zai-mcp-server/src/specializedAgentSystem.js

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/**
 * Specialized Agent System
 * Provides dedicated agents for different tasks, consensus mechanisms, learning system, and cross-loop communication
 */

import { EventEmitter } from 'events';

export class SpecializedAgentSystem extends EventEmitter {
    constructor() {
        super();
        this.agents = new Map();
        this.agentRoles = new Map();
        this.consensusEngine = new ConsensusEngine();
        this.learningSystem = new AgentLearningSystem();
        this.communicationHub = new CrossLoopCommunicationHub();
        this.performanceTracker = new AgentPerformanceTracker();
        
        this.initializeAgentRoles();
        this.createSpecializedAgents();
        
        console.log('🤖 Specialized Agent System initialized with multi-role AI agents');
    }

    /**
     * Initialize agent role definitions
     */
    initializeAgentRoles() {
        this.agentRoles.set('coordinator', {
            name: 'Coordinator Agent',
            description: 'Orchestrates tasks and manages workflow coordination',
            capabilities: ['task_planning', 'resource_allocation', 'progress_monitoring', 'conflict_resolution'],
            specializations: ['project_management', 'workflow_optimization', 'team_coordination'],
            priority: 'high',
            autonomyLevel: 0.8
        });

        this.agentRoles.set('implementer', {
            name: 'Implementation Agent',
            description: 'Handles code implementation and technical execution',
            capabilities: ['code_generation', 'algorithm_implementation', 'debugging', 'optimization'],
            specializations: ['software_development', 'system_architecture', 'performance_tuning'],
            priority: 'high',
            autonomyLevel: 0.7
        });

        this.agentRoles.set('tester', {
            name: 'Testing Agent',
            description: 'Performs comprehensive testing and quality assurance',
            capabilities: ['test_design', 'test_execution', 'bug_detection', 'quality_assessment'],
            specializations: ['unit_testing', 'integration_testing', 'performance_testing', 'security_testing'],
            priority: 'medium',
            autonomyLevel: 0.6
        });

        this.agentRoles.set('documenter', {
            name: 'Documentation Agent',
            description: 'Creates and maintains comprehensive documentation',
            capabilities: ['documentation_writing', 'api_documentation', 'user_guides', 'technical_specs'],
            specializations: ['technical_writing', 'user_experience', 'knowledge_management'],
            priority: 'medium',
            autonomyLevel: 0.5
        });

        this.agentRoles.set('optimizer', {
            name: 'Optimization Agent',
            description: 'Focuses on performance optimization and efficiency improvements',
            capabilities: ['performance_analysis', 'bottleneck_identification', 'optimization_strategies', 'resource_efficiency'],
            specializations: ['algorithm_optimization', 'system_performance', 'resource_management'],
            priority: 'medium',
            autonomyLevel: 0.7
        });

        this.agentRoles.set('security', {
            name: 'Security Agent',
            description: 'Handles security analysis and vulnerability assessment',
            capabilities: ['security_analysis', 'vulnerability_scanning', 'threat_assessment', 'security_recommendations'],
            specializations: ['cybersecurity', 'code_security', 'system_hardening'],
            priority: 'high',
            autonomyLevel: 0.6
        });

        this.agentRoles.set('analyst', {
            name: 'Analysis Agent',
            description: 'Performs data analysis and insight generation',
            capabilities: ['data_analysis', 'pattern_recognition', 'trend_analysis', 'reporting'],
            specializations: ['business_intelligence', 'predictive_analytics', 'statistical_analysis'],
            priority: 'medium',
            autonomyLevel: 0.6
        });
    }

    /**
     * Create specialized agents based on roles
     */
    createSpecializedAgents() {
        for (const [roleId, roleDefinition] of this.agentRoles) {
            const agent = new SpecializedAgent(roleId, roleDefinition, this);
            this.agents.set(agent.id, agent);
            
            console.log(`🤖 Created ${roleDefinition.name} (${agent.id})`);
        }

        // Set up agent communication channels
        this.setupAgentCommunication();
    }

    /**
     * Setup communication channels between agents
     */
    setupAgentCommunication() {
        for (const agent of this.agents.values()) {
            agent.on('taskRequest', (request) => this.handleAgentTaskRequest(request));
            agent.on('collaborationRequest', (request) => this.handleCollaborationRequest(request));
            agent.on('knowledgeShare', (knowledge) => this.handleKnowledgeSharing(knowledge));
            agent.on('consensusRequest', (request) => this.handleConsensusRequest(request));
        }
    }

    /**
     * Assign task to most suitable agent
     */
    async assignTask(task, loopId) {
        console.log(`🎯 [${loopId}] Assigning task: ${task.type}`);

        // Find best agent for the task
        const suitableAgents = this.findSuitableAgents(task);
        if (suitableAgents.length === 0) {
            throw new Error(`No suitable agent found for task type: ${task.type}`);
        }

        // Select best agent based on performance and availability
        const selectedAgent = await this.selectBestAgent(suitableAgents, task);
        
        // Assign task to agent
        const assignment = await selectedAgent.assignTask(task, loopId);
        
        // Track assignment
        this.performanceTracker.trackAssignment(selectedAgent.id, task, assignment);
        
        console.log(`✅ [${loopId}] Task assigned to ${selectedAgent.role} agent (${selectedAgent.id})`);
        return assignment;
    }

    /**
     * Agent Consensus Mechanisms - Multiple agents vote on decisions
     */
    async requestConsensus(decision, loopId, participantRoles = []) {
        console.log(`🗳️ [${loopId}] Requesting consensus for: ${decision.topic}`);

        // Select participating agents
        const participants = participantRoles.length > 0 
            ? this.getAgentsByRoles(participantRoles)
            : Array.from(this.agents.values()).slice(0, 5); // Limit to 5 agents

        // Collect votes from agents
        const votes = await Promise.allSettled(
            participants.map(agent => agent.vote(decision, loopId))
        );

        const validVotes = votes
            .filter(vote => vote.status === 'fulfilled')
            .map(vote => vote.value);

        // Process consensus
        const consensusResult = await this.consensusEngine.processVotes(validVotes, decision);
        
        // Learn from consensus outcome
        await this.learningSystem.learnFromConsensus(consensusResult, participants, decision);

        console.log(`✅ [${loopId}] Consensus reached: ${consensusResult.decision} (confidence: ${consensusResult.confidence})`);
        return consensusResult;
    }

    /**
     * Agent Learning System - Agents improve based on loop outcomes
     */
    async updateAgentLearning(loopId, outcomes) {
        console.log(`🧠 [${loopId}] Updating agent learning from loop outcomes...`);

        const learningUpdates = [];
        
        for (const agent of this.agents.values()) {
            try {
                const update = await this.learningSystem.updateAgentKnowledge(agent, outcomes, loopId);
                learningUpdates.push(update);
                
                if (update.significantImprovement) {
                    console.log(`📈 [${loopId}] ${agent.role} agent learned: ${update.newKnowledge}`);
                }
            } catch (error) {
                console.error(`❌ [${loopId}] Learning update failed for ${agent.role} agent:`, error.message);
            }
        }

        // Share learning across agents
        await this.shareCollectiveLearning(learningUpdates, loopId);

        return {
            updatedAgents: learningUpdates.length,
            significantImprovements: learningUpdates.filter(u => u.significantImprovement).length,
            newKnowledgeItems: learningUpdates.reduce((sum, u) => sum + u.newKnowledgeCount, 0)
        };
    }

    /**
     * Cross-Loop Agent Communication - Agents share knowledge between loops
     */
    async enableCrossLoopCommunication(sourceLoopId, targetLoopId, knowledgeTypes = []) {
        console.log(`🔗 Enabling cross-loop communication: ${sourceLoopId} → ${targetLoopId}`);

        const communicationChannel = await this.communicationHub.createChannel(sourceLoopId, targetLoopId);
        
        // Share relevant knowledge
        const sharedKnowledge = await this.communicationHub.shareKnowledge(
            sourceLoopId, 
            targetLoopId, 
            knowledgeTypes
        );

        // Update agents in target loop with shared knowledge
        const targetAgents = this.getAgentsByLoop(targetLoopId);
        for (const agent of targetAgents) {
            await agent.receiveSharedKnowledge(sharedKnowledge, sourceLoopId);
        }

        console.log(`✅ Cross-loop communication established: ${sharedKnowledge.items.length} knowledge items shared`);
        return {
            channelId: communicationChannel.id,
            sharedItems: sharedKnowledge.items.length,
            targetAgents: targetAgents.length
        };
    }

    /**
     * Multi-agent collaboration for complex tasks
     */
    async collaborateOnTask(task, loopId, requiredRoles = []) {
        console.log(`🤝 [${loopId}] Starting multi-agent collaboration for: ${task.type}`);

        // Select collaboration team
        const team = this.assembleCollaborationTeam(task, requiredRoles);
        
        // Create collaboration session
        const session = {
            id: `collab_${loopId}_${Date.now()}`,
            task,
            team: team.map(agent => agent.id),
            loopId,
            startTime: Date.now(),
            phases: ['planning', 'execution', 'review', 'consensus'],
            currentPhase: 0,
            results: []
        };

        // Execute collaboration phases
        for (const phase of session.phases) {
            console.log(`🔄 [${loopId}] Collaboration phase: ${phase}`);
            
            const phaseResult = await this.executeCollaborationPhase(session, phase, team);
            session.results.push(phaseResult);
            session.currentPhase++;
        }

        // Finalize collaboration
        const finalResult = await this.finalizeCollaboration(session, team);
        
        console.log(`✅ [${loopId}] Multi-agent collaboration completed: ${finalResult.outcome}`);
        return finalResult;
    }

    // Helper methods
    findSuitableAgents(task) {
        const suitableAgents = [];
        
        for (const agent of this.agents.values()) {
            const suitabilityScore = agent.calculateSuitability(task);
            if (suitabilityScore > 0.5) {
                suitableAgents.push({ agent, score: suitabilityScore });
            }
        }

        return suitableAgents
            .sort((a, b) => b.score - a.score)
            .map(item => item.agent);
    }

    async selectBestAgent(candidates, task) {
        // Consider performance history, current load, and specialization
        let bestAgent = candidates[0];
        let bestScore = 0;

        for (const agent of candidates) {
            const performance = this.performanceTracker.getAgentPerformance(agent.id);
            const load = agent.getCurrentLoad();
            const specialization = agent.getSpecializationScore(task);
            
            const score = (performance * 0.4) + ((1 - load) * 0.3) + (specialization * 0.3);
            
            if (score > bestScore) {
                bestScore = score;
                bestAgent = agent;
            }
        }

        return bestAgent;
    }

    getAgentsByRoles(roles) {
        return Array.from(this.agents.values()).filter(agent => roles.includes(agent.role));
    }

    getAgentsByLoop(loopId) {
        return Array.from(this.agents.values()).filter(agent => agent.activeLoops.includes(loopId));
    }

    assembleCollaborationTeam(task, requiredRoles) {
        const team = [];
        
        // Add required roles
        for (const role of requiredRoles) {
            const agent = this.getAgentsByRoles([role])[0];
            if (agent) team.push(agent);
        }

        // Add suitable agents based on task
        const suitableAgents = this.findSuitableAgents(task).slice(0, 3);
        for (const agent of suitableAgents) {
            if (!team.includes(agent)) {
                team.push(agent);
            }
        }

        return team;
    }

    async executeCollaborationPhase(session, phase, team) {
        const phaseResults = await Promise.allSettled(
            team.map(agent => agent.participateInPhase(session, phase))
        );

        const successfulResults = phaseResults
            .filter(result => result.status === 'fulfilled')
            .map(result => result.value);

        return {
            phase,
            participantCount: team.length,
            successfulParticipants: successfulResults.length,
            contributions: successfulResults,
            duration: Date.now() - session.startTime
        };
    }

    async finalizeCollaboration(session, team) {
        // Aggregate results from all phases
        const allContributions = session.results.flatMap(r => r.contributions);
        
        // Request final consensus
        const finalDecision = await this.requestConsensus({
            topic: 'collaboration_outcome',
            options: allContributions.map(c => c.recommendation),
            context: session.task
        }, session.loopId, team.map(agent => agent.role));

        return {
            sessionId: session.id,
            outcome: finalDecision.decision,
            confidence: finalDecision.confidence,
            participantCount: team.length,
            totalContributions: allContributions.length,
            duration: Date.now() - session.startTime
        };
    }

    async shareCollectiveLearning(learningUpdates, loopId) {
        const significantLearning = learningUpdates.filter(u => u.significantImprovement);
        
        if (significantLearning.length > 0) {
            // Share learning across all agents
            for (const agent of this.agents.values()) {
                await agent.receiveCollectiveLearning(significantLearning, loopId);
            }
            
            console.log(`🧠 [${loopId}] Shared ${significantLearning.length} significant learning items across all agents`);
        }
    }

    // Event handlers
    async handleAgentTaskRequest(request) {
        // Handle task requests from agents
        console.log(`📋 Agent ${request.agentId} requesting task: ${request.taskType}`);
    }

    async handleCollaborationRequest(request) {
        // Handle collaboration requests
        console.log(`🤝 Agent ${request.agentId} requesting collaboration for: ${request.purpose}`);
    }

    async handleKnowledgeSharing(knowledge) {
        // Handle knowledge sharing between agents
        console.log(`🧠 Knowledge shared by agent ${knowledge.agentId}: ${knowledge.type}`);
    }

    async handleConsensusRequest(request) {
        // Handle consensus requests
        console.log(`🗳️ Consensus requested by agent ${request.agentId} for: ${request.topic}`);
    }

    // Public API
    getAgent(agentId) {
        return this.agents.get(agentId);
    }

    getAllAgents() {
        return Array.from(this.agents.values());
    }

    getAgentsByRole(role) {
        return Array.from(this.agents.values()).filter(agent => agent.role === role);
    }

    getSystemStats() {
        return {
            totalAgents: this.agents.size,
            activeAgents: Array.from(this.agents.values()).filter(agent => agent.isActive()).length,
            roles: Array.from(this.agentRoles.keys()),
            totalTasks: this.performanceTracker.getTotalTasks(),
            averagePerformance: this.performanceTracker.getAveragePerformance()
        };
    }
}

/**
 * Individual Specialized Agent
 */
class SpecializedAgent extends EventEmitter {
    constructor(role, roleDefinition, system) {
        super();
        this.id = `agent_${role}_${Date.now()}`;
        this.role = role;
        this.definition = roleDefinition;
        this.system = system;
        this.knowledge = new Map();
        this.experience = [];
        this.currentTasks = [];
        this.activeLoops = [];
        this.performance = {
            tasksCompleted: 0,
            successRate: 1.0,
            averageQuality: 0.8,
            learningRate: 0.1
        };
        
        this.initializeKnowledge();
    }

    initializeKnowledge() {
        // Initialize with role-specific knowledge
        for (const capability of this.definition.capabilities) {
            this.knowledge.set(capability, {
                level: 0.7,
                experience: 0,
                lastUpdated: Date.now()
            });
        }
    }

    async assignTask(task, loopId) {
        this.currentTasks.push(task);
        if (!this.activeLoops.includes(loopId)) {
            this.activeLoops.push(loopId);
        }

        const assignment = {
            taskId: task.id,
            agentId: this.id,
            loopId,
            assignedAt: Date.now(),
            estimatedDuration: this.estimateTaskDuration(task),
            confidence: this.calculateTaskConfidence(task)
        };

        this.emit('taskAssigned', assignment);
        return assignment;
    }

    async vote(decision, loopId) {
        // Agent voting logic based on role and knowledge
        const vote = {
            agentId: this.id,
            role: this.role,
            decision: this.makeDecision(decision),
            confidence: this.calculateDecisionConfidence(decision),
            reasoning: this.generateReasoning(decision),
            timestamp: Date.now()
        };

        return vote;
    }

    calculateSuitability(task) {
        let score = 0;
        
        // Check capability match
        for (const capability of this.definition.capabilities) {
            if (task.requiredCapabilities?.includes(capability)) {
                score += 0.3;
            }
        }

        // Check specialization match
        for (const specialization of this.definition.specializations) {
            if (task.domain === specialization) {
                score += 0.4;
            }
        }

        // Consider current load
        const loadFactor = Math.max(0, 1 - (this.currentTasks.length / 5));
        score *= loadFactor;

        return Math.min(1, score);
    }

    getCurrentLoad() {
        return this.currentTasks.length / 5; // Normalize to 0-1
    }

    getSpecializationScore(task) {
        return this.definition.specializations.includes(task.domain) ? 1 : 0.5;
    }

    isActive() {
        return this.currentTasks.length > 0 || this.activeLoops.length > 0;
    }

    // Placeholder methods for agent behavior
    estimateTaskDuration(task) {
        return 5000 + Math.random() * 10000; // 5-15 seconds
    }

    calculateTaskConfidence(task) {
        return 0.7 + Math.random() * 0.3; // 70-100%
    }

    makeDecision(decision) {
        // Simple decision making based on role
        const options = decision.options || ['approve', 'reject', 'modify'];
        return options[Math.floor(Math.random() * options.length)];
    }

    calculateDecisionConfidence(decision) {
        return 0.6 + Math.random() * 0.4; // 60-100%
    }

    generateReasoning(decision) {
        return `${this.definition.name} analysis based on ${this.definition.capabilities.join(', ')}`;
    }

    async participateInPhase(session, phase) {
        return {
            agentId: this.id,
            role: this.role,
            phase,
            contribution: `${this.role} contribution for ${phase}`,
            recommendation: `Recommendation from ${this.role} perspective`,
            confidence: 0.8
        };
    }

    async receiveSharedKnowledge(knowledge, sourceLoopId) {
        // Process shared knowledge from other loops
        console.log(`🧠 Agent ${this.id} received knowledge from loop ${sourceLoopId}`);
    }

    async receiveCollectiveLearning(learningItems, loopId) {
        // Process collective learning from other agents
        console.log(`📚 Agent ${this.id} received collective learning from loop ${loopId}`);
    }
}

// Supporting classes
class ConsensusEngine {
    async processVotes(votes, decision) {
        const voteCounts = {};
        let totalConfidence = 0;

        for (const vote of votes) {
            voteCounts[vote.decision] = (voteCounts[vote.decision] || 0) + 1;
            totalConfidence += vote.confidence;
        }

        const winningDecision = Object.keys(voteCounts).reduce((a, b) => 
            voteCounts[a] > voteCounts[b] ? a : b
        );

        return {
            decision: winningDecision,
            votes: voteCounts,
            confidence: totalConfidence / votes.length,
            participantCount: votes.length,
            consensus: voteCounts[winningDecision] / votes.length > 0.6
        };
    }
}

class AgentLearningSystem {
    async updateAgentKnowledge(agent, outcomes, loopId) {
        // Simple learning update
        const update = {
            agentId: agent.id,
            newKnowledgeCount: Math.floor(Math.random() * 3),
            significantImprovement: Math.random() > 0.7,
            newKnowledge: `Learning from loop ${loopId}`,
            timestamp: Date.now()
        };

        return update;
    }

    async learnFromConsensus(consensusResult, participants, decision) {
        // Learn from consensus outcomes
        console.log(`📊 Learning from consensus: ${consensusResult.decision} (${participants.length} participants)`);
    }
}

class CrossLoopCommunicationHub {
    constructor() {
        this.channels = new Map();
        this.knowledgeBase = new Map();
    }

    async createChannel(sourceLoopId, targetLoopId) {
        const channel = {
            id: `channel_${sourceLoopId}_${targetLoopId}_${Date.now()}`,
            source: sourceLoopId,
            target: targetLoopId,
            createdAt: Date.now(),
            active: true
        };

        this.channels.set(channel.id, channel);
        return channel;
    }

    async shareKnowledge(sourceLoopId, targetLoopId, knowledgeTypes) {
        return {
            items: [
                { type: 'pattern', content: 'Shared pattern from source loop' },
                { type: 'optimization', content: 'Performance optimization technique' }
            ]
        };
    }
}

class AgentPerformanceTracker {
    constructor() {
        this.assignments = [];
        this.performance = new Map();
    }

    trackAssignment(agentId, task, assignment) {
        this.assignments.push({ agentId, task, assignment, timestamp: Date.now() });
    }

    getAgentPerformance(agentId) {
        return 0.8; // Placeholder
    }

    getTotalTasks() {
        return this.assignments.length;
    }

    getAveragePerformance() {
        return 0.8; // Placeholder
    }
}