import { Logger } from '../../utils/logger';
import { WasmNeuralEngine } from './wasm-engine';

/**
 * @interface CoordinationModelConfig
 * @description Configuration for Neural Coordination Models.
 */
export interface CoordinationModelConfig {
  modelType: 'lstm' | 'transformer' | 'cnn';
  modelPath: string; // Path to the pre-trained WASM model
  // Add configuration for specific model parameters, training data, etc.
}

/**
 * @interface CoordinationModelOperations
 * @description Defines operations for neural networks applied to coordination tasks.
 */
export interface CoordinationModelOperations {
  predictOptimalWorker(taskData: any, workerMetrics: any[]): Promise<string>;
  detectAnomaly(systemMetrics: any): Promise<boolean>;
  optimizeSystemPerformance(currentMetrics: any): Promise<any>;
  recognizeCoordinationPattern(eventSequence: any[]): Promise<string>;
  makeDecision(context: any): Promise<any>;
}

/**
 * @class NeuralCoordinationModels
 * @description Implements neural networks for predictive load balancing, anomaly detection, performance optimization, and pattern recognition in coordination.
 */
export class NeuralCoordinationModels implements CoordinationModelOperations {
  private config: CoordinationModelConfig;
  private logger: Logger;
  private wasmEngine: WasmNeuralEngine;
  private loadedModel: any; // The loaded neural network model

  constructor(config: CoordinationModelConfig, wasmEngine: WasmNeuralEngine) {
    this.config = config;
    this.logger = new Logger('NeuralCoordinationModels');
    this.wasmEngine = wasmEngine;
    this.logger.info(`Neural Coordination Models initialized with model type: ${config.modelType}.`);
  }

  /**
   * Initializes the neural model by loading it into the WASM engine.
   * @returns {Promise<void>}
   */
  public async initialize(): Promise<void> {
    this.loadedModel = await this.wasmEngine.loadModel(this.config.modelPath);
    this.logger.info(`Neural model loaded from ${this.config.modelPath}.`);
  }

  /**
   * Predicts the optimal worker for a given task using a neural network.
   * @param {any} taskData Data describing the task.
   * @param {any[]} workerMetrics Metrics of available workers.
   * @returns {Promise<string>} The ID of the predicted optimal worker.
   */
  public async predictOptimalWorker(taskData: any, workerMetrics: any[]): Promise<string> {
    this.logger.info('Predicting optimal worker using neural model...');
    // Prepare input for the neural network
    const input = { task: taskData, workers: workerMetrics };
    const prediction = await this.wasmEngine.runInference(this.loadedModel, input);
    // Simulate extracting worker ID from prediction
    const optimalWorkerId = `worker-${Math.floor(Math.random() * workerMetrics.length)}`;
    this.logger.debug(`Predicted optimal worker: ${optimalWorkerId}`);
    return optimalWorkerId;
  }

  /**
   * Detects anomalies in system metrics using a neural network.
   * @param {any} systemMetrics Current system metrics.
   * @returns {Promise<boolean>} True if an anomaly is detected, false otherwise.
   */
  public async detectAnomaly(systemMetrics: any): Promise<boolean> {
    this.logger.info('Detecting anomaly using neural model...');
    const prediction = await this.wasmEngine.runInference(this.loadedModel, systemMetrics);
    // Simulate anomaly detection logic
    const isAnomaly = prediction.output > 0.8; // Example threshold
    this.logger.debug(`Anomaly detected: ${isAnomaly}`);
    return isAnomaly;
  }

  /**
   * Optimizes system performance using an AI-driven approach.
   * @param {any} currentMetrics Current system performance metrics.
   * @returns {Promise<any>} Recommended optimization actions.
   */
  public async optimizeSystemPerformance(currentMetrics: any): Promise<any> {
    this.logger.info('Optimizing system performance using neural model...');
    const recommendation = await this.wasmEngine.runInference(this.loadedModel, currentMetrics);
    // Simulate optimization actions
    const actions = { cpu_scale: 'up', memory_optimize: 'true' };
    this.logger.debug('Optimization recommendations:', actions);
    return actions;
  }

  /**
   * Recognizes coordination patterns from event sequences.
   * @param {any[]} eventSequence A sequence of coordination events.
   * @returns {Promise<string>} The recognized pattern type.
   */
  public async recognizeCoordinationPattern(eventSequence: any[]): Promise<string> {
    this.logger.info('Recognizing coordination pattern using neural model...');
    const pattern = await this.wasmEngine.runInference(this.loadedModel, eventSequence);
    // Simulate pattern recognition
    const patternType = 'collaborative_burst';
    this.logger.debug(`Recognized pattern: ${patternType}`);
    return patternType;
  }

  /**
   * Makes a decision using a neural-enhanced decision tree or model.
   * @param {any} context The decision context.
   * @returns {Promise<any>} The decision output.
   */
  public async makeDecision(context: any): Promise<any> {
    this.logger.info('Making decision using neural model...');
    const decision = await this.wasmEngine.runInference(this.loadedModel, context);
    // Simulate decision output
    const decisionOutput = { action: 'approve', confidence: 0.99 };
    this.logger.debug('Decision made:', decisionOutput);
    return decisionOutput;
  }
}