Enhanced EdTech Analysis - ${video.title}

\n \n \n

\n \n

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

Student Comments Analyzed

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

Overall Teacher Rating

${analysis.edtech?.learningOutcomes?.learningSuccessRate || '0%'}

Learning Success Rate

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

AI Analysis Passes

\n\n \n

🎓 Advanced Teacher Performance Analysis

\n \n

📊 Overall Assessment: ${analysis.aiInsights?.teacherPerformance?.overallTeacherRating?.score || 'Processing...'}

Justification: ${analysis.aiInsights?.teacherPerformance?.overallTeacherRating?.justification || 'AI analysis in progress...'}

\n\n

📊 Teaching Methodology Assessment

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

\n \n

💬 Communication Excellence Evaluation

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

\n \n

🧠 Subject Matter Expertise

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

\n \n

❤️ Emotional Intelligence

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

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

\n\n \n

🧠 Cognitive Learning Analysis

\n \n

📈 Bloom's Taxonomy Distribution

\n ${generateBloomsTaxonomy(analysis.aiInsights?.learningAnalytics?.cognitiveProcessing?.bloomsTaxonomyDistribution)}\n

\n \n

🎯 Learning Progression Tracking

\n ${generateLearningProgression(analysis.aiInsights?.learningAnalytics?.learningProgression)}\n

\n\n \n

👥 Student Psychology & Behavior Analysis

\n ${generateMotivationAnalysis(analysis.aiInsights?.studentBehavior?.motivationPsychology)}\n ${generateEmotionalStateAnalysis(analysis.aiInsights?.studentBehavior?.emotionalState)}\n

\n\n \n

📚 Content Effectiveness Analysis

\n ${generateContentEffectiveness(analysis.aiInsights?.contentEffectiveness)}\n

\n\n \n

🔮 Predictive Analytics & Recommendations

\n ${generatePredictiveInsights(analysis.aiInsights?.predictiveInsights)}\n

\n\n \n

📊 Statistical Analysis Summary

😊 Sentiment Distribution

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

Overall Score: ${analysis.sentiment?.overallScore || '0'}

❓ Questions Analysis

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

👥 Community Engagement

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

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

\n \n \n `;\n}\n\n// ========================================\n// DASHBOARD HELPER FUNCTIONS\n// ========================================\n\nfunction generateSkillCards(skills) {\n if (!skills) return '

Analysis in progress...

';\n \n return Object.entries(skills).map(([skillName, skillData]) => `\n

${skillName.replace(/([A-Z])/g, ' $1').replace(/^./, str => str.toUpperCase())}

${skillData.score || 'Analyzing...'}

${skillData.analysis || 'Processing feedback...'}

\n Evidence:\n ${(skillData.evidence || []).map(quote => `

\"${quote}\"

`).join('') || '

No evidence available

'}\n

\n Improvements:\n

${imp}
Processing recommendations...

\n `).join('');\n}\n\nfunction generateTeacherSummary(teacherPerformance) {\n if (!teacherPerformance) return '';\n \n return `\n

🏆 Teacher Performance Summary

Teaching Personality: ${teacherPerformance.teachingPersonality || 'AI analysis in progress...'}

\n \n

\n Key Strengths:\n

${strength}
Analysis pending...

\n \n

\n Priority Improvements:\n

${improvement}
Processing recommendations...

\n\n

\n Competitive Advantages:\n

${advantage}
Analyzing unique strengths...

\n `;\n}\n\nfunction generateBloomsTaxonomy(taxonomy) {\n if (!taxonomy) return '

Processing cognitive analysis...

';\n \n const levels = ['remember', 'understand', 'apply', 'analyze', 'evaluate', 'create'];\n \n return levels.map(level => `\n

${level.toUpperCase()}

${taxonomy[level] || '0%'}

\n `).join('');\n}\n\nfunction generateLearningProgression(progression) {\n if (!progression) return '

Processing learning progression analysis...

';\n \n return `\n

📈 Knowledge Construction

Stage: ${progression.knowledgeConstruction?.stage || 'Analyzing...'}

Evidence: ${(progression.knowledgeConstruction?.evidence || []).join(', ') || 'Processing...'}

\n \n

🎯 Skill Development

Current Stage: ${progression.skillDevelopment?.current_stage || 'Analyzing...'}

Progression Rate: ${progression.skillDevelopment?.progression_rate || 'Analyzing...'}

\n \n

🏆 Topic Mastery

\n ${(progression.masteryByTopic || []).map(topic => `\n

\n ${topic.topic}: ${topic.mastery_level} mastery (Confidence: ${topic.confidence})\n

${(topic.evidence || []).join(', ')}

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

Processing topic mastery...

'}\n

\n `;\n}\n\nfunction generateMotivationAnalysis(motivation) {\n if (!motivation) return '

Processing motivation analysis...

';\n \n const sdt = motivation.selfDeterminationTheory;\n \n return `\n

🎯 Self-Determination Theory Analysis

\n Autonomy: ${sdt?.autonomy?.level || 'Processing...'}\n

${(sdt?.autonomy?.evidence || []).join(', ') || 'Analyzing evidence...'}

\n Competence: ${sdt?.competence?.level || 'Processing...'}\n

${(sdt?.competence?.evidence || []).join(', ') || 'Analyzing evidence...'}

\n Relatedness: ${sdt?.relatedness?.level || 'Processing...'}\n

${(sdt?.relatedness?.evidence || []).join(', ') || 'Analyzing evidence...'}

\n \n

\n Primary Motivation: ${motivation.motivationType?.primary || 'Analyzing...'}
\n Achievement Goals: ${motivation.achievementGoals?.mastery_focused || '0%'} Mastery-focused, ${motivation.achievementGoals?.performance_focused || '0%'} Performance-focused
\n Self-Efficacy: ${motivation.selfEfficacy?.level || 'Processing...'}\n

\n `;\n}\n\nfunction generateEmotionalStateAnalysis(emotional) {\n if (!emotional) return '

Processing emotional analysis...

';\n \n return `\n

😊 Emotional State Analysis

Emotional Regulation: ${emotional.emotionalRegulation?.level || 'Processing...'}

Stress/Anxiety: ${emotional.stressAnxiety?.level || 'Processing...'}

Confidence Level: ${emotional.confidenceLevel?.overall || 'Processing...'}

Satisfaction: ${emotional.satisfactionMarkers?.frequency || 'Processing...'}

\n `;\n}\n\nfunction generateContentEffectiveness(content) {\n if (!content) return '

Processing content effectiveness analysis...

';\n \n return `\n

📖 Content Quality Assessment

\n Curriculum Alignment: ${content.curriculumAlignment?.score || 'Processing...'}/10\n

${content.curriculumAlignment?.analysis || 'Analyzing alignment...'}

\n Learning Objectives: ${content.learningObjectives?.achievement_rate || 'Processing...'} achievement rate\n

\n Content Structure: ${content.contentStructure?.flow_quality || 'Processing...'}\n

\n Engagement Level: ${content.engagementLevel?.overall || 'Processing...'}\n

\n `;\n}\n\nfunction generatePredictiveInsights(predictive) {\n if (!predictive) return '

Processing predictive analysis...

';\n \n return `\n

🔮 Future Predictions

\n Student Success Probability: ${predictive.studentSuccess?.probability || 'Processing...'}\n

${(predictive.studentSuccess?.indicators || []).join(', ') || 'Analyzing indicators...'}

\n \n

\n Engagement Trend: ${predictive.engagementTrends?.trajectory || 'Processing...'}\n

${predictive.engagementTrends?.forecast || 'Generating forecast...'}

\n \n

📋 Recommended Actions:

\n Immediate:\n

${action}
Processing...

\n Short-term:\n

${action}
Processing...

\n Long-term:\n

${action}
Processing...

\n `;\n}\n\nfunction getScoreClass(score) {\n if (!score) return '';\n const numScore = parseFloat(score.toString().split('/')[0] || 0);\n if (numScore >= 8) return 'score-high';\n if (numScore >= 6) return 'score-medium';\n return 'score-low';\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\n// ========================================\n// INTERFACE AND ERROR HANDLING\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 `\n \n \n \n Analysis Error\n \n \n \n

❌ Enhanced Analysis Error

Error: ${error}

The enhanced multi-pass analysis system encountered an issue. Please try again.

\n ← Try Again\n

\n \n \n `;\n}\n\nfunction generateQuotaErrorHTML() {\n return `\n \n \n \n API Quota Exceeded\n \n \n \n

⚠️ API Quota Temporarily Exceeded

Due to high usage of the enhanced multi-pass analysis system, please try again in a few minutes.

\n ← Go Back\n

\n \n \n `;\n}","deleted","label","children",[],[99],{"_104":170,"_95":171,"_152":172,"_154":-5,"_155":138,"_156":159,"_157":22,"_106":173,"_100":174,"_160":161,"_162":175,"_164":22,"_165":-5,"_166":176,"_98":177},"784c2d3c-8663-11f0-a2fe-0224a6c84d84","main.tsx","2f26960a-865a-11f0-997f-0224a6c84d84",["D",1756642222647],6,"// 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}",[],[171],{"_104":179,"_95":180,"_152":181,"_154":-5,"_155":138,"_156":182,"_157":183,"_106":184,"_100":185,"_160":161,"_162":186,"_164":22,"_165":-5,"_166":187,"_98":188},"d5a85978-88b7-11f0-88a6-0224a6c84d84","new-file-4421.tsx","cb71ac2c-88b5-11f0-b66d-0224a6c84d84",23,true,["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.

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🎓 Advanced Teacher Performance Analysis

📊 Overall Assessment: ${analysis.aiInsights?.teacherPerformance?.overallTeacherRating?.score || 'Processing...'}

📊 Teaching Methodology Assessment

💬 Communication Excellence Evaluation

🧠 Subject Matter Expertise

❤️ Emotional Intelligence

🧠 Cognitive Learning Analysis

📈 Bloom's Taxonomy Distribution

🎯 Learning Progression Tracking

👥 Student Psychology & Behavior Analysis

📚 Content Effectiveness Analysis

🔮 Predictive Analytics & Recommendations

📊 Statistical Analysis Summary

😊 Sentiment Distribution

❓ Questions Analysis

👥 Community Engagement

🏆 Teacher Performance Summary

📈 Knowledge Construction

🎯 Skill Development

🏆 Topic Mastery

🎯 Self-Determination Theory Analysis

😊 Emotional State Analysis

📖 Content Quality Assessment

🔮 Future Predictions

📋 Recommended Actions:

🎓 Enhanced EdTech Analyzer

🚀 Start Enhanced Analysis

❌ Enhanced Analysis Error

⚠️ API Quota Temporarily Exceeded

🎬 YouTube Comment Analyzer

Maximum Collection

Triple Strategy

AI Analysis

Rich Dashboard

🚀 Start Maximum Collection Analysis

🎯 Maximum Collection Results (1000 Comment Limit)

🚀 Advanced Collection Strategy

🤖 AI-Powered Insights (Gemini)

👥 Audience Profile

📊 Content Reception

🎯 Key Topics Discussed

💡 AI Recommendations

🚀 Actionable Insights

😊 Audience Sentiment

🔍 What People Are Talking About

🏆 Most Popular Comments

😀 Popular Emojis

❓ Questions from Audience

❌ Analysis Error

🎓 AI Teacher Performance Analysis

📊 Statistical Analysis Summary

😊 Sentiment Distribution

❓ Questions Analysis

👥 Community Engagement

🎓 Enhanced EdTech Analyzer

🚀 Start Enhanced Analysis

Error: ${error}

API Quota Exceeded