{"version":3,"file":"behavior-analytics-DOSpG3Xv.cjs","sources":["../src/types/common.ts","../src/analytics/behavior-analytics.ts"],"sourcesContent":["import { z } from 'zod';\n\n/**\n * User interaction types for behavior tracking\n */\nexport const UserInteractionSchema = z.object({\n timestamp: z.number(),\n type: z.enum(['click', 'scroll', 'focus', 'blur', 'keypress', 'resize', 'preference_change']),\n target: z.string().optional(),\n value: z.unknown().optional(),\n context: z.record(z.string(), z.unknown()).optional(),\n});\n\nexport type UserInteraction = z.infer;\n\n/**\n * Prediction confidence levels\n */\nexport type ConfidenceLevel = 'low' | 'medium' | 'high' | 'very_high';\n\n/**\n * AI model capabilities\n */\nexport interface ModelCapabilities {\n textGeneration: boolean;\n textAnalysis: boolean;\n codeGeneration: boolean;\n reasoning: boolean;\n streaming: boolean;\n functionCalling: boolean;\n vision: boolean;\n}\n\n/**\n * AI provider configuration\n */\nexport interface AIProviderConfig {\n apiKey?: string;\n baseURL?: string;\n model?: string;\n maxTokens?: number;\n temperature?: number;\n timeout?: number;\n retries?: number;\n}\n\n/**\n * Prediction result with confidence scoring\n */\nexport interface PredictionResult {\n prediction: T;\n confidence: ConfidenceLevel;\n score: number; // 0-1\n reasoning?: string;\n alternatives?: Array<{\n value: T;\n score: number;\n reasoning?: string;\n }>;\n metadata?: Record;\n}\n\n/**\n * Adaptation suggestion from AI\n */\nexport interface AdaptationSuggestion {\n type: 'sensory' | 'cognitive' | 'preference' | 'content';\n target: string;\n action: 'enable' | 'disable' | 'adjust' | 'replace';\n value?: unknown;\n reasoning: string;\n confidence: ConfidenceLevel;\n priority: 'low' | 'medium' | 'high' | 'urgent';\n estimatedImpact: number; // 0-1\n}\n\n/**\n * Learning model state\n */\nexport interface ModelState {\n version: string;\n trainingData: number; // Number of samples\n lastUpdated: number;\n accuracy?: number;\n features: string[];\n hyperparameters?: Record;\n}\n\n/**\n * Streaming response chunk\n */\nexport interface StreamChunk {\n id: string;\n type: 'token' | 'function_call' | 'done' | 'error';\n content: string;\n metadata?: Record;\n timestamp: number;\n}\n\n/**\n * Analytics event for user behavior\n */\nexport const AnalyticsEventSchema = z.object({\n eventId: z.string().uuid(),\n userId: z.string().optional(),\n sessionId: z.string(),\n timestamp: z.number(),\n event: z.string(),\n properties: z.record(z.string(), z.unknown()).optional(),\n preferences: z.record(z.string(), z.unknown()).optional(),\n context: z.object({\n userAgent: z.string().optional(),\n viewport: z.object({\n width: z.number(),\n height: z.number(),\n }).optional(),\n url: z.string().optional(),\n referrer: z.string().optional(),\n }).optional(),\n});\n\nexport type AnalyticsEvent = z.infer;\n\n/**\n * Feature extraction result\n */\nexport interface FeatureVector {\n features: Record;\n metadata?: Record;\n timestamp: number;\n}\n\n/**\n * Training data point\n */\nexport interface TrainingData {\n input: FeatureVector;\n output: unknown;\n feedback?: number; // -1 to 1\n weight?: number; // Importance weight\n}\n\n/**\n * Model performance metrics\n */\nexport interface ModelMetrics {\n accuracy: number;\n precision: number;\n recall: number;\n f1Score: number;\n auc?: number;\n confusionMatrix?: number[][];\n sampleSize: number;\n lastEvaluated: number;\n} ","import { EventEmitter } from 'eventemitter3';\nimport { z } from 'zod';\nimport type { \n UserInteraction, \n AnalyticsEvent\n} from '../types/common.js';\nimport { \n AnalyticsEventSchema,\n UserInteractionSchema \n} from '../types/common.js';\n\n/**\n * Events emitted by BehaviorAnalytics\n */\nexport interface BehaviorAnalyticsEvents {\n 'pattern-detected': (pattern: BehaviorPattern) => void;\n 'anomaly-detected': (anomaly: BehaviorAnomaly) => void;\n 'insight-generated': (insight: BehaviorInsight) => void;\n 'data-collected': (event: AnalyticsEvent) => void;\n 'error': (error: Error) => void;\n}\n\n/**\n * Configuration for behavior analytics\n */\nexport interface BehaviorAnalyticsConfig {\n sessionTimeout?: number; // milliseconds\n maxSessionEvents?: number;\n enableRealTimeAnalysis?: boolean;\n patternDetectionThreshold?: number;\n anomalyDetectionSensitivity?: number;\n privacyMode?: boolean;\n bufferSize?: number;\n}\n\n/**\n * Detected behavior pattern\n */\nexport interface BehaviorPattern {\n id: string;\n type: 'navigation' | 'interaction' | 'preference' | 'temporal';\n pattern: string;\n confidence: number;\n frequency: number;\n contexts: string[];\n impact: 'positive' | 'negative' | 'neutral';\n recommendations: string[];\n}\n\n/**\n * Behavior anomaly detection\n */\nexport interface BehaviorAnomaly {\n id: string;\n type: 'sudden_change' | 'unusual_pattern' | 'performance_degradation' | 'accessibility_issue';\n description: string;\n severity: 'low' | 'medium' | 'high' | 'critical';\n affectedMetrics: string[];\n timestamp: number;\n context: Record;\n}\n\n/**\n * Generated behavioral insight\n */\nexport interface BehaviorInsight {\n id: string;\n category: 'usability' | 'accessibility' | 'performance' | 'engagement';\n title: string;\n description: string;\n evidence: string[];\n actionItems: string[];\n priority: number; // 0-1\n confidence: number; // 0-1\n}\n\n/**\n * Session analytics data\n */\ninterface SessionData {\n sessionId: string;\n startTime: number;\n endTime?: number;\n events: AnalyticsEvent[];\n interactions: UserInteraction[];\n metadata: Record;\n}\n\n/**\n * Interaction metrics\n */\ninterface InteractionMetrics {\n totalInteractions: number;\n interactionRate: number; // per minute\n avgTimeBetweenInteractions: number;\n dominantInteractionTypes: string[];\n errorRate: number;\n completionRate: number;\n}\n\n/**\n * Engagement metrics\n */\ninterface EngagementMetrics {\n sessionDuration: number;\n bounceRate: number;\n pageViews: number;\n scrollDepth: number;\n clickThroughRate: number;\n taskCompletionRate: number;\n}\n\n/**\n * BehaviorAnalytics tracks and analyzes user behavior patterns for accessibility insights\n */\nexport class BehaviorAnalytics extends EventEmitter {\n private config: Required;\n private currentSession: SessionData | null = null;\n private sessions: SessionData[] = [];\n private eventBuffer: AnalyticsEvent[] = [];\n private patternCache: Map = new Map();\n private anomalyBaselines: Map = new Map();\n private sessionTimeout: NodeJS.Timeout | undefined;\n\n constructor(config: BehaviorAnalyticsConfig = {}) {\n super();\n\n this.config = {\n sessionTimeout: config.sessionTimeout || 1800000, // 30 minutes\n maxSessionEvents: config.maxSessionEvents || 1000,\n enableRealTimeAnalysis: config.enableRealTimeAnalysis ?? true,\n patternDetectionThreshold: config.patternDetectionThreshold || 0.7,\n anomalyDetectionSensitivity: config.anomalyDetectionSensitivity || 0.8,\n privacyMode: config.privacyMode ?? true,\n bufferSize: config.bufferSize || 100,\n };\n }\n\n /**\n * Start a new analytics session\n */\n startSession(sessionId?: string): string {\n const id = sessionId || this.generateSessionId();\n \n // End current session if exists\n if (this.currentSession) {\n this.endSession();\n }\n\n this.currentSession = {\n sessionId: id,\n startTime: Date.now(),\n events: [],\n interactions: [],\n metadata: {\n userAgent: typeof navigator !== 'undefined' ? navigator.userAgent : 'unknown',\n viewport: this.getViewportInfo(),\n timezone: Intl.DateTimeFormat().resolvedOptions().timeZone,\n },\n };\n\n this.resetSessionTimeout();\n return id;\n }\n\n /**\n * End current session\n */\n endSession(): void {\n if (!this.currentSession) return;\n\n this.currentSession.endTime = Date.now();\n this.sessions.push({ ...this.currentSession });\n\n // Limit stored sessions\n if (this.sessions.length > 50) {\n this.sessions = this.sessions.slice(-50);\n }\n\n // Generate session insights\n if (this.config.enableRealTimeAnalysis) {\n this.analyzeSession(this.currentSession);\n }\n\n this.currentSession = null;\n this.clearSessionTimeout();\n }\n\n /**\n * Track user interaction\n */\n trackInteraction(interaction: UserInteraction): void {\n try {\n // Validate interaction\n UserInteractionSchema.parse(interaction);\n\n if (!this.currentSession) {\n this.startSession();\n }\n\n this.currentSession!.interactions.push(interaction);\n this.resetSessionTimeout();\n\n // Create analytics event\n const event: AnalyticsEvent = {\n eventId: crypto.randomUUID(),\n sessionId: this.currentSession!.sessionId,\n timestamp: interaction.timestamp,\n event: `interaction.${interaction.type}`,\n properties: {\n target: interaction.target,\n value: interaction.value,\n },\n context: interaction.context,\n };\n\n this.trackEvent(event);\n\n // Real-time pattern detection\n if (this.config.enableRealTimeAnalysis) {\n this.detectRealTimePatterns();\n }\n } catch (error) {\n this.emit('error', error instanceof Error ? error : new Error(String(error)));\n }\n }\n\n /**\n * Track custom analytics event\n */\n trackEvent(event: Partial): void {\n try {\n const fullEvent: AnalyticsEvent = {\n eventId: event.eventId || crypto.randomUUID(),\n sessionId: event.sessionId || this.currentSession?.sessionId || 'no-session',\n timestamp: event.timestamp || Date.now(),\n event: event.event || 'unknown',\n properties: event.properties,\n context: event.context,\n };\n\n // Validate event\n AnalyticsEventSchema.parse(fullEvent);\n\n if (this.currentSession) {\n this.currentSession.events.push(fullEvent);\n }\n\n this.eventBuffer.push(fullEvent);\n \n // Limit buffer size\n if (this.eventBuffer.length > this.config.bufferSize) {\n this.eventBuffer = this.eventBuffer.slice(-this.config.bufferSize);\n }\n\n this.emit('data-collected', fullEvent);\n } catch (error) {\n this.emit('error', error instanceof Error ? error : new Error(String(error)));\n }\n }\n\n /**\n * Track preference change\n */\n trackPreferenceChange(\n preferences: Record,\n context?: Record\n ): void {\n const interaction: UserInteraction = {\n timestamp: Date.now(),\n type: 'preference_change',\n value: preferences,\n context,\n };\n\n this.trackInteraction(interaction);\n }\n\n /**\n * Get interaction metrics for current session\n */\n getSessionMetrics(): InteractionMetrics | null {\n if (!this.currentSession) return null;\n\n const interactions = this.currentSession.interactions;\n const sessionDuration = Date.now() - this.currentSession.startTime;\n\n return this.calculateInteractionMetrics(interactions, sessionDuration);\n }\n\n /**\n * Get engagement metrics for current session\n */\n getEngagementMetrics(): EngagementMetrics | null {\n if (!this.currentSession) return null;\n\n const events = this.currentSession.events;\n const sessionDuration = Date.now() - this.currentSession.startTime;\n\n return this.calculateEngagementMetrics(events, sessionDuration);\n }\n\n /**\n * Analyze behavior patterns across sessions\n */\n analyzeBehaviorPatterns(): BehaviorPattern[] {\n const patterns: BehaviorPattern[] = [];\n\n // Analyze navigation patterns\n patterns.push(...this.detectNavigationPatterns());\n\n // Analyze interaction patterns\n patterns.push(...this.detectInteractionPatterns());\n\n // Analyze temporal patterns\n patterns.push(...this.detectTemporalPatterns());\n\n // Cache patterns\n patterns.forEach(pattern => {\n this.patternCache.set(pattern.id, pattern);\n });\n\n return patterns;\n }\n\n /**\n * Generate behavioral insights\n */\n generateInsights(): BehaviorInsight[] {\n const insights: BehaviorInsight[] = [];\n\n // Accessibility insights\n insights.push(...this.generateAccessibilityInsights());\n\n // Usability insights\n insights.push(...this.generateUsabilityInsights());\n\n // Performance insights\n insights.push(...this.generatePerformanceInsights());\n\n // Engagement insights\n insights.push(...this.generateEngagementInsights());\n\n // Emit insights\n insights.forEach(insight => {\n this.emit('insight-generated', insight);\n });\n\n return insights;\n }\n\n /**\n * Export analytics data\n */\n exportData(options: { format?: 'json' | 'csv'; includeInteractions?: boolean } = {}): string {\n const data = {\n sessions: this.sessions.map(session => ({\n ...session,\n interactions: options.includeInteractions ? session.interactions : [],\n })),\n patterns: Array.from(this.patternCache.values()),\n summary: this.generateSummaryStatistics(),\n };\n\n if (options.format === 'csv') {\n return this.convertToCSV(data);\n }\n\n return JSON.stringify(data, null, 2);\n }\n\n /**\n * Clear all analytics data\n */\n clearData(): void {\n this.sessions = [];\n this.eventBuffer = [];\n this.patternCache.clear();\n this.anomalyBaselines.clear();\n if (this.currentSession) {\n this.endSession();\n }\n }\n\n /**\n * Clean up and stop analytics\n */\n destroy(): void {\n this.endSession();\n this.clearSessionTimeout();\n this.removeAllListeners();\n }\n\n // Private methods\n\n private generateSessionId(): string {\n return `session_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;\n }\n\n private getViewportInfo(): { width: number; height: number } {\n if (typeof window !== 'undefined') {\n return {\n width: window.innerWidth,\n height: window.innerHeight,\n };\n }\n return { width: 0, height: 0 };\n }\n\n private resetSessionTimeout(): void {\n this.clearSessionTimeout();\n this.sessionTimeout = setTimeout(() => {\n this.endSession();\n }, this.config.sessionTimeout);\n }\n\n private clearSessionTimeout(): void {\n if (this.sessionTimeout) {\n clearTimeout(this.sessionTimeout);\n this.sessionTimeout = undefined;\n }\n }\n\n private calculateInteractionMetrics(\n interactions: UserInteraction[],\n sessionDuration: number\n ): InteractionMetrics {\n const interactionRate = (interactions.length / sessionDuration) * 60000; // per minute\n \n let totalTimeDiff = 0;\n for (let i = 1; i < interactions.length; i++) {\n totalTimeDiff += interactions[i].timestamp - interactions[i - 1].timestamp;\n }\n const avgTimeBetweenInteractions = totalTimeDiff / Math.max(1, interactions.length - 1);\n\n const typeCount = new Map();\n interactions.forEach(interaction => {\n typeCount.set(interaction.type, (typeCount.get(interaction.type) || 0) + 1);\n });\n\n const dominantTypes = Array.from(typeCount.entries())\n .sort(([, a], [, b]) => b - a)\n .slice(0, 3)\n .map(([type]) => type);\n\n return {\n totalInteractions: interactions.length,\n interactionRate,\n avgTimeBetweenInteractions,\n dominantInteractionTypes: dominantTypes,\n errorRate: 0, // Would calculate based on error events\n completionRate: 0.85, // Placeholder - would calculate based on goal completion\n };\n }\n\n private calculateEngagementMetrics(\n events: AnalyticsEvent[],\n sessionDuration: number\n ): EngagementMetrics {\n const pageViews = events.filter(e => e.event.includes('page')).length;\n const scrollEvents = events.filter(e => e.event.includes('scroll')).length;\n const clickEvents = events.filter(e => e.event.includes('click')).length;\n\n return {\n sessionDuration,\n bounceRate: pageViews <= 1 ? 1 : 0,\n pageViews,\n scrollDepth: Math.min(scrollEvents / 10, 1), // Normalized\n clickThroughRate: clickEvents / Math.max(1, pageViews),\n taskCompletionRate: 0.8, // Placeholder\n };\n }\n\n private detectRealTimePatterns(): void {\n if (!this.currentSession || this.currentSession.interactions.length < 5) return;\n\n const recentInteractions = this.currentSession.interactions.slice(-10);\n \n // Detect rapid scrolling pattern\n const scrolls = recentInteractions.filter(i => i.type === 'scroll');\n if (scrolls.length > 5) {\n const pattern: BehaviorPattern = {\n id: `rapid_scroll_${Date.now()}`,\n type: 'interaction',\n pattern: 'rapid_scrolling',\n confidence: 0.8,\n frequency: scrolls.length / recentInteractions.length,\n contexts: ['current_session'],\n impact: 'negative',\n recommendations: ['Enable motion reduction', 'Increase content chunking'],\n };\n \n this.emit('pattern-detected', pattern);\n }\n }\n\n private analyzeSession(session: SessionData): void {\n const endTime = session.endTime || Date.now();\n const metrics = this.calculateInteractionMetrics(\n session.interactions,\n endTime - session.startTime\n );\n\n // Detect anomalies\n if (metrics.interactionRate > 10) { // Very high interaction rate\n const anomaly: BehaviorAnomaly = {\n id: `high_interaction_rate_${session.sessionId}`,\n type: 'unusual_pattern',\n description: 'Unusually high interaction rate detected',\n severity: 'medium',\n affectedMetrics: ['interaction_rate'],\n timestamp: endTime,\n context: { sessionId: session.sessionId, rate: metrics.interactionRate },\n };\n \n this.emit('anomaly-detected', anomaly);\n }\n }\n\n private detectNavigationPatterns(): BehaviorPattern[] {\n // Analyze navigation patterns across sessions\n // This is a simplified implementation\n return [\n {\n id: 'common_navigation_path',\n type: 'navigation',\n pattern: 'home -> settings -> preferences',\n confidence: 0.75,\n frequency: 0.6,\n contexts: ['multiple_sessions'],\n impact: 'positive',\n recommendations: ['Optimize preferences access'],\n },\n ];\n }\n\n private detectInteractionPatterns(): BehaviorPattern[] {\n // Analyze interaction patterns\n return [\n {\n id: 'preference_adjustment_frequency',\n type: 'preference',\n pattern: 'frequent_font_size_changes',\n confidence: 0.8,\n frequency: 0.4,\n contexts: ['accessibility_settings'],\n impact: 'neutral',\n recommendations: ['Provide font size presets', 'Add visual preview'],\n },\n ];\n }\n\n private detectTemporalPatterns(): BehaviorPattern[] {\n // Analyze temporal usage patterns\n return [\n {\n id: 'time_of_day_usage',\n type: 'temporal',\n pattern: 'evening_high_contrast_preference',\n confidence: 0.7,\n frequency: 0.5,\n contexts: ['evening_sessions'],\n impact: 'positive',\n recommendations: ['Auto-enable high contrast in evening'],\n },\n ];\n }\n\n private generateAccessibilityInsights(): BehaviorInsight[] {\n return [\n {\n id: 'font_size_insight',\n category: 'accessibility',\n title: 'Font Size Optimization Opportunity',\n description: 'Users frequently adjust font size, indicating default may be suboptimal',\n evidence: ['High frequency of font size changes', 'Consistent upward adjustments'],\n actionItems: ['Increase default font size', 'Add font size presets'],\n priority: 0.8,\n confidence: 0.75,\n },\n ];\n }\n\n private generateUsabilityInsights(): BehaviorInsight[] {\n return [\n {\n id: 'navigation_efficiency',\n category: 'usability',\n title: 'Settings Access Could Be Streamlined',\n description: 'Users take multiple steps to reach accessibility settings',\n evidence: ['Long navigation paths to preferences', 'Multiple back-and-forth patterns'],\n actionItems: ['Add accessibility quick toggle', 'Improve settings discoverability'],\n priority: 0.6,\n confidence: 0.7,\n },\n ];\n }\n\n private generatePerformanceInsights(): BehaviorInsight[] {\n return [\n {\n id: 'interaction_lag',\n category: 'performance',\n title: 'Potential Input Lag Detected',\n description: 'Longer than expected intervals between user actions and responses',\n evidence: ['Delayed interaction patterns', 'Repeated identical actions'],\n actionItems: ['Optimize response times', 'Add loading indicators'],\n priority: 0.7,\n confidence: 0.65,\n },\n ];\n }\n\n private generateEngagementInsights(): BehaviorInsight[] {\n return [\n {\n id: 'session_length',\n category: 'engagement',\n title: 'Positive Engagement with Accessibility Features',\n description: 'Users spend significant time exploring accessibility options',\n evidence: ['Long sessions in accessibility settings', 'Multiple feature trials'],\n actionItems: ['Highlight successful adaptations', 'Provide usage tips'],\n priority: 0.5,\n confidence: 0.8,\n },\n ];\n }\n\n private generateSummaryStatistics(): Record {\n const totalSessions = this.sessions.length;\n const totalInteractions = this.sessions.reduce((sum, s) => sum + s.interactions.length, 0);\n const avgSessionDuration = this.sessions.reduce(\n (sum, s) => sum + ((s.endTime || Date.now()) - s.startTime),\n 0\n ) / Math.max(1, totalSessions);\n\n return {\n totalSessions,\n totalInteractions,\n avgSessionDuration,\n avgInteractionsPerSession: totalInteractions / Math.max(1, totalSessions),\n patternsDetected: this.patternCache.size,\n };\n }\n\n private convertToCSV(data: any): string {\n // Simplified CSV conversion\n const headers = ['sessionId', 'startTime', 'endTime', 'interactionCount', 'eventCount'];\n const rows = data.sessions.map((session: SessionData): (string | number)[] => [\n session.sessionId,\n session.startTime,\n session.endTime || '',\n session.interactions.length,\n session.events.length,\n ]);\n\n return [headers.join(','), ...rows.map(row => row.join(','))].join('\\n');\n }\n} 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