{"version":3,"file":"PredictivePrefetch.mjs","sources":["../../../src/lib/performance/PredictivePrefetch.ts"],"sourcesContent":["/**\n * @file Predictive Prefetching System\n * @description AI-driven prefetching that learns user navigation patterns\n * and predictively loads resources for likely next pages.\n *\n * FEATURE 3: Predictive Navigation Prefetching\n *\n * Strategies:\n * 1. Markov Chain prediction based on navigation history\n * 2. Time-of-day patterns for recurring user behavior\n * 3. Session context awareness (recent interactions)\n * 4. Network-adaptive prefetching (respects connection quality)\n */\n\nimport type { QueryClient } from '@tanstack/react-query';\n\n// ============================================================================\n// Types\n// ============================================================================\n\n/**\n * Navigation event for pattern learning\n */\nexport interface NavigationEvent {\n from: string;\n to: string;\n timestamp: number;\n sessionId: string;\n timeOfDay: 'morning' | 'afternoon' | 'evening' | 'night';\n dayOfWeek: number;\n}\n\n/**\n * Route configuration for prefetching\n */\nexport interface PrefetchableRoute {\n /** Route path pattern */\n path: string;\n /** Module loader for code splitting */\n loader?: () => Promise;\n /** Query configuration for data prefetching */\n queries?: Array<{\n queryKey: readonly unknown[];\n queryFn: () => Promise;\n staleTime?: number;\n }>;\n /** Static assets to preload */\n assets?: string[];\n /** Estimated load priority (0-10) */\n priority?: number;\n}\n\n/**\n * Prediction result\n */\nexport interface RoutePrediction {\n route: string;\n probability: number;\n confidence: 'high' | 'medium' | 'low';\n source: 'markov' | 'time-pattern' | 'session-context' | 'static';\n}\n\n/**\n * Transition matrix for Markov chain\n */\ntype TransitionMatrix = Map>;\n\n/**\n * Time pattern entry\n */\ninterface TimePattern {\n route: string;\n timeOfDay: string;\n dayOfWeek: number;\n count: number;\n}\n\n/**\n * Configuration for predictive prefetch\n */\nexport interface PredictivePrefetchConfig {\n /** Enable learning from navigation */\n enableLearning?: boolean;\n /** Probability threshold for triggering prefetch (0-1) */\n probabilityThreshold?: number;\n /** Maximum routes to prefetch at once */\n maxPrefetchCount?: number;\n /** Storage key for persisting learned patterns */\n storageKey?: string;\n /** Static route priorities (fallback) */\n staticRoutes?: Record;\n /** Network quality threshold ('4g' | '3g' | '2g' | 'slow-2g') */\n minNetworkQuality?: string;\n /** Respect user's data saver preference */\n respectDataSaver?: boolean;\n /** Debug logging */\n debug?: boolean;\n /** Decay factor for old transitions (0-1) */\n decayFactor?: number;\n /** Maximum history entries to keep */\n maxHistorySize?: number;\n}\n\n// ============================================================================\n// Constants\n// ============================================================================\n\nconst DEFAULT_CONFIG: Required = {\n enableLearning: true,\n probabilityThreshold: 0.3,\n maxPrefetchCount: 3,\n storageKey: 'predictive-prefetch-patterns',\n staticRoutes: {},\n minNetworkQuality: '3g',\n respectDataSaver: true,\n debug: false,\n decayFactor: 0.95,\n maxHistorySize: 1000,\n};\n\nconst NETWORK_QUALITY_RANK: Record = {\n '4g': 4,\n '3g': 3,\n '2g': 2,\n 'slow-2g': 1,\n unknown: 3,\n};\n\n// ============================================================================\n// Utility Functions\n// ============================================================================\n\n/**\n * Get time of day category\n */\nfunction getTimeOfDay(): 'morning' | 'afternoon' | 'evening' | 'night' {\n const hour = new Date().getHours();\n if (hour >= 5 && hour < 12) return 'morning';\n if (hour >= 12 && hour < 17) return 'afternoon';\n if (hour >= 17 && hour < 21) return 'evening';\n return 'night';\n}\n\n/**\n * Normalize path for comparison\n */\nfunction normalizePath(path: string): string {\n // Remove trailing slash and query params\n const pathParts = path.split('?');\n const pathWithoutQuery = pathParts[0] ?? '';\n return (pathWithoutQuery !== '' ? pathWithoutQuery : '').replace(/\\/$/, '') || '/';\n}\n\n/**\n * Get current network quality\n */\nfunction getNetworkQuality(): string {\n const nav = navigator as Navigator & {\n connection?: { effectiveType?: string; saveData?: boolean };\n };\n return nav.connection?.effectiveType ?? 'unknown';\n}\n\n/**\n * Check if data saver is enabled\n */\nfunction isDataSaverEnabled(): boolean {\n const nav = navigator as Navigator & {\n connection?: { saveData?: boolean };\n };\n return nav.connection?.saveData ?? false;\n}\n\n// ============================================================================\n// Predictive Prefetch Engine\n// ============================================================================\n\n/**\n * Predictive prefetch engine that learns navigation patterns\n */\nexport class PredictivePrefetchEngine {\n private config: Required;\n private transitionMatrix: TransitionMatrix = new Map();\n private timePatterns: TimePattern[] = [];\n private sessionHistory: string[] = [];\n // Session ID for tracking navigation patterns\n private routeRegistry: Map = new Map();\n private prefetchedRoutes: Set = new Set();\n private queryClient: QueryClient | null = null;\n\n constructor(config: PredictivePrefetchConfig = {}) {\n this.config = { ...DEFAULT_CONFIG, ...config };\n this.loadPersistedPatterns();\n }\n\n // ==========================================================================\n // Initialization\n // ==========================================================================\n\n /**\n * Initialize with query client for data prefetching\n */\n setQueryClient(client: QueryClient): void {\n this.queryClient = client;\n }\n\n /**\n * Register routes available for prefetching\n */\n registerRoutes(routes: PrefetchableRoute[]): void {\n routes.forEach((route) => {\n this.routeRegistry.set(normalizePath(route.path), route);\n });\n this.log(`Registered ${routes.length} prefetchable routes`);\n }\n\n // ==========================================================================\n // Navigation Tracking\n // ==========================================================================\n\n /**\n * Record a navigation event for learning\n */\n recordNavigation(from: string, to: string): void {\n const normalizedFrom = normalizePath(from);\n const normalizedTo = normalizePath(to);\n\n // Skip if same page\n if (normalizedFrom === normalizedTo) return;\n\n // Record in session history\n this.sessionHistory.push(normalizedTo);\n if (this.sessionHistory.length > 20) {\n this.sessionHistory.shift();\n }\n\n // Update transition matrix\n if (this.config.enableLearning) {\n this.updateTransitionMatrix(normalizedFrom, normalizedTo);\n this.updateTimePatterns(normalizedTo);\n this.persistPatterns();\n }\n\n // Clear prefetch cache for new navigation\n this.prefetchedRoutes.clear();\n\n this.log(`Recorded navigation: ${normalizedFrom} -> ${normalizedTo}`);\n }\n\n /**\n * Get predicted next routes from current page\n */\n getPredictions(currentPath: string): RoutePrediction[] {\n const normalizedPath = normalizePath(currentPath);\n const predictions: RoutePrediction[] = [];\n\n // 1. Markov chain predictions\n const markovPredictions = this.getMarkovPredictions(normalizedPath);\n predictions.push(...markovPredictions);\n\n // 2. Time pattern predictions\n const timePredictions = this.getTimePatternPredictions();\n predictions.push(...timePredictions);\n\n // 3. Session context predictions\n const sessionPredictions = this.getSessionContextPredictions();\n predictions.push(...sessionPredictions);\n\n // 4. Static route priorities\n const staticPredictions = this.getStaticPredictions(normalizedPath);\n predictions.push(...staticPredictions);\n\n // Deduplicate and sort by probability\n const deduped = this.deduplicatePredictions(predictions);\n\n // Filter by threshold\n const filtered = deduped.filter(\n (p) => p.probability >= this.config.probabilityThreshold\n );\n\n this.log(`Predictions for ${normalizedPath}:`, filtered);\n\n return filtered.slice(0, this.config.maxPrefetchCount);\n }\n\n /**\n * Execute prefetch for predicted routes\n */\n async prefetchPredictedRoutes(currentPath: string): Promise {\n // Check network conditions\n if (!this.shouldPrefetch()) {\n this.log('Skipping prefetch due to network conditions');\n return;\n }\n\n const predictions = this.getPredictions(currentPath);\n\n for (const prediction of predictions) {\n await this.prefetchRoute(prediction.route);\n }\n }\n\n // ==========================================================================\n // Prediction\n // ==========================================================================\n\n /**\n * Prefetch a specific route\n */\n async prefetchRoute(routePath: string): Promise {\n const normalizedPath = normalizePath(routePath);\n\n // Skip if already prefetched\n if (this.prefetchedRoutes.has(normalizedPath)) {\n return;\n }\n\n const route = this.routeRegistry.get(normalizedPath);\n if (!route) {\n this.log(`Route not found in registry: ${normalizedPath}`);\n return;\n }\n\n this.prefetchedRoutes.add(normalizedPath);\n this.log(`Prefetching route: ${normalizedPath}`);\n\n // Prefetch module (code splitting)\n if (route.loader) {\n try {\n await route.loader();\n this.log(`Module prefetched: ${normalizedPath}`);\n } catch (error) {\n this.log(`Module prefetch failed: ${normalizedPath}`, error);\n }\n }\n\n // Prefetch data\n if (route.queries && this.queryClient) {\n for (const query of route.queries) {\n try {\n await this.queryClient.prefetchQuery({\n queryKey: query.queryKey,\n queryFn: query.queryFn,\n staleTime: query.staleTime ?? 5 * 60 * 1000,\n });\n this.log(`Data prefetched: ${JSON.stringify(query.queryKey)}`);\n } catch (error) {\n this.log(`Data prefetch failed: ${JSON.stringify(query.queryKey)}`, error);\n }\n }\n }\n\n // Preload static assets\n if (route.assets) {\n route.assets.forEach((asset) => {\n this.preloadAsset(asset);\n });\n }\n }\n\n /**\n * Clear all learned patterns\n */\n clearPatterns(): void {\n this.transitionMatrix.clear();\n this.timePatterns = [];\n this.sessionHistory = [];\n this.prefetchedRoutes.clear();\n localStorage.removeItem(this.config.storageKey);\n this.log('Cleared all patterns');\n }\n\n /**\n * Get analytics about learned patterns\n */\n getAnalytics(): {\n totalTransitions: number;\n uniqueRoutes: number;\n timePatterns: number;\n topRoutes: Array<{ route: string; visits: number }>;\n } {\n const routeVisits = new Map();\n\n this.transitionMatrix.forEach((transitions) => {\n transitions.forEach((count, route) => {\n routeVisits.set(route, (routeVisits.get(route) ?? 0) + count);\n });\n });\n\n const topRoutes = Array.from(routeVisits.entries())\n .sort(([, a], [, b]) => b - a)\n .slice(0, 10)\n .map(([route, visits]) => ({ route, visits: Math.round(visits) }));\n\n return {\n totalTransitions: Array.from(this.transitionMatrix.values())\n .flatMap((t) => Array.from(t.values()))\n .reduce((a, b) => a + b, 0),\n uniqueRoutes: new Set([\n ...this.transitionMatrix.keys(),\n ...Array.from(this.transitionMatrix.values()).flatMap((t) =>\n Array.from(t.keys())\n ),\n ]).size,\n timePatterns: this.timePatterns.length,\n topRoutes,\n };\n }\n\n /**\n * Update transition matrix with new navigation\n */\n private updateTransitionMatrix(from: string, to: string): void {\n if (!this.transitionMatrix.has(from)) {\n this.transitionMatrix.set(from, new Map());\n }\n\n const transitions = this.transitionMatrix.get(from);\n if (transitions == null) return;\n const currentCount = transitions.get(to) ?? 0;\n transitions.set(to, currentCount + 1);\n\n // Apply decay to all transitions from this page\n transitions.forEach((count, route) => {\n if (route !== to) {\n transitions.set(route, count * this.config.decayFactor);\n }\n });\n\n // Clean up near-zero transitions\n transitions.forEach((count, route) => {\n if (count < 0.1) {\n transitions.delete(route);\n }\n });\n }\n\n /**\n * Update time-based patterns\n */\n private updateTimePatterns(route: string): void {\n const timeOfDay = getTimeOfDay();\n const dayOfWeek = new Date().getDay();\n\n const existingPattern = this.timePatterns.find(\n (p) =>\n p.route === route &&\n p.timeOfDay === timeOfDay &&\n p.dayOfWeek === dayOfWeek\n );\n\n if (existingPattern) {\n existingPattern.count++;\n } else {\n this.timePatterns.push({\n route,\n timeOfDay,\n dayOfWeek,\n count: 1,\n });\n }\n\n // Limit time patterns\n if (this.timePatterns.length > 100) {\n this.timePatterns = this.timePatterns\n .sort((a, b) => b.count - a.count)\n .slice(0, 100);\n }\n }\n\n /**\n * Get predictions from transition matrix (Markov chain)\n */\n private getMarkovPredictions(currentPath: string): RoutePrediction[] {\n const transitions = this.transitionMatrix.get(currentPath);\n if (!transitions || transitions.size === 0) return [];\n\n const total = Array.from(transitions.values()).reduce((a, b) => a + b, 0);\n\n return Array.from(transitions.entries())\n .map(([route, count]) => ({\n route,\n probability: count / total,\n confidence: this.getConfidence(count / total),\n source: 'markov' as const,\n }))\n .filter((p) => p.probability > 0.1);\n }\n\n /**\n * Get predictions based on time patterns\n */\n private getTimePatternPredictions(): RoutePrediction[] {\n const timeOfDay = getTimeOfDay();\n const dayOfWeek = new Date().getDay();\n\n const relevantPatterns = this.timePatterns.filter(\n (p) => p.timeOfDay === timeOfDay && p.dayOfWeek === dayOfWeek\n );\n\n const totalCount = relevantPatterns.reduce((sum, p) => sum + p.count, 0);\n if (totalCount === 0) return [];\n\n return relevantPatterns.map((pattern) => ({\n route: pattern.route,\n probability: (pattern.count / totalCount) * 0.7, // Discount time patterns\n confidence: this.getConfidence((pattern.count / totalCount) * 0.7),\n source: 'time-pattern' as const,\n }));\n }\n\n // ==========================================================================\n // Prefetching\n // ==========================================================================\n\n /**\n * Get predictions based on session context\n */\n private getSessionContextPredictions(): RoutePrediction[] {\n if (this.sessionHistory.length < 2) return [];\n\n // Look for patterns in recent session\n const recentHistory = this.sessionHistory.slice(-5);\n const predictions: RoutePrediction[] = [];\n\n // Check if user is following a known path\n for (const [from, transitions] of this.transitionMatrix) {\n if (recentHistory.includes(from)) {\n const total = Array.from(transitions.values()).reduce((a, b) => a + b, 0);\n for (const [to, count] of transitions) {\n if (!recentHistory.includes(to)) {\n predictions.push({\n route: to,\n probability: (count / total) * 0.5, // Discount session context\n confidence: 'medium',\n source: 'session-context',\n });\n }\n }\n }\n }\n\n return predictions;\n }\n\n /**\n * Get static route predictions\n */\n private getStaticPredictions(currentPath: string): RoutePrediction[] {\n return Object.entries(this.config.staticRoutes)\n .filter(([route]) => route !== currentPath)\n .map(([route, priority]) => ({\n route,\n probability: priority / 10, // Convert priority to probability\n confidence: 'low' as const,\n source: 'static' as const,\n }));\n }\n\n /**\n * Deduplicate predictions, keeping highest probability\n */\n private deduplicatePredictions(predictions: RoutePrediction[]): RoutePrediction[] {\n const routeMap = new Map();\n\n predictions.forEach((prediction) => {\n const existing = routeMap.get(prediction.route);\n if (!existing || prediction.probability > existing.probability) {\n routeMap.set(prediction.route, prediction);\n }\n });\n\n return Array.from(routeMap.values()).sort(\n (a, b) => b.probability - a.probability\n );\n }\n\n /**\n * Get confidence level from probability\n */\n private getConfidence(probability: number): 'high' | 'medium' | 'low' {\n if (probability >= 0.7) return 'high';\n if (probability >= 0.4) return 'medium';\n return 'low';\n }\n\n // ==========================================================================\n // Persistence\n // ==========================================================================\n\n /**\n * Preload a static asset\n */\n private preloadAsset(url: string): void {\n const link = document.createElement('link');\n link.rel = 'prefetch';\n link.href = url;\n\n // Determine type from extension\n if (url.endsWith('.js') || url.endsWith('.mjs')) {\n link.as = 'script';\n } else if (url.endsWith('.css')) {\n link.as = 'style';\n } else if (/\\.(png|jpg|jpeg|gif|webp|avif|svg)$/i.test(url)) {\n link.as = 'image';\n } else if (/\\.(woff2?|eot|ttf|otf)$/i.test(url)) {\n link.as = 'font';\n link.crossOrigin = 'anonymous';\n }\n\n document.head.appendChild(link);\n this.log(`Asset prefetched: ${url}`);\n }\n\n /**\n * Check if prefetching should proceed\n */\n private shouldPrefetch(): boolean {\n // Check data saver\n if (this.config.respectDataSaver && isDataSaverEnabled()) {\n return false;\n }\n\n // Check network quality\n const quality = getNetworkQuality();\n const minQuality = this.config.minNetworkQuality;\n const qualityRank = NETWORK_QUALITY_RANK[quality] ?? 0;\n const minQualityRank = NETWORK_QUALITY_RANK[minQuality] ?? 0;\n const unknownRank = NETWORK_QUALITY_RANK['unknown'] ?? 0;\n return (\n qualityRank >= minQualityRank ||\n qualityRank >= unknownRank\n );\n }\n\n /**\n * Persist learned patterns to storage\n */\n private persistPatterns(): void {\n try {\n const data = {\n transitionMatrix: Array.from(this.transitionMatrix.entries()).map(\n ([from, transitions]) => [from, Array.from(transitions.entries())]\n ),\n timePatterns: this.timePatterns,\n version: 1,\n };\n\n localStorage.setItem(this.config.storageKey, JSON.stringify(data));\n } catch (error) {\n this.log('Failed to persist patterns:', error);\n }\n }\n\n // ==========================================================================\n // Analytics\n // ==========================================================================\n\n /**\n * Load persisted patterns from storage\n */\n private loadPersistedPatterns(): void {\n try {\n const stored = localStorage.getItem(this.config.storageKey);\n if (stored == null || stored === '') return;\n\n const data = JSON.parse(stored) as {\n transitionMatrix?: unknown;\n timePatterns?: unknown;\n version?: number;\n };\n if (data.version !== 1) return;\n\n // Restore transition matrix\n if (Array.isArray(data.transitionMatrix)) {\n this.transitionMatrix = new Map(\n (data.transitionMatrix as Array<[string, Array<[string, number]>]>).map(([from, transitions]) => [\n from,\n new Map(transitions),\n ])\n );\n }\n\n // Restore time patterns\n this.timePatterns = (Array.isArray(data.timePatterns) ? data.timePatterns : []) as TimePattern[];\n\n this.log('Loaded persisted patterns');\n } catch (error) {\n this.log('Failed to load persisted patterns:', error);\n }\n }\n\n // ==========================================================================\n // Debug\n // ==========================================================================\n\n private log(message: string, ...args: unknown[]): void {\n if (this.config.debug) {\n // eslint-disable-next-line no-console\n console.log(`[PredictivePrefetch] ${message}`, ...args);\n }\n }\n}\n\n// ============================================================================\n// Singleton Instance\n// ============================================================================\n\nlet engineInstance: PredictivePrefetchEngine | null = null;\n\n/**\n * Get or create the global PredictivePrefetchEngine instance\n */\nexport function getPredictivePrefetchEngine(\n config?: PredictivePrefetchConfig\n): PredictivePrefetchEngine {\n engineInstance ??= new PredictivePrefetchEngine(config);\n return engineInstance;\n}\n\n// ============================================================================\n// React Integration\n// ============================================================================\n\n/**\n * Hook options for usePredictivePrefetch\n */\nexport interface UsePredictivePrefetchOptions {\n /** Enable automatic prefetching on route change */\n autoPrefetch?: boolean;\n /** Delay before prefetching (ms) */\n prefetchDelay?: number;\n}\n\n/**\n * Create navigation listener for automatic tracking\n */\nexport function createNavigationListener(\n engine: PredictivePrefetchEngine,\n options: UsePredictivePrefetchOptions = {}\n): (location: { pathname: string }) => void {\n const { autoPrefetch = true, prefetchDelay = 500 } = options;\n let lastPath = '';\n\n return (location) => {\n const currentPath = location.pathname;\n\n if (lastPath && lastPath !== currentPath) {\n // Record navigation\n engine.recordNavigation(lastPath, currentPath);\n\n // Trigger prefetch after delay\n if (autoPrefetch) {\n setTimeout(() => {\n void engine.prefetchPredictedRoutes(currentPath);\n }, prefetchDelay);\n }\n }\n\n lastPath = currentPath;\n };\n}\n\n// ============================================================================\n// Exports\n// ============================================================================\n\nexport type { TransitionMatrix, TimePattern 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