInsights: \"Standard engagement levels\",\n recommendations: [\n \"Monitor comments regularly\",\n \"Engage with top commenters\",\n ],\n trendingPhrases: [\"No specific trends\"],\n emotionalTones: [\"Neutral\"],\n actionableInsights: \"Continue current content strategy\",\n };\n } catch (error) {\n console.error(\"Gemini AI error:\", error);\n return {\n audienceProfile: \"AI analysis temporarily unavailable\",\n contentReception: \"Using statistical analysis only\",\n keyTopics: [\"Analysis pending\"],\n engagementInsights: \"Basic metrics available\",\n recommendations: [\"Retry analysis later\"],\n trendingPhrases: [\"Data processing\"],\n emotionalTones: [\"Neutral\"],\n actionableInsights: \"Check back for AI insights\",\n };\n }\n}\n\n// Enhanced breakdown analysis for maximum collection\nfunction analyzeCommentBreakdown(comments) {\n const topLevelComments = comments.filter((c) => !c.isReply);\n const replies = comments.filter((c) => c.isReply);\n\n // Analyze fetch methods\n const timeMethod = comments.filter((c) => c.fetchMethod === \"time\").length;\n const relevanceMethod =\n comments.filter((c) => c.fetchMethod === \"relevance\").length;\n const detailedMethod =\n comments.filter((c) => c.fetchMethod === \"detailed\").length;\n\n // Calculate expected vs actual\n const totalRepliesExpected = topLevelComments.reduce(\n (sum, c) => sum + c.replyCount,\n 0,\n );\n const estimatedAccessible = Math.min(\n topLevelComments.length + totalRepliesExpected,\n 1000,\n );\n\n return {\n totalFetched: comments.length,\n topLevelComments: topLevelComments.length,\n repliesFetched: replies.length,\n totalRepliesExpected: totalRepliesExpected,\n missingReplies: Math.max(0, totalRepliesExpected - replies.length),\n\n // Collection efficiency\n collectionEfficiency:\n ((comments.length / Math.max(estimatedAccessible, 1)) * 100).toFixed(1) +\n \"%\",\n limitReached: comments.length >= 1000 ? \"Yes\" : \"No\",\n\n // Method breakdown\n fetchMethods: {\n timeOrder: timeMethod,\n relevanceOrder: relevanceMethod,\n detailedReplies: detailedMethod,\n totalUnique: comments.length,\n },\n\n // Quality metrics\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 // Collection stats\n estimatedTotal: estimatedAccessible,\n collectionRate:\n ((comments.length / Math.max(estimatedAccessible, 1)) * 100).toFixed(1) +\n \"%\",\n };\n}\n\n// Main comment analysis function\nfunction analyzeComments(comments) {\n if (comments.length === 0) {\n return {\n message: \"No comments found for analysis\",\n suggestions: [\n \"Check if the video exists and is public\",\n \"Verify the video has comments enabled\",\n \"Ensure the video ID is correct\",\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 };\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 \"beautiful\",\n \"helpful\",\n \"thanks\",\n \"thank\",\n \"appreciate\",\n \"brilliant\",\n ];\n const negativeWords = [\n \"hate\",\n \"bad\",\n \"terrible\",\n \"awful\",\n \"worst\",\n \"horrible\",\n \"disgusting\",\n \"boring\",\n \"waste\",\n \"stupid\",\n \"sucks\",\n \"disappointed\",\n \"trash\",\n ];\n const positiveEmojis = [\"❤️\", \"😍\", \"👍\", \"🔥\", \"💯\", \"😊\", \"🥰\"];\n const negativeEmojis = [\"👎\", \"😡\", \"😠\", \"💩\"];\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 positiveEmojis.forEach((emoji) => {\n positiveScore += comment.textOriginal.split(emoji).length - 1;\n });\n\n negativeEmojis.forEach((emoji) => {\n negativeScore += comment.textOriginal.split(emoji).length - 1;\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\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\n// Main Interface HTML\nfunction generateMainInterface() {\n return `\n \n \n \n YouTube Comment Analyzer - Maximum Collection\n \n \n \n \n \n

\n \n \n

🎯

Maximum Collection

Up to 1000 comments per video

🚀

Triple Strategy

Time + Relevance + Detailed Replies

😊

AI Analysis

Gemini-powered insights

📊

Rich Dashboard

Professional analytics

\n\n

🚀 Start Maximum Collection Analysis

How to get Video ID:

From URL: https://www.youtube.com/watch?v=C3xrFDFKmZ8

Extract: C3xrFDFKmZ8 (everything after \"v=\")

🎯 New Maximum System: Collects up to 1000 comments using advanced triple-fetch strategy!

\n \n \n \n

\n \n \n

\n\n

🎯 Maximum Collection: Up to 1000 comments with triple-fetch strategy

🤖 AI Enhanced: Gemini AI provides actionable insights

⚡ Optimized: Smart rate limiting and duplicate removal

🔒 Your data is processed securely and not stored

\n \n \n \n \n `;\n}\n\n// Enhanced Dashboard HTML Generator\nfunction generateDashboardHTML(video, analysis) {\n return `\n \n \n \n Maximum Collection Analysis - ${video.title}\n \n \n \n \n \n

\n \n \n

\n \n

${analysis.breakdown.totalFetched}

Total Comments Collected

${analysis.breakdown.topLevelComments}

Top-Level Comments

${analysis.breakdown.repliesFetched}

Replies Collected

${analysis.sentiment.overallScore}

Sentiment Score

\n\n \n

🎯 Maximum Collection Results (1000 Comment Limit)

\n \n

${analysis.breakdown.totalFetched}

Total Comments Collected

\n ${\n analysis.breakdown.limitReached === \"Yes\"\n ? \"🎯 Limit Reached!\"\n : \"📊 Under Limit\"\n }\n

\n \n

${analysis.breakdown.topLevelComments}

Top-Level Comments

Direct to video

\n \n

${analysis.breakdown.repliesFetched}

Replies Collected

Comment responses

\n \n

${analysis.breakdown.collectionEfficiency}

Collection Efficiency

Of accessible comments

\n \n

🚀 Advanced Collection Strategy

\n Time-Ordered: ${analysis.breakdown.fetchMethods.timeOrder} comments
\n Most recent comments first\n

\n Relevance-Ordered: ${analysis.breakdown.fetchMethods.relevanceOrder} comments
\n Most popular comments first\n

\n Detailed Replies: ${analysis.breakdown.fetchMethods.detailedReplies} replies
\n Individual reply fetching\n

\n Average Engagement: ${analysis.breakdown.averageLikes} likes/comment
\n Quality indicator\n

\n \n

\n 📊 Collection Completeness:
\n ✅ Dual-method fetching (time + relevance orders)
\n ✅ Additional reply collection for high-engagement comments
\n ✅ Duplicate removal across collection methods
\n ✅ Smart pagination with 1000 comment limit
\n ✅ Rate limiting to prevent API quota exhaustion
\n
\n ⚠️ Some comments may still be unavailable due to:
\n • YouTube's automatic spam filtering
\n • Community guideline violations
\n • Shadow-banned or restricted users
\n • Regional content restrictions
\n • Real-time comment moderation\n

\n\n \n

🤖 AI-Powered Insights (Gemini)

\n \n

👥 Audience Profile

${analysis.aiInsights.audienceProfile}

\n \n

📊 Content Reception

${analysis.aiInsights.contentReception}

\n \n

🎯 Key Topics Discussed

${analysis.aiInsights.keyTopics.join(\", \")}

\n \n

💡 AI Recommendations

• ${rec}

\n \n

🚀 Actionable Insights

${analysis.aiInsights.actionableInsights}

\n\n \n

😊 Audience Sentiment

\n Overall Mood: ${\n getSentimentDescription(analysis.sentiment.overallScore)\n }\n

\n \n

\n 😊 Positive: ${analysis.sentiment.positive.percentage}\n 😐 Neutral: ${analysis.sentiment.neutral.percentage}\n 😞 Negative: ${analysis.sentiment.negative.percentage}\n

\n\n \n

🔍 What People Are Talking About

\n ${\n analysis.keywords.slice(0, 12).map((kw) =>\n `${kw.word} (${kw.percentage})`\n ).join(\"\")\n }\n

\n\n \n

🏆 Most Popular Comments

\n ${\n analysis.topComments.slice(0, 3).map((comment) => `\n

${comment.author}

${comment.text}

\n 👍 ${comment.likes} likes • 💬 ${comment.replies} replies\n

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

\n\n \n

😀 Popular Emojis

\n ${\n analysis.emojis.topEmojis.slice(0, 8).map((emoji) =>\n `${emoji.emoji}`\n ).join(\"\")\n }\n

\n ${analysis.emojis.emojiUsageRate} of comments contain emojis\n

\n\n \n

❓ Questions from Audience

\n ${analysis.questions.totalQuestions} questions found (${analysis.questions.questionRate} of all comments)\n

\n ${\n analysis.questions.topQuestions.slice(0, 3).map((q) => `\n

${q.author}

${q.question}

👍 ${q.likes} likes

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

\n\n

\n \n \n `;\n}\n\nfunction getSentimentDescription(score) {\n if (score > 20) return \"Very Positive - Audience loves this content! 🎉\";\n if (score > 5) return \"Positive - Good reception from viewers 😊\";\n if (score > -5) return \"Neutral - Mixed but balanced reactions 😐\";\n if (score > -20) return \"Negative - Some concerns from audience 😟\";\n return \"Very Negative - Significant issues raised 😞\";\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 generateErrorHTML(error) {\n return `\n \n \n \n Analysis Error\n \n \n \n

❌ Analysis Error

Error: ${error}

Common solutions:

Check if the video ID is correct
Ensure the video is public
Verify API keys are configured
Make sure the video has comments enabled

\n \n

\n \n \n `;\n}",6,["D",1756642222647],{"_103":242,"_155":137,"_152":172,"_95":99,"_163":243,"_161":162,"_100":244,"_154":-5,"_105":245,"_156":185,"_166":-5},"e50116b0-8661-11f0-a0fa-0224a6c84d84","// Enhanced YouTube Comment Analysis Tool with Improved Comment Collection\n// Complete HTTP Val for Val Town\n\nexport default async function server(req: Request): Promise {\n const url = new URL(req.url);\n const videoId = url.searchParams.get(\"videoId\");\n const format = url.searchParams.get(\"format\");\n\n // Show main interface if no videoId\n if (!videoId) {\n return new Response(generateMainInterface(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n // Get API keys from environment\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: \"Go to Val Town Settings → Secrets and add both API keys\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n try {\n // Fetch video data\n const [videoDetails, comments] = await Promise.all([\n fetchVideoDetails(videoId, youtubeApiKey),\n fetchYouTubeComments(videoId, youtubeApiKey),\n ]);\n\n // Analyze comments\n const basicAnalysis = analyzeComments(comments);\n\n // Enhance with Gemini AI\n const geminiInsights = await enhanceWithGemini(\n comments,\n videoDetails,\n geminiApiKey,\n );\n\n // Combine analyses\n const completeAnalysis = {\n ...basicAnalysis,\n aiInsights: geminiInsights,\n };\n\n // Return dashboard view\n if (format === \"dashboard\") {\n return new Response(\n generateDashboardHTML(videoDetails, completeAnalysis),\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n }\n\n // Return JSON data\n return new Response(\n JSON.stringify(\n {\n success: true,\n analyzedAt: new Date().toISOString(),\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(\"Analysis error:\", error);\n return new Response(generateErrorHTML(error.message), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n}\n\n// Enhanced YouTube comment fetching with better collection\nasync function fetchYouTubeComments(videoId, apiKey, maxResults = 100) {\n const comments = [];\n let nextPageToken = \"\";\n const maxPages = 15; // Increased from 5 to get more comments\n let pageCount = 0;\n\n console.log(`Starting to fetch comments for video: ${videoId}`);\n\n try {\n do {\n const url = `https://www.googleapis.com/youtube/v3/commentThreads?` +\n `part=snippet,replies&videoId=${videoId}&key=${apiKey}&maxResults=${maxResults}&order=time` +\n (nextPageToken ? `&pageToken=${nextPageToken}` : \"\");\n\n console.log(`Fetching page ${pageCount + 1}...`);\n\n const response = await fetch(url);\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) {\n data.items.forEach((item) => {\n const comment = item.snippet.topLevelComment.snippet;\n\n // Add top-level comment\n comments.push({\n text: comment.textDisplay,\n textOriginal: comment.textOriginal,\n author: comment.authorDisplayName,\n authorChannelId: comment.authorChannelId?.value,\n likeCount: comment.likeCount || 0,\n publishedAt: comment.publishedAt,\n replyCount: item.snippet.totalReplyCount || 0,\n isReply: false,\n commentType: \"top-level\",\n });\n\n // Add replies if they exist and are loaded\n if (item.replies && item.replies.comments) {\n item.replies.comments.forEach((reply) => {\n const replySnippet = reply.snippet;\n comments.push({\n text: replySnippet.textDisplay,\n textOriginal: replySnippet.textOriginal,\n author: replySnippet.authorDisplayName,\n authorChannelId: replySnippet.authorChannelId?.value,\n likeCount: replySnippet.likeCount || 0,\n publishedAt: replySnippet.publishedAt,\n replyCount: 0,\n isReply: true,\n commentType: \"reply\",\n parentAuthor: comment.authorDisplayName,\n });\n });\n }\n });\n }\n\n nextPageToken = data.nextPageToken;\n pageCount++;\n\n console.log(\n `Page ${pageCount} complete. Total comments so far: ${comments.length}`,\n );\n\n // Add small delay to avoid rate limiting\n if (nextPageToken && pageCount < maxPages) {\n await new Promise((resolve) => setTimeout(resolve, 200));\n }\n } while (nextPageToken && pageCount < maxPages && comments.length < 1500);\n\n console.log(\n `Final result: Fetched ${comments.length} total comments (${\n comments.filter((c) => !c.isReply).length\n } top-level + ${\n comments.filter((c) => c.isReply).length\n } replies) across ${pageCount} pages`,\n );\n } catch (error) {\n console.error(\"Error fetching comments:\", error);\n throw error;\n }\n\n return comments;\n}\n\n// Fetch video details\nasync function fetchVideoDetails(videoId, apiKey) {\n const url =\n `https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics&id=${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: ${data.error.message}`);\n if (!data.items || data.items.length === 0) {\n throw new Error(\"Video not found\");\n }\n\n const video = data.items[0];\n return {\n title: video.snippet.title,\n channel: video.snippet.channelTitle,\n publishedAt: video.snippet.publishedAt,\n viewCount: parseInt(video.statistics.viewCount || 0),\n likeCount: parseInt(video.statistics.likeCount || 0),\n commentCount: parseInt(video.statistics.commentCount || 0),\n };\n}\n\n// Gemini AI Integration\nasync function enhanceWithGemini(comments, videoDetails, geminiApiKey) {\n try {\n const sampleComments = comments.slice(0, 30).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const prompt =\n `As an expert social media analyst, analyze these YouTube comments for the video \"${videoDetails.title}\" by ${videoDetails.channel}.\n\nComments data: ${JSON.stringify(sampleComments)}\n\nVideo stats: ${videoDetails.viewCount} views, ${videoDetails.likeCount} likes, ${videoDetails.commentCount} total comments.\n\nProvide insights in this exact JSON format:\n{\n \"audienceProfile\": \"Description of the audience demographic and behavior\",\n \"contentReception\": \"How the audience is receiving this content\",\n \"keyTopics\": [\"topic1\", \"topic2\", \"topic3\"],\n \"engagementInsights\": \"Analysis of engagement patterns\",\n \"recommendations\": [\"recommendation1\", \"recommendation2\", \"recommendation3\"],\n \"trendingPhrases\": [\"phrase1\", \"phrase2\"],\n \"emotionalTones\": [\"tone1\", \"tone2\"],\n \"actionableInsights\": \"Specific actions the creator should take\"\n}\n\nFocus on marketing-relevant insights that non-technical teams can understand and act upon.`;\n\n const response = await fetch(\n `https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=${geminiApiKey}`,\n {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{ text: prompt }],\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 return JSON.parse(jsonMatch[0]);\n }\n }\n\n return {\n audienceProfile: \"Analysis unavailable - using basic metrics\",\n contentReception: \"Mixed engagement patterns observed\",\n keyTopics: [\"General discussion\"],\n engagementInsights: \"Standard engagement levels\",\n recommendations: [\n \"Monitor comments regularly\",\n \"Engage with top commenters\",\n ],\n trendingPhrases: [\"No specific trends\"],\n emotionalTones: [\"Neutral\"],\n actionableInsights: \"Continue current content strategy\",\n };\n } catch (error) {\n console.error(\"Gemini AI error:\", error);\n return {\n audienceProfile: \"AI analysis temporarily unavailable\",\n contentReception: \"Using statistical analysis only\",\n keyTopics: [\"Analysis pending\"],\n engagementInsights: \"Basic metrics available\",\n recommendations: [\"Retry analysis later\"],\n trendingPhrases: [\"Data processing\"],\n emotionalTones: [\"Neutral\"],\n actionableInsights: \"Check back for AI insights\",\n };\n }\n}\n\n// Comment breakdown analysis\nfunction analyzeCommentBreakdown(comments) {\n const topLevelComments = comments.filter((c) => !c.isReply);\n const replies = comments.filter((c) => c.isReply);\n const totalRepliesExpected = topLevelComments.reduce(\n (sum, c) => sum + c.replyCount,\n 0,\n );\n\n return {\n totalFetched: comments.length,\n topLevelComments: topLevelComments.length,\n repliesFetched: replies.length,\n totalRepliesExpected: totalRepliesExpected,\n missingReplies: Math.max(0, totalRepliesExpected - replies.length),\n fetchEfficiency:\n ((comments.length /\n Math.max(topLevelComments.length + totalRepliesExpected, 1)) * 100)\n .toFixed(1) + \"%\",\n };\n}\n\n// Main comment analysis function\nfunction analyzeComments(comments) {\n if (comments.length === 0) {\n return { message: \"No comments found for analysis\" };\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), // Added breakdown analysis\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 \"beautiful\",\n \"helpful\",\n \"thanks\",\n \"thank\",\n \"appreciate\",\n \"brilliant\",\n ];\n const negativeWords = [\n \"hate\",\n \"bad\",\n \"terrible\",\n \"awful\",\n \"worst\",\n \"horrible\",\n \"disgusting\",\n \"boring\",\n \"waste\",\n \"stupid\",\n \"sucks\",\n \"disappointed\",\n \"trash\",\n ];\n const positiveEmojis = [\"❤️\", \"😍\", \"👍\", \"🔥\", \"💯\", \"😊\", \"🥰\"];\n const negativeEmojis = [\"👎\", \"😡\", \"😠\", \"💩\"];\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 positiveEmojis.forEach((emoji) => {\n positiveScore += comment.textOriginal.split(emoji).length - 1;\n });\n\n negativeEmojis.forEach((emoji) => {\n negativeScore += comment.textOriginal.split(emoji).length - 1;\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\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\n// Main Interface HTML\nfunction generateMainInterface() {\n return `\n \n \n \n YouTube Comment Analyzer with AI\n \n \n \n \n \n

\n \n \n

📊

Enhanced Collection

Up to 15 pages + replies

😊

Sentiment Analysis

AI-powered emotion detection

🔍

Smart Keywords

Topic extraction & trends

🤖

AI Insights

Gemini-powered analysis

\n\n

🚀 Start Your Enhanced Analysis

How to get Video ID:

From URL: https://www.youtube.com/watch?v=C3xrFDFKmZ8

Extract: C3xrFDFKmZ8 (everything after \"v=\")

New: Now collects 250-300+ comments instead of ~140!

\n \n \n \n

\n \n \n

\n\n

🚀 Enhanced Collection: Now fetches 3x more comments with replies

✨ AI Powered: Google Gemini for deeper insights

🔒 Your data is processed securely and not stored

\n \n \n \n \n `;\n}\n\n// Enhanced Dashboard HTML Generator\nfunction generateDashboardHTML(video, analysis) {\n return `\n \n \n \n Enhanced Comment Analysis - ${video.title}\n \n \n \n \n \n

\n \n \n

\n \n

${analysis.breakdown.totalFetched}

Comments Fetched

${analysis.breakdown.topLevelComments}

Top-Level Comments

${analysis.breakdown.repliesFetched}

Replies Fetched

${analysis.sentiment.overallScore}

Sentiment Score

\n\n \n

📊 Enhanced Comment Collection Details

\n Total Fetched: ${analysis.breakdown.totalFetched}
\n Comments + Replies collected\n

\n Top-Level: ${analysis.breakdown.topLevelComments}
\n Direct video comments\n

\n Replies: ${analysis.breakdown.repliesFetched}
\n Responses to comments\n

\n Fetch Rate: ${analysis.breakdown.fetchEfficiency}
\n Collection efficiency\n

\n 📋 Why comment counts differ:
\n • YouTube's count includes hidden/moderated comments
\n • Some replies may not be accessible via API
\n • Comments in different languages might be filtered
\n • Spam and community guideline violations are excluded\n

\n\n \n

🤖 AI-Powered Insights (Gemini)

\n \n

👥 Audience Profile

${analysis.aiInsights.audienceProfile}

\n \n

📊 Content Reception

${analysis.aiInsights.contentReception}

\n \n

🎯 Key Topics Discussed

${analysis.aiInsights.keyTopics.join(\", \")}

\n \n

💡 AI Recommendations

• ${rec}

\n \n

🚀 Actionable Insights

${analysis.aiInsights.actionableInsights}

\n\n \n

😊 Audience Sentiment

\n Overall Mood: ${\n getSentimentDescription(analysis.sentiment.overallScore)\n }\n

\n \n

\n 😊 Positive: ${analysis.sentiment.positive.percentage}\n 😐 Neutral: ${analysis.sentiment.neutral.percentage}\n 😞 Negative: ${analysis.sentiment.negative.percentage}\n

\n\n \n

🔍 What People Are Talking About

\n ${\n analysis.keywords.slice(0, 12).map((kw) =>\n `${kw.word} (${kw.percentage})`\n ).join(\"\")\n }\n

\n\n \n

🏆 Most Popular Comments

\n ${\n analysis.topComments.slice(0, 3).map((comment) => `\n

${comment.author}

${comment.text}

\n 👍 ${comment.likes} likes • 💬 ${comment.replies} replies\n

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

\n\n \n

😀 Popular Emojis

\n ${\n analysis.emojis.topEmojis.slice(0, 8).map((emoji) =>\n `${emoji.emoji}`\n ).join(\"\")\n }\n

\n ${analysis.emojis.emojiUsageRate} of comments contain emojis\n

\n\n \n

❓ Questions from Audience

\n ${analysis.questions.totalQuestions} questions found (${analysis.questions.questionRate} of all comments)\n

\n ${\n analysis.questions.topQuestions.slice(0, 3).map((q) => `\n

${q.author}

${q.question}

👍 ${q.likes} likes

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

\n\n

❌ Analysis Error

Error: ${error}

Common solutions:

Check if the video ID is correct
Ensure the video is public
Verify API keys are configured
Make sure the video has comments enabled

\n \n

\n \n \n `;\n}",5,["D",1756641546036],{"_103":247,"_155":137,"_152":172,"_95":99,"_163":248,"_161":162,"_100":249,"_154":-5,"_105":250,"_156":239,"_166":-5},"5d5f4dd8-865e-11f0-a906-0224a6c84d84","// YouTube Comment Analysis Tool with Gemini AI Integration\n// Complete HTTP Val for Val Town\n\nexport default async function server(req: Request): Promise {\n const url = new URL(req.url);\n const videoId = url.searchParams.get(\"videoId\");\n const format = url.searchParams.get(\"format\");\n\n // Show main interface if no videoId\n if (!videoId) {\n return new Response(generateMainInterface(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n // Get API keys from environment\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: \"Go to Val Town Settings → Secrets and add both API keys\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n try {\n // Fetch video data\n const [videoDetails, comments] = await Promise.all([\n fetchVideoDetails(videoId, youtubeApiKey),\n fetchYouTubeComments(videoId, youtubeApiKey),\n ]);\n\n // Analyze comments\n const basicAnalysis = analyzeComments(comments);\n\n // Enhance with Gemini AI\n const geminiInsights = await enhanceWithGemini(\n comments,\n videoDetails,\n geminiApiKey,\n );\n\n // Combine analyses\n const completeAnalysis = {\n ...basicAnalysis,\n aiInsights: geminiInsights,\n };\n\n // Return dashboard view\n if (format === \"dashboard\") {\n return new Response(\n generateDashboardHTML(videoDetails, completeAnalysis),\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n }\n\n // Return JSON data\n return new Response(\n JSON.stringify(\n {\n success: true,\n analyzedAt: new Date().toISOString(),\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(\"Analysis error:\", error);\n return new Response(generateErrorHTML(error.message), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n}\n\n// Main Interface HTML\nfunction generateMainInterface() {\n return `\n \n \n \n YouTube Comment Analyzer with AI\n \n \n \n \n \n

\n \n \n

😊

Sentiment Analysis

AI-powered emotion detection

🔍

Smart Keywords

Topic extraction & trends

📊

Visual Dashboard

Easy-to-read insights

🤖

AI Insights

Gemini-powered analysis

\n\n

🚀 Start Your Analysis

How to get Video ID:

From URL: https://www.youtube.com/watch?v=9NW33HtlU8g

Extract: 9NW33HtlU8g (everything after \"v=\")

\n \n \n \n

\n \n \n

\n\n

✨ New: Enhanced with Google Gemini AI for deeper insights

🔒 Your data is processed securely and not stored

\n \n \n \n \n `;\n}\n\n// Gemini AI Integration\nasync function enhanceWithGemini(comments, videoDetails, geminiApiKey) {\n try {\n // Prepare sample comments for analysis (limit to avoid token limits)\n const sampleComments = comments.slice(0, 30).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const prompt =\n `As an expert social media analyst, analyze these YouTube comments for the video \"${videoDetails.title}\" by ${videoDetails.channel}.\n\nComments data: ${JSON.stringify(sampleComments)}\n\nVideo stats: ${videoDetails.viewCount} views, ${videoDetails.likeCount} likes, ${videoDetails.commentCount} total comments.\n\nProvide insights in this exact JSON format:\n{\n \"audienceProfile\": \"Description of the audience demographic and behavior\",\n \"contentReception\": \"How the audience is receiving this content\",\n \"keyTopics\": [\"topic1\", \"topic2\", \"topic3\"],\n \"engagementInsights\": \"Analysis of engagement patterns\",\n \"recommendations\": [\"recommendation1\", \"recommendation2\", \"recommendation3\"],\n \"trendingPhrases\": [\"phrase1\", \"phrase2\"],\n \"emotionalTones\": [\"tone1\", \"tone2\"],\n \"actionableInsights\": \"Specific actions the creator should take\"\n}\n\nFocus on marketing-relevant insights that non-technical teams can understand and act upon.`;\n\n const response = await fetch(\n `https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=${geminiApiKey}`,\n {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{ text: prompt }],\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 // Extract JSON from the response\n const jsonMatch = aiText.match(/\\{[\\s\\S]*\\}/);\n if (jsonMatch) {\n return JSON.parse(jsonMatch[0]);\n }\n }\n\n // Fallback if Gemini fails\n return {\n audienceProfile: \"Analysis unavailable - using basic metrics\",\n contentReception: \"Mixed engagement patterns observed\",\n keyTopics: [\"General discussion\"],\n engagementInsights: \"Standard engagement levels\",\n recommendations: [\n \"Monitor comments regularly\",\n \"Engage with top commenters\",\n ],\n trendingPhrases: [\"No specific trends\"],\n emotionalTones: [\"Neutral\"],\n actionableInsights: \"Continue current content strategy\",\n };\n } catch (error) {\n console.error(\"Gemini AI error:\", error);\n return {\n audienceProfile: \"AI analysis temporarily unavailable\",\n contentReception: \"Using statistical analysis only\",\n keyTopics: [\"Analysis pending\"],\n engagementInsights: \"Basic metrics available\",\n recommendations: [\"Retry analysis later\"],\n trendingPhrases: [\"Data processing\"],\n emotionalTones: [\"Neutral\"],\n actionableInsights: \"Check back for AI insights\",\n };\n }\n}\n\n// YouTube API Functions\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: ${data.error.message}`);\n if (!data.items || data.items.length === 0) {\n throw new Error(\"Video not found\");\n }\n\n const video = data.items[0];\n return {\n title: video.snippet.title,\n channel: video.snippet.channelTitle,\n publishedAt: video.snippet.publishedAt,\n viewCount: parseInt(video.statistics.viewCount || 0),\n likeCount: parseInt(video.statistics.likeCount || 0),\n commentCount: parseInt(video.statistics.commentCount || 0),\n };\n}\n\nasync function fetchYouTubeComments(videoId, apiKey, maxResults = 100) {\n const comments = [];\n let nextPageToken = \"\";\n const maxPages = 5;\n let pageCount = 0;\n\n try {\n do {\n const url =\n `https://www.googleapis.com/youtube/v3/commentThreads?part=snippet&videoId=${videoId}&key=${apiKey}&maxResults=${maxResults}&order=relevance${\n nextPageToken ? `&pageToken=${nextPageToken}` : \"\"\n }`;\n\n const response = await fetch(url);\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) {\n data.items.forEach((item) => {\n const comment = item.snippet.topLevelComment.snippet;\n comments.push({\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 });\n });\n }\n\n nextPageToken = data.nextPageToken;\n pageCount++;\n } while (nextPageToken && pageCount < maxPages && comments.length < 500);\n } catch (error) {\n console.error(\"Error fetching comments:\", error);\n throw error;\n }\n\n return comments;\n}\n\n// Comment Analysis Functions\nfunction analyzeComments(comments) {\n if (comments.length === 0) {\n return { message: \"No comments found for analysis\" };\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 };\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 \"beautiful\",\n \"helpful\",\n \"thanks\",\n \"thank\",\n \"appreciate\",\n \"brilliant\",\n ];\n const negativeWords = [\n \"hate\",\n \"bad\",\n \"terrible\",\n \"awful\",\n \"worst\",\n \"horrible\",\n \"disgusting\",\n \"boring\",\n \"waste\",\n \"stupid\",\n \"sucks\",\n \"disappointed\",\n \"trash\",\n ];\n const positiveEmojis = [\"❤️\", \"😍\", \"👍\", \"🔥\", \"💯\", \"😊\", \"🥰\"];\n const negativeEmojis = [\"👎\", \"😡\", \"😠\", \"💩\"];\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 positiveEmojis.forEach((emoji) => {\n positiveScore += comment.textOriginal.split(emoji).length - 1;\n });\n\n negativeEmojis.forEach((emoji) => {\n negativeScore += comment.textOriginal.split(emoji).length - 1;\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\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\n// Dashboard HTML Generator\nfunction generateDashboardHTML(video, analysis) {\n return `\n \n \n \n Comment Analysis Dashboard - ${video.title}\n \n \n \n \n \n

\n \n \n

\n \n

${analysis.statistics.totalComments}

Total Comments

${analysis.sentiment.overallScore}

Sentiment Score

${analysis.engagement.engagementRate}

Engagement Rate

${analysis.statistics.uniqueAuthors}

Unique Commenters

\n\n \n

🤖 AI-Powered Insights (Gemini)

\n \n

👥 Audience Profile

${analysis.aiInsights.audienceProfile}

\n \n

📊 Content Reception

${analysis.aiInsights.contentReception}

\n \n

🎯 Key Topics Discussed

${analysis.aiInsights.keyTopics.join(\", \")}

\n \n

💡 AI Recommendations

• ${rec}

\n \n

🚀 Actionable Insights

${analysis.aiInsights.actionableInsights}

\n\n \n

😊 Audience Sentiment

\n Overall Mood: ${\n getSentimentDescription(analysis.sentiment.overallScore)\n }\n

\n \n

\n 😊 Positive: ${analysis.sentiment.positive.percentage}\n 😐 Neutral: ${analysis.sentiment.neutral.percentage}\n 😞 Negative: ${analysis.sentiment.negative.percentage}\n

\n\n \n

🔍 What People Are Talking About

\n ${\n analysis.keywords.slice(0, 12).map((kw) =>\n `${kw.word} (${kw.percentage})`\n ).join(\"\")\n }\n

\n\n \n

🏆 Most Popular Comments

\n ${\n analysis.topComments.slice(0, 3).map((comment) => `\n

${comment.author}

${comment.text}

\n 👍 ${comment.likes} likes • 💬 ${comment.replies} replies\n

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

\n\n \n

😀 Popular Emojis

\n ${\n analysis.emojis.topEmojis.slice(0, 8).map((emoji) =>\n `${emoji.emoji}`\n ).join(\"\")\n }\n

\n ${analysis.emojis.emojiUsageRate} of comments contain emojis\n

\n\n \n

❓ Questions from Audience

\n ${analysis.questions.totalQuestions} questions found (${analysis.questions.questionRate} of all comments)\n

\n ${\n analysis.questions.topQuestions.slice(0, 3).map((q) => `\n

${q.author}

${q.question}

👍 ${q.likes} likes

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

\n\n

❌ Analysis Error

Error: ${error}

Common solutions:

Check if the video ID is correct
Ensure the video is public
Verify API keys are configured
Make sure the video has comments enabled

\n \n

\n \n \n `;\n}",4,["D",1756640029994],{"_103":252,"_155":137,"_152":172,"_95":99,"_163":253,"_161":162,"_100":254,"_154":-5,"_105":255,"_156":244,"_166":-5},"40c4902c-865c-11f0-8885-0224a6c84d84","// YouTube Comment Analysis Tool for Val Town\n// Complete HTTP val implementation\n\nexport default async function server(req: Request): Promise {\n const url = new URL(req.url);\n const videoId = url.searchParams.get(\"videoId\");\n\n // If no videoId, show web interface\n if (!videoId) {\n return new Response(\n `\n \n \n \n YouTube Comment Analyzer\n \n \n \n \n \n

🎬 YouTube Comment Analyzer

\n \n

📊 What This Tool Analyzes:

📈 Sentiment Analysis

🔑 Popular Keywords

👍 Engagement Metrics

⏰ Time Distribution

🏆 Top Comments

😀 Emoji Usage

❓ Questions Found

📋 Detailed Statistics

\n\n

📝 How to Use:

Step 1: Copy any YouTube video URL

Example: https://www.youtube.com/watch?v=9NW33HtlU8g

Step 2: Extract the video ID (everything after \"v=\")

Video ID: 9NW33HtlU8g

Step 3: Enter the video ID below and click analyze!

\n\n \n \n \n

⚡ Features:

• Analyzes up to 500 comments per video

• Advanced sentiment analysis with emoji detection

• Keyword extraction with stop-word filtering

• Engagement metrics and time-based analysis

• Question detection and top comment identification

\n \n \n \n \n `,\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n }\n\n // Get API key from environment\n const apiKey = process.env.YOUTUBE_API_KEY;\n\n if (!apiKey) {\n return new Response(\n JSON.stringify({\n error: \"YouTube API key not configured\",\n setup:\n \"Go to Val Town Settings → Secrets → Add YOUTUBE_API_KEY with your Google Cloud API key\",\n documentation:\n \"https://developers.google.com/youtube/v3/getting-started\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n try {\n // Fetch video details and comments in parallel\n const [videoDetails, comments] = await Promise.all([\n fetchVideoDetails(videoId, apiKey),\n fetchYouTubeComments(videoId, apiKey),\n ]);\n\n // Analyze the comments\n const analysis = analyzeComments(comments);\n\n return new Response(\n JSON.stringify(\n {\n success: true,\n analyzedAt: new Date().toISOString(),\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=${videoId}`,\n },\n fetchedComments: comments.length,\n analysis,\n },\n null,\n 2,\n ),\n {\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n },\n );\n } catch (error) {\n console.error(\"Analysis error:\", error);\n return new Response(\n JSON.stringify({\n error: error.message,\n videoId: videoId,\n timestamp: new Date().toISOString(),\n suggestions: [\n \"Verify the video ID is correct\",\n \"Ensure the video has comments enabled\",\n \"Check that your API key has YouTube Data API v3 enabled\",\n \"Make sure the video is public or unlisted\",\n ],\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n}\n\n// Fetch video details from YouTube API\nasync function fetchVideoDetails(videoId: string, apiKey: string) {\n const url = `https://www.googleapis.com/youtube/v3/videos?` +\n `part=snippet,statistics&id=${videoId}&key=${apiKey}`;\n\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error) {\n throw new Error(`YouTube API Error: ${data.error.message}`);\n }\n\n if (!data.items || data.items.length === 0) {\n throw new Error(\"Video not found or not accessible\");\n }\n\n const video = data.items[0];\n return {\n title: video.snippet.title,\n channel: video.snippet.channelTitle,\n publishedAt: video.snippet.publishedAt,\n viewCount: parseInt(video.statistics.viewCount || 0),\n likeCount: parseInt(video.statistics.likeCount || 0),\n commentCount: parseInt(video.statistics.commentCount || 0),\n };\n}\n\n// Fetch comments from YouTube API with pagination\nasync function fetchYouTubeComments(\n videoId: string,\n apiKey: string,\n maxResults: number = 100,\n) {\n const comments = [];\n let nextPageToken = \"\";\n const maxPages = 5; // Limit to avoid quota issues\n let pageCount = 0;\n\n try {\n do {\n const url = `https://www.googleapis.com/youtube/v3/commentThreads?` +\n `part=snippet&videoId=${videoId}&key=${apiKey}&maxResults=${maxResults}&order=relevance` +\n (nextPageToken ? `&pageToken=${nextPageToken}` : \"\");\n\n const response = await fetch(url);\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) {\n data.items.forEach((item) => {\n const comment = item.snippet.topLevelComment.snippet;\n comments.push({\n text: comment.textDisplay,\n textOriginal: comment.textOriginal,\n author: comment.authorDisplayName,\n authorChannelId: comment.authorChannelId?.value,\n likeCount: comment.likeCount || 0,\n publishedAt: comment.publishedAt,\n replyCount: item.snippet.totalReplyCount || 0,\n });\n });\n }\n\n nextPageToken = data.nextPageToken;\n pageCount++;\n } while (nextPageToken && pageCount < maxPages && comments.length < 500);\n } catch (error) {\n console.error(\"Error fetching comments:\", error);\n throw error;\n }\n\n return comments;\n}\n\n// Main comment analysis function\nfunction analyzeComments(comments) {\n if (comments.length === 0) {\n return {\n message: \"No comments found for analysis\",\n possibleReasons: [\n \"Comments are disabled for this video\",\n \"Video is private or restricted\",\n \"No comments have been posted yet\",\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 };\n}\n\n// Enhanced sentiment analysis with more sophisticated scoring\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 \"beautiful\",\n \"helpful\",\n \"thanks\",\n \"thank\",\n \"appreciate\",\n \"brilliant\",\n \"outstanding\",\n \"superb\",\n \"nice\",\n \"cool\",\n \"impressive\",\n \"incredible\",\n \"magnificent\",\n \"spectacular\",\n \"phenomenal\",\n ];\n\n const negativeWords = [\n \"hate\",\n \"bad\",\n \"terrible\",\n \"awful\",\n \"worst\",\n \"horrible\",\n \"disgusting\",\n \"ugly\",\n \"boring\",\n \"waste\",\n \"stupid\",\n \"dumb\",\n \"sucks\",\n \"disappointed\",\n \"trash\",\n \"pathetic\",\n \"ridiculous\",\n \"annoying\",\n \"useless\",\n \"pointless\",\n ];\n\n const positiveEmojis = [\n \"❤️\",\n \"😍\",\n \"👍\",\n \"🔥\",\n \"💯\",\n \"😊\",\n \"🥰\",\n \"😘\",\n \"👏\",\n \"🙌\",\n ];\n const negativeEmojis = [\"👎\", \"😡\", \"😠\", \"💩\", \"🤮\", \"😤\", \"🙄\", \"😒\"];\n\n let positive = 0, negative = 0, neutral = 0, mixed = 0;\n const sentimentDetails = [];\n\n comments.forEach((comment, index) => {\n const text = comment.textOriginal.toLowerCase();\n let positiveScore = 0;\n let negativeScore = 0;\n\n // Word-based scoring\n positiveWords.forEach((word) => {\n const matches =\n (text.match(new RegExp(`\\\\b${word}\\\\b`, \"g\")) || []).length;\n positiveScore += matches;\n });\n\n negativeWords.forEach((word) => {\n const matches =\n (text.match(new RegExp(`\\\\b${word}\\\\b`, \"g\")) || []).length;\n negativeScore += matches;\n });\n\n // Emoji-based scoring\n positiveEmojis.forEach((emoji) => {\n positiveScore += comment.textOriginal.split(emoji).length - 1;\n });\n\n negativeEmojis.forEach((emoji) => {\n negativeScore += comment.textOriginal.split(emoji).length - 1;\n });\n\n // Determine sentiment\n let sentiment;\n if (positiveScore > 0 && negativeScore > 0) {\n sentiment = \"mixed\";\n mixed++;\n } else if (positiveScore > negativeScore) {\n sentiment = \"positive\";\n positive++;\n } else if (negativeScore > positiveScore) {\n sentiment = \"negative\";\n negative++;\n } else {\n sentiment = \"neutral\";\n neutral++;\n }\n\n sentimentDetails.push({\n index,\n sentiment,\n positiveScore,\n negativeScore,\n author: comment.author,\n });\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 mixed: {\n count: mixed,\n percentage: ((mixed / total) * 100).toFixed(1) + \"%\",\n },\n overallScore: parseFloat(((positive - negative) / total * 100).toFixed(1)),\n distribution: sentimentDetails.slice(0, 10), // Top 10 for debugging\n };\n}\n\n// Extract keywords with improved filtering and stemming\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 \"who\",\n \"whom\",\n \"whose\",\n \"which\",\n \"am\",\n \"im\",\n \"so\",\n \"very\",\n \"just\",\n \"like\",\n \"really\",\n \"too\",\n \"also\",\n \"about\",\n \"up\",\n \"down\",\n \"out\",\n \"off\",\n \"over\",\n \"under\",\n \"again\",\n \"then\",\n \"there\",\n \"here\",\n \"all\",\n \"both\",\n \"each\",\n \"few\",\n \"more\",\n \"most\",\n \"other\",\n \"some\",\n \"such\",\n \"only\",\n \"own\",\n \"same\",\n \"than\",\n \"after\",\n \"before\",\n \"dont\",\n \"doesnt\",\n \"isnt\",\n \"arent\",\n \"wasnt\",\n \"werent\",\n \"havent\",\n \"hasnt\",\n \"hadnt\",\n \"wont\",\n \"wouldnt\",\n \"shouldnt\",\n \"couldnt\",\n \"cant\",\n \"mustnt\",\n ]);\n\n comments.forEach((comment) => {\n const cleanText = comment.textOriginal\n .replace(/<[^>]*>/g, \"\") // Remove HTML\n .replace(/https?:\\/\\/[^\\s]+/g, \"\") // Remove URLs\n .replace(/[@#]\\w+/g, \"\") // Remove mentions/hashtags\n .replace(/[^\\w\\s]/g, \" \") // Remove punctuation\n .toLowerCase();\n\n const words = cleanText.match(/\\b[a-z]{3,}\\b/g) || [];\n\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, 20)\n .map(([word, count]) => ({\n word,\n count,\n percentage: ((count / comments.length) * 100).toFixed(1) + \"%\",\n }));\n}\n\n// Comprehensive engagement analysis\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 const engagementBuckets = {\n noEngagement:\n comments.filter((c) => c.likeCount === 0 && c.replyCount === 0).length,\n lowEngagement:\n comments.filter((c) =>\n (c.likeCount + c.replyCount) > 0 && (c.likeCount + c.replyCount) <= 5\n ).length,\n mediumEngagement:\n comments.filter((c) =>\n (c.likeCount + c.replyCount) > 5 && (c.likeCount + c.replyCount) <= 50\n ).length,\n highEngagement:\n comments.filter((c) => (c.likeCount + c.replyCount) > 50).length,\n };\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 engagementDistribution: engagementBuckets,\n engagementRate:\n ((comments.filter((c) => c.likeCount > 0 || c.replyCount > 0).length /\n comments.length) * 100).toFixed(1) + \"%\",\n };\n}\n\n// Time-based comment analysis\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 const hourlyDistribution = Array(24).fill(0);\n const dailyActivity = {};\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 // Time ranges\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 // Hourly distribution\n hourlyDistribution[commentDate.getHours()]++;\n\n // Daily activity\n const dayKey = commentDate.toDateString();\n dailyActivity[dayKey] = (dailyActivity[dayKey] || 0) + 1;\n });\n\n return {\n timeRanges,\n peakHour: hourlyDistribution.indexOf(Math.max(...hourlyDistribution)),\n dailyActivity: Object.entries(dailyActivity)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 7)\n .map(([date, count]) => ({ date, count })),\n };\n}\n\n// Get top performing comments\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, 250) +\n (comment.textOriginal.length > 250 ? \"...\" : \"\"),\n likes: comment.likeCount,\n replies: comment.replyCount,\n totalEngagement: comment.likeCount + comment.replyCount,\n publishedAt: comment.publishedAt,\n wordCount: comment.textOriginal.split(\" \").length,\n }));\n}\n\n// Comprehensive statistics\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 medianLength: lengths.sort((a, b) => a - b)[Math.floor(lengths.length / 2)],\n shortestComment: Math.min(...lengths),\n longestComment: Math.max(...lengths),\n averageWordCount: Math.round(\n wordCounts.reduce((a, b) => a + b, 0) / wordCounts.length,\n ),\n commentsWithReplies: comments.filter((c) => c.replyCount > 0).length,\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\n// Advanced emoji analysis\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, 15)\n .map(([emoji, count]) => ({ emoji, count }));\n\n return {\n totalEmojis,\n commentsWithEmojis,\n uniqueEmojis: Object.keys(emojiCount).length,\n topEmojis,\n emojiUsageRate: ((commentsWithEmojis / comments.length) * 100).toFixed(1) +\n \"%\",\n averageEmojisPerComment: (totalEmojis / comments.length).toFixed(2),\n };\n}\n\n// Enhanced question detection\nfunction findQuestions(comments) {\n const questionPatterns = [\n /\\?/,\n /^(what|where|when|why|how|who|which|is|are|can|could|would|will|do|does|did|should|has|have)/i,\n /(please|help|explain|tell me|show me)/i,\n ];\n\n const questions = comments.filter((comment) => {\n return questionPatterns.some((pattern) =>\n pattern.test(comment.textOriginal)\n );\n });\n\n const 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, 200) +\n (q.textOriginal.length > 200 ? \"...\" : \"\"),\n likes: q.likeCount,\n replies: q.replyCount,\n }));\n\n return {\n totalQuestions: questions.length,\n questionRate: ((questions.length / comments.length) * 100).toFixed(1) + \"%\",\n topQuestions,\n avgLikesOnQuestions: questions.length > 0\n ? (questions.reduce((sum, q) => sum + q.likeCount, 0) / questions.length)\n .toFixed(1)\n : 0,\n };\n}\n\n// Author analysis\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 totalWords: 0,\n };\n }\n\n const stats = authorStats[comment.author];\n stats.commentCount++;\n stats.totalLikes += comment.likeCount;\n stats.totalReplies += comment.replyCount;\n stats.totalWords += comment.textOriginal.split(\" \").length;\n });\n\n const topAuthors = Object.entries(authorStats)\n .sort((a, b) => b[1].totalLikes - a[1].totalLikes)\n .slice(0, 10)\n .map(([author, stats]) => ({\n author,\n ...stats,\n averageLikesPerComment: (stats.totalLikes / stats.commentCount).toFixed(\n 1,\n ),\n }));\n\n return {\n uniqueAuthors: Object.keys(authorStats).length,\n topContributors: topAuthors,\n multipleCommenters:\n Object.values(authorStats).filter((s) => s.commentCount > 1).length,\n };\n}",3,["D",1756639123009],{"_103":257,"_155":137,"_152":172,"_95":99,"_163":258,"_161":162,"_100":198,"_154":-5,"_105":259,"_156":249,"_166":-5},"85080928-865a-11f0-adee-0224a6c84d84","export default async function server(req: Request): Promise {\n return new Response(\"Hello World!\", {\n headers: { \"Content-Type\": \"text/plain\" },\n });\n}",["D",1756638378545],{"_103":261,"_155":137,"_152":172,"_95":99,"_163":72,"_161":162,"_100":195,"_154":-5,"_105":262,"_156":254,"_166":-5},"82e635a2-865a-11f0-846f-0224a6c84d84",["D",1756638374968],{"_103":264,"_155":137,"_152":172,"_95":99,"_163":72,"_161":265,"_100":32,"_154":-5,"_105":266,"_156":195,"_166":-5},"2f26952e-865a-11f0-997f-0224a6c84d84","script",["D",1756638234463],"versions",[269,271,272,273,274,275,276,277,278,279],{"_201":223,"_270":225},"previous",{"_201":225,"_270":231},{"_201":231,"_270":236},{"_201":236,"_270":241},{"_201":241,"_270":246},{"_201":246,"_270":251},{"_201":251,"_270":256},{"_201":256,"_270":260},{"_201":260,"_270":263},{"_201":263,"_270":-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

🤖 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

History for main.tsx