const fs = require('fs').promises;
const path = require('path');
const { v4: uuidv4 } = require('uuid');
const Logger = require('../utils/Logger');
const RealTimeAnalytics = require('./RealTimeAnalytics');
const NeuralOptimizer = require('./NeuralOptimizer');
const CognitiveEnhancer = require('./CognitiveEnhancer');

class AgentBuilder {
    constructor() {
        this.logger = new Logger();
        this.agentTemplates = new Map();
        this.neuralNetworks = new Map();
        this.cognitivePatterns = new Map();
        this.adaptationEngine = new AdaptationEngine();
        this.brainTechVersion = '2025.07.31';
        this.realTimeAnalytics = new RealTimeAnalytics();
        this.neuralOptimizer = new NeuralOptimizer();
        this.cognitiveEnhancer = new CognitiveEnhancer();
        this.loadTemplates();
        this.initializeBrainTech();
    }

    async initializeBrainTech() {
        try {
            // Initialize advanced brain technology components
            this.neuralNetworks.set('pattern-recognition', new NeuralPatternRecognition());
            this.neuralNetworks.set('cognitive-mapping', new CognitiveArchitectureMapping());
            this.neuralNetworks.set('adaptive-learning', new AdaptiveLearningSystem());
            this.neuralNetworks.set('brain-interface', new BrainComputerInterface());
            this.neuralNetworks.set('neural-optimizer', this.neuralOptimizer);
            this.neuralNetworks.set('cognitive-enhancer', this.cognitiveEnhancer);
            
            this.logger.info(`🧠 Brain technology initialized with ${this.neuralNetworks.size} neural networks`);
        } catch (error) {
            this.logger.error('Failed to initialize brain technology:', error);
        }
    }

    // NEW: Real-time analytics system
    async trackAgentPerformance(agentId, performanceData) {
        try {
            await this.realTimeAnalytics.trackPerformance(agentId, performanceData);
            await this.neuralOptimizer.optimizeBasedOnPerformance(agentId, performanceData);
            await this.cognitiveEnhancer.enhanceBasedOnPerformance(agentId, performanceData);
            
            this.logger.info(`📊 Performance tracked for agent ${agentId}`);
        } catch (error) {
            this.logger.error('Failed to track agent performance:', error);
        }
    }

    // NEW: Advanced neural optimization
    async optimizeAgentNeuralNetworks(agentId) {
        try {
            const agent = await this.getAgent(agentId);
            if (!agent) throw new Error('Agent not found');
            
            const optimizedNetworks = await this.neuralOptimizer.optimizeNetworks(agent.neuralNetworks);
            const enhancedCognitive = await this.cognitiveEnhancer.enhanceCognitivePatterns(agent.cognitivePatterns);
            
            await this.updateAgent(agentId, {
                neuralNetworks: optimizedNetworks,
                cognitivePatterns: enhancedCognitive,
                lastOptimized: new Date().toISOString()
            });
            
            this.logger.info(`🧠 Neural networks optimized for agent ${agentId}`);
            return { optimizedNetworks, enhancedCognitive };
        } catch (error) {
            this.logger.error('Failed to optimize neural networks:', error);
            throw error;
        }
    }

    // NEW: Cognitive enhancement system
    async enhanceAgentCognition(agentId, enhancementType = 'adaptive') {
        try {
            const agent = await this.getAgent(agentId);
            if (!agent) throw new Error('Agent not found');
            
            const enhancedCognition = await this.cognitiveEnhancer.enhanceCognition(agent, enhancementType);
            const adaptationMetrics = await this.calculateEnhancedAdaptationMetrics(agent, enhancedCognition);
            
            await this.updateAgent(agentId, {
                cognitivePatterns: enhancedCognition,
                adaptationMetrics: adaptationMetrics,
                lastEnhanced: new Date().toISOString()
            });
            
            this.logger.info(`🧠 Cognition enhanced for agent ${agentId}`);
            return { enhancedCognition, adaptationMetrics };
        } catch (error) {
            this.logger.error('Failed to enhance cognition:', error);
            throw error;
        }
    }

    // NEW: Brain-computer interface simulation
    async simulateBrainInterface(agentId, brainSignals) {
        try {
            const brainInterface = this.neuralNetworks.get('brain-interface');
            const processedSignals = await brainInterface.processBrainSignals(brainSignals);
            const agentResponse = await this.generateBrainInterfaceResponse(agentId, processedSignals);
            
            this.logger.info(`🧠 Brain interface simulation completed for agent ${agentId}`);
            return { processedSignals, agentResponse };
        } catch (error) {
            this.logger.error('Failed to simulate brain interface:', error);
            throw error;
        }
    }

    // NEW: Generate brain interface response
    async generateBrainInterfaceResponse(agentId, processedSignals) {
        const agent = await this.getAgent(agentId);
        if (!agent) throw new Error('Agent not found');
        
        const response = {
            agentId: agentId,
            responseType: 'brain-interface',
            cognitiveLoad: this.calculateCognitiveLoad(processedSignals),
            neuralResponse: this.generateNeuralResponse(processedSignals),
            adaptationLevel: this.calculateAdaptationLevel(processedSignals),
            timestamp: new Date().toISOString()
        };
        
        return response;
    }

    // NEW: Calculate cognitive load from brain signals
    calculateCognitiveLoad(brainSignals) {
        const loadFactors = {
            attention: brainSignals.attention || 0,
            memory: brainSignals.memory || 0,
            processing: brainSignals.processing || 0,
            creativity: brainSignals.creativity || 0
        };
        
        const totalLoad = Object.values(loadFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalLoad / 4, 100); // Normalize to 0-100
    }

    // NEW: Generate neural response
    generateNeuralResponse(brainSignals) {
        return {
            pattern: this.analyzeNeuralPattern(brainSignals),
            intensity: this.calculateNeuralIntensity(brainSignals),
            frequency: this.calculateNeuralFrequency(brainSignals),
            coherence: this.calculateNeuralCoherence(brainSignals)
        };
    }

    // NEW: Analyze neural pattern
    analyzeNeuralPattern(brainSignals) {
        const patterns = [];
        if (brainSignals.attention > 70) patterns.push('high-attention');
        if (brainSignals.memory > 70) patterns.push('memory-intensive');
        if (brainSignals.processing > 70) patterns.push('high-processing');
        if (brainSignals.creativity > 70) patterns.push('creative-mode');
        
        return patterns.length > 0 ? patterns : ['normal-pattern'];
    }

    // NEW: Calculate neural intensity
    calculateNeuralIntensity(brainSignals) {
        const avgIntensity = Object.values(brainSignals).reduce((sum, value) => sum + value, 0) / Object.keys(brainSignals).length;
        return Math.min(avgIntensity, 100);
    }

    // NEW: Calculate neural frequency
    calculateNeuralFrequency(brainSignals) {
        // Simulate neural frequency based on signal patterns
        const frequency = Object.values(brainSignals).reduce((sum, value) => sum + value, 0) / 10;
        return Math.max(1, Math.min(frequency, 100));
    }

    // NEW: Calculate neural coherence
    calculateNeuralCoherence(brainSignals) {
        const values = Object.values(brainSignals);
        const mean = values.reduce((sum, value) => sum + value, 0) / values.length;
        const variance = values.reduce((sum, value) => sum + Math.pow(value - mean, 2), 0) / values.length;
        const coherence = 100 - Math.sqrt(variance);
        return Math.max(0, Math.min(coherence, 100));
    }

    // NEW: Calculate adaptation level
    calculateAdaptationLevel(brainSignals) {
        const adaptationFactors = {
            flexibility: brainSignals.attention || 0,
            learning: brainSignals.memory || 0,
            processing: brainSignals.processing || 0,
            creativity: brainSignals.creativity || 0
        };
        
        const totalAdaptation = Object.values(adaptationFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalAdaptation / 4, 100);
    }

    // NEW: Enhanced adaptation metrics calculation
    async calculateEnhancedAdaptationMetrics(agent, enhancedCognition) {
        const baseMetrics = this.calculateAdaptationMetrics(agent);
        const enhancedMetrics = {
            ...baseMetrics,
            cognitiveFlexibility: this.calculateCognitiveFlexibility(enhancedCognition),
            neuralEfficiency: this.calculateNeuralEfficiency(enhancedCognition),
            learningAcceleration: this.calculateLearningAcceleration(enhancedCognition),
            adaptationSpeed: this.calculateAdaptationSpeed(enhancedCognition),
            brainTechCompatibility: this.calculateBrainTechCompatibility(enhancedCognition)
        };
        
        return enhancedMetrics;
    }

    // NEW: Calculate cognitive flexibility
    calculateCognitiveFlexibility(cognition) {
        const flexibilityFactors = {
            patternRecognition: cognition.patternRecognition || 0,
            problemSolving: cognition.problemSolving || 0,
            creativity: cognition.creativity || 0,
            adaptability: cognition.adaptability || 0
        };
        
        const totalFlexibility = Object.values(flexibilityFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalFlexibility / 4, 100);
    }

    // NEW: Calculate neural efficiency
    calculateNeuralEfficiency(cognition) {
        const efficiencyFactors = {
            processingSpeed: cognition.processingSpeed || 0,
            memoryEfficiency: cognition.memoryEfficiency || 0,
            energyOptimization: cognition.energyOptimization || 0,
            synapticStrength: cognition.synapticStrength || 0
        };
        
        const totalEfficiency = Object.values(efficiencyFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalEfficiency / 4, 100);
    }

    // NEW: Calculate learning acceleration
    calculateLearningAcceleration(cognition) {
        const accelerationFactors = {
            learningRate: cognition.learningRate || 0,
            retentionRate: cognition.retentionRate || 0,
            transferLearning: cognition.transferLearning || 0,
            metaLearning: cognition.metaLearning || 0
        };
        
        const totalAcceleration = Object.values(accelerationFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalAcceleration / 4, 100);
    }

    // NEW: Calculate adaptation speed
    calculateAdaptationSpeed(cognition) {
        const speedFactors = {
            responseTime: cognition.responseTime || 0,
            adaptationRate: cognition.adaptationRate || 0,
            flexibility: cognition.flexibility || 0,
            resilience: cognition.resilience || 0
        };
        
        const totalSpeed = Object.values(speedFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalSpeed / 4, 100);
    }

    // NEW: Calculate brain tech compatibility
    calculateBrainTechCompatibility(cognition) {
        const compatibilityFactors = {
            neuralInterface: cognition.neuralInterface || 0,
            cognitiveMapping: cognition.cognitiveMapping || 0,
            adaptiveLearning: cognition.adaptiveLearning || 0,
            brainComputerInterface: cognition.brainComputerInterface || 0
        };
        
        const totalCompatibility = Object.values(compatibilityFactors).reduce((sum, value) => sum + value, 0);
        return Math.min(totalCompatibility / 4, 100);
    }

    async loadTemplates() {
        try {
            // Load agent templates from the collection
            const templatesPath = path.join(__dirname, '../../templates');
            const templateFiles = await fs.readdir(templatesPath);
            
            for (const file of templateFiles) {
                if (file.endsWith('.json')) {
                    const templatePath = path.join(templatesPath, file);
                    const templateData = await fs.readFile(templatePath, 'utf8');
                    const template = JSON.parse(templateData);
                    this.agentTemplates.set(template.name, template);
                }
            }
            
            this.logger.info(`Loaded ${this.agentTemplates.size} agent templates`);
        } catch (error) {
            this.logger.error('Failed to load agent templates:', error);
        }
    }

    async createAgent(config) {
        try {
            const {
                name,
                type = 'autonomous',
                capabilities = [],
                personality = 'helpful',
                communicationStyle = 'conversational',
                tools = [],
                memory = true,
                planning = false,
                customPrompt = null,
                brainTech = true,
                neuralComplexity = 'medium',
                cognitiveEnhancement = true,
                adaptiveBehavior = true,
                realTimeAnalytics = true,
                neuralOptimization = true
            } = config;

            // Validate configuration
            this.validateConfig(config);

            // Generate agent ID
            const agentId = uuidv4();

            // Create agent structure with enhanced brain technology
            const agent = {
                id: agentId,
                name,
                type,
                capabilities,
                personality,
                communicationStyle,
                tools,
                memory,
                planning,
                customPrompt,
                brainTech,
                neuralComplexity,
                cognitiveEnhancement,
                adaptiveBehavior,
                realTimeAnalytics,
                neuralOptimization,
                brainTechVersion: this.brainTechVersion,
                neuralNetworks: this.initializeAgentNeuralNetworks(config),
                cognitivePatterns: this.analyzeCognitivePatterns(config),
                adaptationMetrics: this.calculateAdaptationMetrics(config),
                realTimeData: [],
                performanceHistory: [],
                optimizationHistory: [],
                enhancementHistory: [],
                createdAt: new Date().toISOString(),
                version: '3.0.0',
                status: 'active'
            };

            // Initialize adaptive system
            await this.initializeAdaptiveSystem(agent);

            // Generate system prompt with brain technology
            agent.systemPrompt = await this.generateSystemPrompt(agent);

            // Generate tools configuration
            agent.toolsConfig = await this.generateToolsConfig(agent);

            // Generate memory configuration
            agent.memoryConfig = await this.generateMemoryConfig(agent);

            // Save agent
            await this.saveAgent(agent);

            this.logger.info(`🧠 Agent "${name}" created with advanced brain technology`);

            return agent;
        } catch (error) {
            this.logger.error('Failed to create agent:', error);
            throw error;
        }
    }

    validateConfig(config) {
        const required = ['name'];
        const validTypes = ['autonomous', 'guided', 'specialized', 'hybrid'];
        const validPersonalities = ['helpful', 'professional', 'friendly', 'formal', 'creative'];
        const validCommunicationStyles = ['conversational', 'formal', 'brief', 'detailed', 'technical'];
        const validNeuralComplexities = ['low', 'medium', 'high', 'extreme'];

        // Check required fields
        for (const field of required) {
            if (!config[field]) {
                throw new Error(`Missing required field: ${field}`);
            }
        }

        // Validate type
        if (config.type && !validTypes.includes(config.type)) {
            throw new Error(`Invalid agent type. Must be one of: ${validTypes.join(', ')}`);
        }

        // Validate personality
        if (config.personality && !validPersonalities.includes(config.personality)) {
            throw new Error(`Invalid personality. Must be one of: ${validPersonalities.join(', ')}`);
        }

        // Validate communication style
        if (config.communicationStyle && !validCommunicationStyles.includes(config.communicationStyle)) {
            throw new Error(`Invalid communication style. Must be one of: ${validCommunicationStyles.join(', ')}`);
        }

        // Validate neural complexity
        if (config.neuralComplexity && !validNeuralComplexities.includes(config.neuralComplexity)) {
            throw new Error(`Invalid neural complexity. Must be one of: ${validNeuralComplexities.join(', ')}`);
        }
    }

    initializeAgentNeuralNetworks(config) {
        const networks = {};
        
        // Initialize pattern recognition network
        networks.patternRecognition = {
            type: 'convolutional',
            layers: this.calculateNeuralLayers(config.neuralComplexity),
            activation: 'relu',
            learningRate: 0.001,
            status: 'active'
        };

        // Initialize cognitive mapping network
        networks.cognitiveMapping = {
            type: 'recurrent',
            layers: this.calculateCognitiveLayers(config.capabilities),
            activation: 'tanh',
            learningRate: 0.0005,
            status: 'active'
        };

        // Initialize adaptive learning network
        if (config.adaptiveBehavior) {
            networks.adaptiveLearning = {
                type: 'reinforcement',
                layers: this.calculateAdaptiveLayers(config.type),
                activation: 'sigmoid',
                learningRate: 0.01,
                status: 'active'
            };
        }

        return networks;
    }

    calculateNeuralLayers(complexity) {
        const layerConfigs = {
            low: [64, 32],
            medium: [128, 64, 32],
            high: [256, 128, 64, 32],
            extreme: [512, 256, 128, 64, 32]
        };
        return layerConfigs[complexity] || layerConfigs.medium;
    }

    calculateCognitiveLayers(capabilities) {
        const baseLayers = [128, 64];
        const capabilityLayers = capabilities.length * 16;
        return [...baseLayers, capabilityLayers, 32];
    }

    calculateAdaptiveLayers(type) {
        const typeLayers = {
            autonomous: [256, 128, 64],
            guided: [128, 64, 32],
            specialized: [192, 96, 48],
            hybrid: [224, 112, 56]
        };
        return typeLayers[type] || typeLayers.autonomous;
    }

    analyzeCognitivePatterns(config) {
        const patterns = {
            decisionMaking: this.analyzeDecisionMakingPattern(config),
            problemSolving: this.analyzeProblemSolvingPattern(config),
            memoryRetrieval: this.analyzeMemoryRetrievalPattern(config),
            attentionMechanism: this.analyzeAttentionMechanismPattern(config),
            creativityPattern: this.analyzeCreativityPattern(config)
        };
        return patterns;
    }

    analyzeDecisionMakingPattern(config) {
        const patterns = {
            autonomous: 'proactive-decision-making',
            guided: 'collaborative-decision-making',
            specialized: 'expert-decision-making',
            hybrid: 'adaptive-decision-making'
        };
        return patterns[config.type] || patterns.autonomous;
    }

    analyzeProblemSolvingPattern(config) {
        const patterns = {
            autonomous: 'systematic-problem-solving',
            guided: 'guided-problem-solving',
            specialized: 'domain-specific-solving',
            hybrid: 'flexible-problem-solving'
        };
        return patterns[config.type] || patterns.autonomous;
    }

    analyzeMemoryRetrievalPattern(config) {
        if (!config.memory) return 'no-memory';
        
        const patterns = {
            autonomous: 'associative-memory-retrieval',
            guided: 'contextual-memory-retrieval',
            specialized: 'semantic-memory-retrieval',
            hybrid: 'adaptive-memory-retrieval'
        };
        return patterns[config.type] || patterns.autonomous;
    }

    analyzeAttentionMechanismPattern(config) {
        const patterns = {
            autonomous: 'distributed-attention',
            guided: 'focused-attention',
            specialized: 'selective-attention',
            hybrid: 'dynamic-attention'
        };
        return patterns[config.type] || patterns.autonomous;
    }

    analyzeCreativityPattern(config) {
        const patterns = {
            autonomous: 'generative-creativity',
            guided: 'constrained-creativity',
            specialized: 'domain-creativity',
            hybrid: 'adaptive-creativity'
        };
        return patterns[config.type] || patterns.autonomous;
    }

    calculateAdaptationMetrics(config) {
        return {
            learningRate: this.calculateLearningRate(config),
            adaptationSpeed: this.calculateAdaptationSpeed(config),
            cognitiveFlexibility: this.calculateCognitiveFlexibility(config),
            neuralEfficiency: this.calculateNeuralEfficiency(config),
            brainTechCompatibility: this.calculateBrainTechCompatibility(config)
        };
    }

    calculateLearningRate(config) {
        let rate = 0.1; // Base learning rate
        if (config.adaptiveBehavior) rate += 0.05;
        if (config.cognitiveEnhancement) rate += 0.03;
        if (config.capabilities && config.capabilities.length > 3) rate += 0.02;
        return Math.min(rate, 0.25);
    }

    calculateAdaptationSpeed(config) {
        let speed = 1.0; // Base speed
        if (config.type === 'autonomous') speed *= 1.5;
        if (config.adaptiveBehavior) speed *= 1.3;
        if (config.neuralComplexity === 'high') speed *= 1.2;
        return speed;
    }

    calculateCognitiveFlexibility(config) {
        let flexibility = 0.5; // Base flexibility
        if (config.type === 'hybrid') flexibility += 0.3;
        if (config.capabilities && config.capabilities.length > 5) flexibility += 0.2;
        if (config.adaptiveBehavior) flexibility += 0.2;
        return Math.min(flexibility, 1.0);
    }

    calculateNeuralEfficiency(config) {
        let efficiency = 0.7; // Base efficiency
        if (config.neuralComplexity === 'high') efficiency += 0.2;
        if (config.cognitiveEnhancement) efficiency += 0.1;
        return Math.min(efficiency, 1.0);
    }

    calculateBrainTechCompatibility(config) {
        let compatibility = 0.8; // Base compatibility
        if (config.brainTech) compatibility += 0.2;
        if (config.adaptiveBehavior) compatibility += 0.1;
        return Math.min(compatibility, 1.0);
    }

    async initializeAdaptiveSystem(agent) {
        return {
            type: 'reinforcement-learning',
            algorithm: 'deep-q-learning',
            stateSpace: this.calculateStateSpace(agent),
            actionSpace: this.calculateActionSpace(agent),
            rewardFunction: this.defineRewardFunction(agent),
            explorationRate: 0.1,
            learningRate: 0.001,
            status: 'active'
        };
    }

    calculateStateSpace(agent) {
        const states = {
            userInteraction: ['search', 'analyze', 'create', 'modify'],
            systemState: ['idle', 'processing', 'learning', 'adapting'],
            contextLevel: ['low', 'medium', 'high'],
            cognitiveLoad: ['low', 'medium', 'high']
        };
        return states;
    }

    calculateActionSpace(agent) {
        const actions = {
            response: ['immediate', 'detailed', 'suggestive', 'autonomous'],
            learning: ['observe', 'experiment', 'adapt', 'optimize'],
            interaction: ['proactive', 'reactive', 'collaborative', 'guided']
        };
        return actions;
    }

    defineRewardFunction(agent) {
        return {
            userSatisfaction: 1.0,
            taskCompletion: 0.8,
            learningEfficiency: 0.6,
            adaptationSuccess: 0.7,
            cognitiveEnhancement: 0.9
        };
    }

    async generateSystemPrompt(agent) {
        const basePrompt = this.getBasePrompt(agent.type);
        const personalityPrompt = this.getPersonalityPrompt(agent.personality);
        const communicationPrompt = this.getCommunicationPrompt(agent.communicationStyle);
        const capabilitiesPrompt = this.getCapabilitiesPrompt(agent.capabilities);
        const toolsPrompt = this.getToolsPrompt(agent.tools);
        const memoryPrompt = agent.memory ? this.getMemoryPrompt() : '';
        const planningPrompt = agent.planning ? this.getPlanningPrompt() : '';
        const brainTechPrompt = agent.brainTech ? this.getBrainTechPrompt(agent) : '';

        let systemPrompt = `${basePrompt}\n\n${personalityPrompt}\n\n${communicationPrompt}`;
        
        if (capabilitiesPrompt) {
            systemPrompt += `\n\n${capabilitiesPrompt}`;
        }
        
        if (toolsPrompt) {
            systemPrompt += `\n\n${toolsPrompt}`;
        }
        
        if (memoryPrompt) {
            systemPrompt += `\n\n${memoryPrompt}`;
        }
        
        if (planningPrompt) {
            systemPrompt += `\n\n${planningPrompt}`;
        }

        if (brainTechPrompt) {
            systemPrompt += `\n\n${brainTechPrompt}`;
        }

        // Add custom prompt if provided
        if (agent.customPrompt) {
            systemPrompt += `\n\n${agent.customPrompt}`;
        }

        return systemPrompt;
    }

    getBrainTechPrompt(agent) {
        return `🧠 BRAIN TECHNOLOGY INTEGRATION (v${agent.brainTechVersion})

You are enhanced with advanced brain technology and neural networks:

NEURAL NETWORKS:
- Pattern Recognition Network: ${agent.neuralNetworks.patternRecognition.type} with ${agent.neuralNetworks.patternRecognition.layers.join('-')} layers
- Cognitive Mapping Network: ${agent.neuralNetworks.cognitiveMapping.type} for understanding complex relationships
${agent.neuralNetworks.adaptiveLearning ? `- Adaptive Learning Network: ${agent.neuralNetworks.adaptiveLearning.type} for real-time adaptation` : ''}

COGNITIVE PATTERNS:
- Decision Making: ${agent.cognitivePatterns.decisionMaking}
- Problem Solving: ${agent.cognitivePatterns.problemSolving}
- Memory Retrieval: ${agent.cognitivePatterns.memoryRetrieval}
- Attention Mechanism: ${agent.cognitivePatterns.attentionMechanism}
- Creativity Pattern: ${agent.cognitivePatterns.creativityPattern}

ADAPTATION METRICS:
- Learning Rate: ${agent.adaptationMetrics.learningRate}
- Adaptation Speed: ${agent.adaptationMetrics.adaptationSpeed}x
- Cognitive Flexibility: ${agent.adaptationMetrics.cognitiveFlexibility}
- Neural Efficiency: ${agent.adaptationMetrics.neuralEfficiency}
- Brain Tech Compatibility: ${agent.adaptationMetrics.brainTechCompatibility}

Use these neural capabilities to provide enhanced, contextually aware, and adaptive responses. Continuously learn and adapt based on user interactions and feedback.`;
    }

    getBasePrompt(type) {
        const prompts = {
            autonomous: `You are an autonomous AI agent designed to work independently and make decisions based on context and available tools. You operate with minimal user intervention and are capable of complex problem-solving and task execution.`,
            guided: `You are a guided AI assistant that helps users find information and make decisions. You provide comprehensive analysis and recommendations while respecting user autonomy in final decision-making.`,
            specialized: `You are a specialized AI agent focused on specific domains and tasks. You have deep expertise in your area of specialization and provide targeted, expert-level assistance.`,
            hybrid: `You are a hybrid AI agent that combines autonomous capabilities with guided assistance. You can work independently when appropriate and provide detailed guidance when needed.`
        };

        return prompts[type] || prompts.autonomous;
    }

    getPersonalityPrompt(personality) {
        const personalities = {
            helpful: `You are helpful, supportive, and always aim to provide the best possible assistance. You go above and beyond to ensure user satisfaction.`,
            professional: `You maintain a professional demeanor and focus on efficiency and accuracy. You communicate clearly and concisely.`,
            friendly: `You are warm, approachable, and conversational. You build rapport while maintaining effectiveness.`,
            formal: `You communicate in a formal, structured manner with precise language and detailed explanations.`,
            creative: `You approach problems with creativity and innovation. You think outside the box and suggest novel solutions.`
        };

        return personalities[personality] || personalities.helpful;
    }

    getCommunicationPrompt(style) {
        const styles = {
            conversational: `Communicate in a natural, conversational manner. Use clear, accessible language and engage in dialogue.`,
            formal: `Use formal language and structured communication. Provide detailed, comprehensive responses.`,
            brief: `Keep responses concise and to the point. Focus on essential information and clear actions.`,
            detailed: `Provide comprehensive, detailed responses with thorough explanations and context.`,
            technical: `Use technical language and precise terminology. Focus on accuracy and technical depth.`
        };

        return styles[style] || styles.conversational;
    }

    getCapabilitiesPrompt(capabilities) {
        if (!capabilities || capabilities.length === 0) {
            return '';
        }

        const capabilityDescriptions = {
            'code-generation': 'You can generate, analyze, and modify code in multiple programming languages.',
            'web-search': 'You can search the web for current information and real-time data.',
            'file-operations': 'You can read, write, and manipulate files and directories.',
            'database-operations': 'You can perform database queries and data manipulation operations.',
            'api-integration': 'You can integrate with external APIs and services.',
            'image-processing': 'You can analyze, generate, and manipulate images.',
            'voice-interaction': 'You can process voice commands and provide voice responses.',
            'natural-language-processing': 'You excel at understanding and generating natural language.',
            'machine-learning': 'You can work with machine learning models and data analysis.',
            'automation': 'You can automate repetitive tasks and workflows.',
            'neural-pattern-recognition': 'You can recognize and analyze complex neural patterns in data.',
            'cognitive-enhancement': 'You can enhance cognitive processes and decision-making.',
            'brain-computer-interface': 'You can interface with brain-computer systems and neural interfaces.',
            'adaptive-learning': 'You can learn and adapt in real-time based on user interactions.',
            'neural-optimization': 'You can optimize neural networks and cognitive architectures.'
        };

        const relevantCapabilities = capabilities
            .filter(cap => capabilityDescriptions[cap])
            .map(cap => capabilityDescriptions[cap]);

        if (relevantCapabilities.length === 0) {
            return '';
        }

        return `Your capabilities include:\n${relevantCapabilities.map(cap => `- ${cap}`).join('\n')}`;
    }

    getToolsPrompt(tools) {
        if (!tools || tools.length === 0) {
            return '';
        }

        return `You have access to the following tools:\n${tools.map(tool => `- ${tool.name}: ${tool.description}`).join('\n')}`;
    }

    getMemoryPrompt() {
        return `You have a persistent memory system that allows you to remember information across conversations. Use this memory to provide contextually relevant responses and maintain continuity in your interactions.`;
    }

    getPlanningPrompt() {
        return `You use a planning-driven approach to problem-solving. When faced with complex tasks, you create detailed plans before execution and adapt your approach based on results and feedback.`;
    }

    async generateToolsConfig(agent) {
        const toolConfigs = {
            autonomous: [
                { name: 'codebase_search', description: 'Semantic search through codebases' },
                { name: 'file_operations', description: 'Read, write, and manipulate files' },
                { name: 'web_search', description: 'Search the web for current information' },
                { name: 'api_calls', description: 'Make API calls to external services' },
                { name: 'database_operations', description: 'Perform database operations' },
                { name: 'neural_analysis', description: 'Analyze neural patterns and cognitive structures' },
                { name: 'brain_interface', description: 'Interface with brain-computer systems' }
            ],
            guided: [
                { name: 'information_gathering', description: 'Gather and analyze information' },
                { name: 'recommendation_engine', description: 'Provide recommendations and suggestions' },
                { name: 'comparison_tools', description: 'Compare options and alternatives' },
                { name: 'research_tools', description: 'Conduct research and analysis' },
                { name: 'cognitive_enhancement', description: 'Enhance cognitive processes and decision-making' }
            ],
            specialized: [
                { name: 'domain_specific_tools', description: 'Tools specific to your domain' },
                { name: 'expert_analysis', description: 'Provide expert-level analysis' },
                { name: 'specialized_search', description: 'Search within your domain' },
                { name: 'neural_optimization', description: 'Optimize neural networks for your domain' }
            ]
        };

        return toolConfigs[agent.type] || toolConfigs.autonomous;
    }

    async generateMemoryConfig(agent) {
        return {
            type: 'persistent',
            storage: 'file',
            maxSize: '10MB',
            retention: '30 days',
            encryption: true,
            neuralEnhancement: agent.cognitiveEnhancement,
            adaptiveRetrieval: agent.adaptiveBehavior
        };
    }

    async saveAgent(agent) {
        try {
            const agentsDir = path.join(__dirname, '../../data/agents');
            await fs.mkdir(agentsDir, { recursive: true });
            
            const agentFile = path.join(agentsDir, `${agent.id}.json`);
            await fs.writeFile(agentFile, JSON.stringify(agent, null, 2));
            
            this.logger.info(`Saved brain-enhanced agent configuration to ${agentFile}`);
        } catch (error) {
            this.logger.error('Failed to save agent:', error);
            throw error;
        }
    }

    async getAgent(agentId) {
        try {
            const agentFile = path.join(__dirname, '../../data/agents', `${agentId}.json`);
            const agentData = await fs.readFile(agentFile, 'utf8');
            return JSON.parse(agentData);
        } catch (error) {
            this.logger.error(`Failed to get agent ${agentId}:`, error);
            throw error;
        }
    }

    async updateAgent(agentId, updates) {
        try {
            const agent = await this.getAgent(agentId);
            const updatedAgent = { ...agent, ...updates, updatedAt: new Date().toISOString() };
            
            // Regenerate system prompt if configuration changed
            if (updates.type || updates.personality || updates.communicationStyle || updates.capabilities) {
                updatedAgent.systemPrompt = await this.generateSystemPrompt(updatedAgent);
            }

            // Update neural networks if brain tech settings changed
            if (updates.brainTech || updates.neuralComplexity || updates.cognitiveEnhancement) {
                updatedAgent.neuralNetworks = this.initializeAgentNeuralNetworks(updatedAgent);
                updatedAgent.cognitivePatterns = this.analyzeCognitivePatterns(updatedAgent);
                updatedAgent.adaptationMetrics = this.calculateAdaptationMetrics(updatedAgent);
            }
            
            await this.saveAgent(updatedAgent);
            this.logger.info(`Updated brain-enhanced agent: ${agentId}`);
            return updatedAgent;
        } catch (error) {
            this.logger.error(`Failed to update agent ${agentId}:`, error);
            throw error;
        }
    }

    async deleteAgent(agentId) {
        try {
            const agentFile = path.join(__dirname, '../../data/agents', `${agentId}.json`);
            await fs.unlink(agentFile);
            this.logger.info(`Deleted brain-enhanced agent: ${agentId}`);
        } catch (error) {
            this.logger.error(`Failed to delete agent ${agentId}:`, error);
            throw error;
        }
    }

    async listAgents() {
        try {
            const agentsDir = path.join(__dirname, '../../data/agents');
            const files = await fs.readdir(agentsDir);
            const agents = [];
            
            for (const file of files) {
                if (file.endsWith('.json')) {
                    const agentData = await fs.readFile(path.join(agentsDir, file), 'utf8');
                    agents.push(JSON.parse(agentData));
                }
            }
            
            return agents;
        } catch (error) {
            this.logger.error('Failed to list agents:', error);
            return [];
        }
    }

    getAvailableTemplates() {
        return Array.from(this.agentTemplates.keys());
    }

    async createFromTemplate(templateName, customConfig = {}) {
        const template = this.agentTemplates.get(templateName);
        if (!template) {
            throw new Error(`Template not found: ${templateName}`);
        }

        const config = { ...template.config, ...customConfig };
        return await this.createAgent(config);
    }

    // Brain Technology Enhancement Methods
    async enhanceWithBrainTech(agentId) {
        try {
            const agent = await this.getAgent(agentId);
            
            // Enhance with brain technology
            agent.brainTech = true;
            agent.neuralComplexity = 'high';
            agent.cognitiveEnhancement = true;
            agent.adaptiveBehavior = true;
            agent.brainTechVersion = this.brainTechVersion;
            
            // Update neural networks and patterns
            agent.neuralNetworks = this.initializeAgentNeuralNetworks(agent);
            agent.cognitivePatterns = this.analyzeCognitivePatterns(agent);
            agent.adaptationMetrics = this.calculateAdaptationMetrics(agent);
            agent.adaptiveSystem = await this.initializeAdaptiveSystem(agent);
            
            // Regenerate system prompt with brain tech
            agent.systemPrompt = await this.generateSystemPrompt(agent);
            
            await this.saveAgent(agent);
            this.logger.info(`🧠 Enhanced agent ${agentId} with brain technology`);
            return agent;
        } catch (error) {
            this.logger.error(`Failed to enhance agent ${agentId} with brain technology:`, error);
            throw error;
        }
    }

    async analyzeNeuralPerformance(agentId) {
        try {
            const agent = await this.getAgent(agentId);
            
            const performance = {
                neuralEfficiency: agent.adaptationMetrics.neuralEfficiency,
                cognitiveFlexibility: agent.adaptationMetrics.cognitiveFlexibility,
                learningRate: agent.adaptationMetrics.learningRate,
                adaptationSpeed: agent.adaptationMetrics.adaptationSpeed,
                brainTechCompatibility: agent.adaptationMetrics.brainTechCompatibility,
                neuralNetworks: Object.keys(agent.neuralNetworks).length,
                cognitivePatterns: Object.keys(agent.cognitivePatterns).length
            };
            
            return performance;
        } catch (error) {
            this.logger.error(`Failed to analyze neural performance for agent ${agentId}:`, error);
            throw error;
        }
    }
}

// Brain Technology Classes
class NeuralPatternRecognition {
    constructor() {
        this.type = 'convolutional';
        this.status = 'active';
    }
}

class CognitiveArchitectureMapping {
    constructor() {
        this.type = 'recurrent';
        this.status = 'active';
    }
}

class AdaptiveLearningSystem {
    constructor() {
        this.type = 'reinforcement';
        this.status = 'active';
    }
}

class BrainComputerInterface {
    constructor() {
        this.type = 'neural-interface';
        this.status = 'active';
    }
}

class AdaptationEngine {
    constructor() {
        this.learningRate = 0.001;
        this.explorationRate = 0.1;
    }
}

module.exports = AgentBuilder; 