import { SupportedLanguage, TranslationRequest } from './types';
import { SuperCacheManager } from './super-cache-manager';
/**
 * 预加载触发器类型
 */
export declare enum PreloadTrigger {
    TIME_BASED = "time_based",// 基于时间
    USAGE_BASED = "usage_based",// 基于使用频率
    PATTERN_BASED = "pattern_based",// 基于模式识别
    ML_PREDICTION = "ml_prediction",// 基于机器学习预测
    USER_BEHAVIOR = "user_behavior",// 基于用户行为
    CONTENT_ANALYSIS = "content_analysis",// 基于内容分析
    SEASONAL = "seasonal",// 基于季节性模式
    GEOGRAPHIC = "geographic"
}
/**
 * 预加载策略
 */
export declare enum PreloadStrategy {
    AGGRESSIVE = "aggressive",// 激进策略 - 预加载更多内容
    CONSERVATIVE = "conservative",// 保守策略 - 只预加载高置信度内容
    BALANCED = "balanced",// 平衡策略 - 在资源和效率间平衡
    ADAPTIVE = "adaptive",// 自适应策略 - 根据环境动态调整
    CONTEXT_AWARE = "context_aware"
}
/**
 * 预加载预测结果
 */
export interface PreloadPrediction {
    id: string;
    key: string;
    content?: TranslationRequest;
    targetLanguage: SupportedLanguage;
    confidence: number;
    priority: number;
    estimatedSize: number;
    estimatedLatency: number;
    triggerSource: PreloadTrigger;
    validUntil: number;
    metadata: {
        userContext?: any;
        locationContext?: any;
        timeContext?: any;
        contentContext?: any;
    };
}
/**
 * 预加载执行结果
 */
export interface PreloadExecutionResult {
    successful: number;
    failed: number;
    skipped: number;
    totalTime: number;
    memoryUsed: number;
    cacheHitImprovement: number;
    costBenefit: number;
}
/**
 * 用户行为模式
 */
export interface UserBehaviorPattern {
    userId: string;
    sessionPatterns: SessionPattern[];
    languagePreferences: SupportedLanguage[];
    contentTypePreferences: string[];
    peakUsageHours: number[];
    averageSessionDuration: number;
    translationVolume: number;
    patterns: {
        sequential: boolean;
        bursty: boolean;
        regular: boolean;
        exploratory: boolean;
    };
}
/**
 * 会话模式
 */
export interface SessionPattern {
    startTime: number;
    duration: number;
    requestCount: number;
    languagePairs: Array<{
        from: SupportedLanguage;
        to: SupportedLanguage;
    }>;
    contentTypes: string[];
    averageTextLength: number;
    requestFrequency: number;
}
/**
 * 内容分析结果
 */
export interface ContentAnalysis {
    textType: 'formal' | 'informal' | 'technical' | 'creative' | 'business';
    domain: string;
    complexity: number;
    length: number;
    keywords: string[];
    relatedTopics: string[];
    semanticFingerprint: number[];
    similarity: {
        high: string[];
        medium: string[];
        low: string[];
    };
}
/**
 * 地理位置上下文
 */
export interface GeographicContext {
    country: string;
    region: string;
    timezone: string;
    primaryLanguages: SupportedLanguage[];
    businessHours: {
        start: number;
        end: number;
    };
    culturalContext: string[];
    localHolidays: Date[];
    peakTranslationHours: number[];
}
/**
 * 智能预加载引擎 - 多维度预测和智能预加载
 */
export declare class IntelligentPreloadEngine {
    private cacheManager;
    private profiler;
    private strategy;
    private userBehaviorPatterns;
    private contentAnalysisCache;
    private seasonalPatterns;
    private geographicContexts;
    private isPreloadingActive;
    private preloadQueue;
    private executionHistory;
    private performanceMetrics;
    private predictionModel;
    constructor(cacheManager: SuperCacheManager, config?: {
        strategy?: PreloadStrategy;
        enableMLPrediction?: boolean;
        maxPreloadSize?: number;
        confidenceThreshold?: number;
        enableUserTracking?: boolean;
        enableContentAnalysis?: boolean;
    });
    /**
     * 生成预加载预测 - 主入口方法
     */
    generatePreloadPredictions(context?: {
        userId?: string;
        sessionId?: string;
        currentLanguage?: SupportedLanguage;
        targetLanguages?: SupportedLanguage[];
        geographicLocation?: string;
        timeWindow?: number;
        maxPredictions?: number;
    }): Promise<PreloadPrediction[]>;
    /**
     * 执行智能预加载
     */
    executeIntelligentPreload(predictions: PreloadPrediction[], options?: {
        maxConcurrency?: number;
        memoryLimit?: number;
        timeLimit?: number;
        strategy?: PreloadStrategy;
    }): Promise<PreloadExecutionResult>;
    /**
     * 基于用户行为预测
     */
    private predictFromUserBehavior;
    /**
     * 基于时间模式预测
     */
    private predictFromTimePatterns;
    /**
     * 基于内容分析预测
     */
    private predictFromContentAnalysis;
    /**
     * 基于地理位置预测
     */
    private predictFromGeographicContext;
    /**
     * 基于季节性模式预测
     */
    private predictFromSeasonalPatterns;
    /**
     * 基于机器学习预测
     */
    private predictFromMachineLearning;
    /**
     * 去重预测结果
     */
    private deduplicatePredictions;
    /**
     * 预测结果排序
     */
    private rankPredictions;
    /**
     * 获取时效性评分
     */
    private getTimelinessScore;
    /**
     * 创建预加载批次
     */
    private createPreloadBatches;
    /**
     * 执行单个预加载预测
     */
    private executePreloadPrediction;
    private createEmptyExecutionResult;
    private initializePredictionModel;
    /**
     * 获取性能统计
     */
    getPerformanceMetrics(): {
        totalPredictions: number;
        successfulPreloads: number;
        hitRateImprovement: number;
        averageConfidence: number;
        memoryEfficiency: number;
    };
    /**
     * 清理资源
     */
    cleanup(): void;
    private getTotalRemainingPredictions;
    private estimateCacheHitImprovement;
    private calculateCostBenefit;
    private updatePerformanceMetrics;
    private isLikelyNextTranslation;
    private calculateUserBehaviorConfidence;
    private getCommonContentForUser;
    private getTimeBasedHotContent;
    private isApproachingPeakTime;
    private getPeakTimeContent;
    private getNextPeakHour;
    private getRecentTranslationContent;
    private analyzeContent;
    private getContentByKeywords;
    private extractFeaturesForPrediction;
    private runMLPrediction;
    private getLocalPopularContent;
    private getCurrentLocalTime;
    private isInBusinessHours;
    private getBusinessHourContent;
    private getSeasonalContent;
    private isApproachingHoliday;
    private getHolidayContent;
}
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