// PatternEvolutionEngine – Phase 2 Week 7-8
// Creative strategy evolution with mutation and A/B testing

import { projectMemory } from '../../services/project/ProjectMemory.js';
import { getDatabase } from '../../database/index.js';

interface Strategy {
    id: string;
    name: string;
    approach: string;
    timeout: number;
    retryCount: number;
    fitnessScore: number;
    createdAt: Date;
    adoptedAt?: Date;
}

interface MutationConfig {
    mutationRate: number;
    creativityFactor: number;
}

interface TestResult {
    strategy: Strategy;
    fitnessScore: number;
    testDuration: number;
    metrics: {
        successRate: number;
        avgLatency: number;
        userSatisfaction: number;
    };
}

export class PatternEvolutionEngine {
    private strategies: Map<string, Strategy> = new Map();
    private currentBestStrategy: Strategy | null = null;

    constructor() {
        this.loadStrategies();
    }

    /**
     * Main evolution loop
     */
    public async evolveStrategies(): Promise<void> {
        console.log('🧬 [Evolution] Starting strategy evolution...');

        // 1. Get current best strategy
        const currentStrategy = await this.getBestStrategy();

        if (!currentStrategy) {
            // Initialize with default strategy
            const defaultStrategy = this.createDefaultStrategy();
            await this.saveStrategy(defaultStrategy);
            this.currentBestStrategy = defaultStrategy;
            console.log('✅ [Evolution] Initialized with default strategy');
            return;
        }

        // 2. Generate mutations
        const mutations = this.generateMutations(currentStrategy, {
            mutationRate: 0.15,
            creativityFactor: 0.4
        });

        console.log(`🧬 [Evolution] Generated ${mutations.length} mutations`);

        // 3. A/B test mutations
        const testResults = await this.abTest(mutations);

        // 4. Select winners (must be >10% improvement)
        const winners = testResults.filter(r =>
            r.fitnessScore > currentStrategy.fitnessScore * 1.1
        );

        // 5. Adopt best winner if improvement found
        if (winners.length > 0) {
            const best = winners.sort((a, b) => b.fitnessScore - a.fitnessScore)[0];
            await this.adoptStrategy(best.strategy);

            // Log to ProjectMemory
            await this.logEvolution({
                oldStrategy: currentStrategy,
                newStrategy: best.strategy,
                improvement: best.fitnessScore / currentStrategy.fitnessScore,
                testResults: testResults.length
            });

            console.log(`✅ [Evolution] Adopted new strategy: ${best.strategy.name} (${((best.fitnessScore / currentStrategy.fitnessScore - 1) * 100).toFixed(1)}% improvement)`);
        } else {
            console.log('ℹ️ [Evolution] No improvement found, keeping current strategy');
        }
    }

    /**
     * Get current best strategy
     */
    private async getBestStrategy(): Promise<Strategy | null> {
        if (this.currentBestStrategy) {
            return this.currentBestStrategy;
        }

        // Load from database or memory
        const strategies = Array.from(this.strategies.values());
        if (strategies.length === 0) {
            return null;
        }

        const best = strategies.sort((a, b) => b.fitnessScore - a.fitnessScore)[0];
        this.currentBestStrategy = best;
        return best;
    }

    /**
     * Generate strategy mutations
     */
    private generateMutations(strategy: Strategy, config: MutationConfig): Strategy[] {
        const mutations: Strategy[] = [];

        for (let i = 0; i < 10; i++) {
            const mutated: Strategy = {
                ...strategy,
                id: `${strategy.id}-mut-${i}-${Date.now()}`,
                name: `${strategy.name} Mutation ${i + 1}`,
                fitnessScore: strategy.fitnessScore, // Will be updated after testing
                createdAt: new Date()
            };

            // Mutate timeout
            if (Math.random() < config.mutationRate) {
                mutated.timeout = Math.max(100, strategy.timeout * (1 + (Math.random() - 0.5) * 0.3));
            }

            // Mutate retry count
            if (Math.random() < config.mutationRate) {
                mutated.retryCount = Math.max(0, strategy.retryCount + Math.floor((Math.random() - 0.5) * 2));
            }

            // Creative mutations (approach changes)
            if (Math.random() < config.creativityFactor) {
                mutated.approach = this.generateCreativeApproach(strategy.approach);
            }

            mutations.push(mutated);
        }

        return mutations;
    }

    /**
     * Generate creative approach variations
     */
    private generateCreativeApproach(currentApproach: string): string {
        const variations = [
            'aggressive', 'conservative', 'balanced', 'adaptive', 'predictive'
        ];
        
        const randomVariation = variations[Math.floor(Math.random() * variations.length)];
        return `${randomVariation}_${currentApproach}`;
    }

    /**
     * A/B test mutations
     */
    private async abTest(mutations: Strategy[]): Promise<TestResult[]> {
        const results: TestResult[] = [];

        for (const mutation of mutations) {
            // Simulate testing (in real implementation, this would run actual tests)
            const testResult = await this.simulateTest(mutation);
            results.push(testResult);
        }

        return results;
    }

    /**
     * Simulate strategy test (placeholder - should run actual tests)
     */
    private async simulateTest(strategy: Strategy): Promise<TestResult> {
        // Simulate fitness calculation based on strategy parameters
        const baseFitness = 0.5;
        
        // Timeout optimization: shorter is better (up to a point)
        const timeoutScore = Math.max(0, 1 - (strategy.timeout / 5000));
        
        // Retry optimization: balanced retries are better
        const retryScore = strategy.retryCount <= 3 ? 1.0 : Math.max(0, 1 - (strategy.retryCount - 3) * 0.2);
        
        // Approach bonus (creative approaches get slight bonus)
        const approachBonus = strategy.approach.includes('adaptive') || strategy.approach.includes('predictive') ? 0.1 : 0;
        
        const fitnessScore = baseFitness + timeoutScore * 0.3 + retryScore * 0.2 + approachBonus;

        return {
            strategy,
            fitnessScore: Math.min(1.0, fitnessScore),
            testDuration: 1000 + Math.random() * 2000,
            metrics: {
                successRate: 0.7 + Math.random() * 0.25,
                avgLatency: strategy.timeout * (0.8 + Math.random() * 0.4),
                userSatisfaction: fitnessScore
            }
        };
    }

    /**
     * Adopt new strategy
     */
    private async adoptStrategy(strategy: Strategy): Promise<void> {
        strategy.adoptedAt = new Date();
        await this.saveStrategy(strategy);
        this.currentBestStrategy = strategy;
        this.strategies.set(strategy.id, strategy);
    }

    /**
     * Create default strategy
     */
    private createDefaultStrategy(): Strategy {
        return {
            id: 'default-strategy',
            name: 'Default Strategy',
            approach: 'balanced',
            timeout: 3000,
            retryCount: 2,
            fitnessScore: 0.5,
            createdAt: new Date()
        };
    }

    /**
     * Save strategy (placeholder - should persist to database)
     */
    private async saveStrategy(strategy: Strategy): Promise<void> {
        this.strategies.set(strategy.id, strategy);
        // TODO: Persist to database
    }

    /**
     * Load strategies (placeholder)
     */
    private loadStrategies(): void {
        // TODO: Load from database
    }

    /**
     * Log evolution to ProjectMemory
     */
    private async logEvolution(evolution: {
        oldStrategy: Strategy;
        newStrategy: Strategy;
        improvement: number;
        testResults: number;
    }): Promise<void> {
        projectMemory.logLifecycleEvent({
            eventType: 'feature',
            status: 'success',
            details: {
                component: 'PatternEvolutionEngine',
                action: 'strategy_evolution',
                oldStrategy: evolution.oldStrategy.name,
                newStrategy: evolution.newStrategy.name,
                improvement: `${((evolution.improvement - 1) * 100).toFixed(1)}%`,
                testResults: evolution.testResults,
                timestamp: new Date().toISOString()
            }
        });
    }

    /**
     * Get current strategy
     */
    public getCurrentStrategy(): Strategy | null {
        return this.currentBestStrategy;
    }

    /**
     * Get evolution history
     */
    public getEvolutionHistory(): Strategy[] {
        return Array.from(this.strategies.values())
            .filter(s => s.adoptedAt)
            .sort((a, b) => (b.adoptedAt?.getTime() || 0) - (a.adoptedAt?.getTime() || 0));
    }
}

export const patternEvolutionEngine = new PatternEvolutionEngine();