/**
 * Training Pipeline - Automated neural model training and optimization
 *
 * Manages the continuous training pipeline for neural models, handling
 * data preparation, model training, validation, and deployment.
 */
import { EventEmitter } from 'eventemitter3';
import { ModelType, Agent, Task, OperationResult } from '../types';
import { NeuralModels, TrainingConfig } from './NeuralModels';
export interface TrainingJob {
    id: string;
    modelId: string;
    status: 'pending' | 'running' | 'completed' | 'failed';
    config: TrainingConfig;
    data: any[];
    startTime?: Date;
    endTime?: Date;
    progress: number;
    metrics?: any;
    error?: string;
}
export interface TrainingSchedule {
    modelId: string;
    interval: number;
    minDataSize: number;
    autoTriggers: string[];
    enabled: boolean;
}
export declare class TrainingPipeline extends EventEmitter {
    private neuralModels;
    private trainingQueue;
    private activeJobs;
    private schedules;
    private trainingData;
    private maxConcurrentJobs;
    private processingInterval;
    constructor(neuralModels: NeuralModels);
    initialize(): Promise<OperationResult>;
    private setupDefaultSchedules;
    private setupEventHandlers;
    private startProcessing;
    /**
     * Add training data for a specific model type
     */
    addTrainingData(modelType: ModelType, data: any[]): void;
    /**
     * Schedule a training job
     */
    scheduleTraining(modelId: string, config?: Partial<TrainingConfig>, priority?: number): Promise<string>;
    /**
     * Process the training queue
     */
    private processTrainingQueue;
    /**
     * Check if automatic training should be triggered
     */
    private checkAutoTraining;
    /**
     * Collect execution data for training
     */
    collectExecutionData(task: Task, agents: Agent[], result: any): Promise<void>;
    private estimateComplexity;
    private extractTaskPattern;
    private extractAgentPattern;
    private extractContextPattern;
    private calculateEfficiency;
    private getLastTrainingTime;
    /**
     * Get training job status
     */
    getJobStatus(jobId: string): TrainingJob | null;
    /**
     * Cancel a training job
     */
    cancelJob(jobId: string): boolean;
    /**
     * Update training schedule
     */
    updateSchedule(modelId: string, schedule: Partial<TrainingSchedule>): void;
    /**
     * Get pipeline metrics
     */
    getMetrics(): any;
    private handleTrainingStarted;
    private handleTrainingCompleted;
    private handleTrainingProgress;
    shutdown(): Promise<OperationResult>;
}
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