@neuroequality/neuroadapt-ai/dist/behavior-analytics-DOSpG3Xv.cjs.map

AI-powered accessibility personalization for neurodivergent users

{"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<typeof UserInteractionSchema>;\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<T = unknown> {\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<string, unknown>;\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<string, unknown>;\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<string, unknown>;\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<typeof AnalyticsEventSchema>;\n\n/**\n * Feature extraction result\n */\nexport interface FeatureVector {\n  features: Record<string, number>;\n  metadata?: Record<string, unknown>;\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<string, unknown>;\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<string, unknown>;\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<BehaviorAnalyticsEvents> {\n  private config: Required<BehaviorAnalyticsConfig>;\n  private currentSession: SessionData | null = null;\n  private sessions: SessionData[] = [];\n  private eventBuffer: AnalyticsEvent[] = [];\n  private patternCache: Map<string, BehaviorPattern> = new Map();\n  private anomalyBaselines: Map<string, number> = 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<AnalyticsEvent>): 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<string, unknown>,\n    context?: Record<string, unknown>\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<string, number>();\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<string, unknown> {\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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