mcp-infinite-loop-server/src/multiAgentCollaborator.js

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import { EventEmitter } from 'events';

/**
 * Multi-Agent Collaboration for AI-to-AI Communication
 * Manages specialist AI agents and consensus mechanisms
 */
export class MultiAgentCollaborator extends EventEmitter {
  constructor() {
    super();
    this.specialists = this.initializeSpecialists();
    this.collaborationSessions = new Map(); // loopId -> session
    this.consensusThreshold = 0.7; // 70% agreement required
    this.agentPerformance = new Map(); // agentId -> performance metrics
  }

  /**
   * Initialize specialist agents
   * @returns {Map} - Specialist agents
   */
  initializeSpecialists() {
    const specialists = new Map();
    
    specialists.set('frontend', {
      id: 'frontend',
      name: 'Frontend Specialist',
      expertise: ['ui', 'ux', 'react', 'vue', 'angular', 'css', 'html', 'javascript'],
      strengths: ['component design', 'user experience', 'responsive design', 'accessibility'],
      confidence: 0.9,
      availability: true,
      workload: 0
    });
    
    specialists.set('backend', {
      id: 'backend',
      name: 'Backend Specialist',
      expertise: ['api', 'database', 'server', 'nodejs', 'python', 'java', 'microservices'],
      strengths: ['api design', 'database optimization', 'scalability', 'security'],
      confidence: 0.85,
      availability: true,
      workload: 0
    });
    
    specialists.set('devops', {
      id: 'devops',
      name: 'DevOps Specialist',
      expertise: ['deployment', 'ci/cd', 'docker', 'kubernetes', 'monitoring', 'performance'],
      strengths: ['deployment automation', 'performance optimization', 'monitoring', 'scalability'],
      confidence: 0.8,
      availability: true,
      workload: 0
    });
    
    specialists.set('testing', {
      id: 'testing',
      name: 'Testing Specialist',
      expertise: ['testing', 'qa', 'automation', 'jest', 'cypress', 'selenium', 'coverage'],
      strengths: ['test strategy', 'automation', 'quality assurance', 'coverage analysis'],
      confidence: 0.88,
      availability: true,
      workload: 0
    });
    
    specialists.set('security', {
      id: 'security',
      name: 'Security Specialist',
      expertise: ['security', 'authentication', 'authorization', 'encryption', 'vulnerabilities'],
      strengths: ['security analysis', 'vulnerability assessment', 'secure coding', 'compliance'],
      confidence: 0.92,
      availability: true,
      workload: 0
    });
    
    specialists.set('performance', {
      id: 'performance',
      name: 'Performance Specialist',
      expertise: ['optimization', 'caching', 'bundling', 'lazy loading', 'memory management'],
      strengths: ['performance analysis', 'optimization strategies', 'profiling', 'monitoring'],
      confidence: 0.87,
      availability: true,
      workload: 0
    });
    
    return specialists;
  }

  /**
   * Route to specialist agent based on topic and codebase type
   * @param {string} topic - Topic to analyze
   * @param {string} codebaseType - Type of codebase
   * @returns {Array} - Relevant specialist agents
   */
  routeToSpecialistAgent(topic, codebaseType) {
    console.error(`[MULTI-AGENT] Routing topic "${topic}" for codebase type "${codebaseType}"`);
    
    const topicLower = topic.toLowerCase();
    const codebaseLower = codebaseType.toLowerCase();
    const relevantAgents = [];
    
    // Analyze topic keywords
    for (const [agentId, agent] of this.specialists.entries()) {
      let relevanceScore = 0;
      
      // Check expertise match
      agent.expertise.forEach(expertise => {
        if (topicLower.includes(expertise) || codebaseLower.includes(expertise)) {
          relevanceScore += 0.3;
        }
      });
      
      // Check strengths match
      agent.strengths.forEach(strength => {
        if (topicLower.includes(strength.split(' ')[0])) {
          relevanceScore += 0.2;
        }
      });
      
      // Special routing logic
      if (topicLower.includes('ui') || topicLower.includes('ux') || topicLower.includes('design')) {
        if (agentId === 'frontend') relevanceScore += 0.5;
      }
      
      if (topicLower.includes('api') || topicLower.includes('backend') || topicLower.includes('database')) {
        if (agentId === 'backend') relevanceScore += 0.5;
      }
      
      if (topicLower.includes('test') || topicLower.includes('coverage') || topicLower.includes('qa')) {
        if (agentId === 'testing') relevanceScore += 0.5;
      }
      
      if (topicLower.includes('performance') || topicLower.includes('optimization')) {
        if (agentId === 'performance') relevanceScore += 0.5;
      }
      
      if (topicLower.includes('security') || topicLower.includes('auth')) {
        if (agentId === 'security') relevanceScore += 0.5;
      }
      
      if (topicLower.includes('deploy') || topicLower.includes('ci') || topicLower.includes('docker')) {
        if (agentId === 'devops') relevanceScore += 0.5;
      }
      
      // Consider agent availability and workload
      if (agent.availability && agent.workload < 3) {
        relevanceScore *= agent.confidence;
        
        if (relevanceScore > 0.3) {
          relevantAgents.push({
            ...agent,
            relevanceScore,
            estimatedEffort: this.estimateEffort(topic, agent)
          });
        }
      }
    }
    
    // Sort by relevance score
    relevantAgents.sort((a, b) => b.relevanceScore - a.relevanceScore);
    
    console.error(`[MULTI-AGENT] Found ${relevantAgents.length} relevant agents`);
    
    return relevantAgents.slice(0, 3); // Return top 3 agents
  }

  /**
   * Estimate effort for agent
   * @param {string} topic - Topic
   * @param {Object} agent - Agent
   * @returns {number} - Estimated effort (1-5)
   */
  estimateEffort(topic, agent) {
    const topicComplexity = this.analyzeTopicComplexity(topic);
    const agentExpertise = agent.confidence;
    
    // Higher expertise = lower effort
    const baseEffort = topicComplexity * (2 - agentExpertise);
    
    return Math.max(1, Math.min(5, Math.round(baseEffort)));
  }

  /**
   * Analyze topic complexity
   * @param {string} topic - Topic to analyze
   * @returns {number} - Complexity score (1-5)
   */
  analyzeTopicComplexity(topic) {
    const complexKeywords = ['architecture', 'microservice', 'distributed', 'scalable', 'enterprise'];
    const mediumKeywords = ['integration', 'optimization', 'refactor', 'migration'];
    const simpleKeywords = ['fix', 'update', 'style', 'format'];
    
    const topicLower = topic.toLowerCase();
    
    if (complexKeywords.some(keyword => topicLower.includes(keyword))) return 5;
    if (mediumKeywords.some(keyword => topicLower.includes(keyword))) return 3;
    if (simpleKeywords.some(keyword => topicLower.includes(keyword))) return 1;
    
    return 2; // Default medium-low complexity
  }

  /**
   * Get agent consensus on improvement
   * @param {string} loopId - Loop ID
   * @param {Object} improvement - Improvement to review
   * @param {Array} specialists - Specialist agents
   * @returns {Promise<Object>} - Consensus result
   */
  async getAgentConsensus(loopId, improvement, specialists) {
    console.error(`[MULTI-AGENT] Getting consensus from ${specialists.length} agents for loop ${loopId}`);
    
    const sessionId = `consensus_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
    const session = {
      id: sessionId,
      loopId,
      improvement,
      specialists,
      reviews: [],
      consensus: null,
      startTime: Date.now()
    };
    
    this.collaborationSessions.set(sessionId, session);
    
    try {
      // Get reviews from each specialist
      const reviewPromises = specialists.map(specialist => 
        this.getSpecialistReview(specialist, improvement, sessionId)
      );
      
      const reviews = await Promise.all(reviewPromises);
      session.reviews = reviews;
      
      // Calculate consensus
      const consensus = this.calculateConsensus(reviews);
      session.consensus = consensus;
      session.endTime = Date.now();
      
      // Update agent performance
      this.updateAgentPerformance(specialists, reviews, consensus);
      
      console.error(`[MULTI-AGENT] Consensus reached: ${consensus.agreement}% agreement, ${consensus.recommendation}`);
      
      this.emit('consensusReached', { sessionId, consensus, reviews });
      
      return {
        sessionId,
        consensus,
        reviews,
        processingTime: session.endTime - session.startTime
      };
      
    } catch (error) {
      console.error(`[MULTI-AGENT] Consensus error: ${error.message}`);
      session.error = error.message;
      session.endTime = Date.now();
      
      return {
        sessionId,
        error: error.message,
        consensus: { agreement: 0, recommendation: 'error' }
      };
    }
  }

  /**
   * Get specialist review
   * @param {Object} specialist - Specialist agent
   * @param {Object} improvement - Improvement to review
   * @param {string} sessionId - Session ID
   * @returns {Promise<Object>} - Specialist review
   */
  async getSpecialistReview(specialist, improvement, sessionId) {
    console.error(`[MULTI-AGENT] Getting review from ${specialist.name}`);
    
    // Simulate specialist analysis time
    const analysisTime = 200 + Math.random() * 300;
    await new Promise(resolve => setTimeout(resolve, analysisTime));
    
    // Generate specialist review based on expertise
    const review = {
      agentId: specialist.id,
      agentName: specialist.name,
      sessionId,
      timestamp: new Date(),
      analysisTime,
      score: this.generateSpecialistScore(specialist, improvement),
      confidence: specialist.confidence * (0.8 + Math.random() * 0.2),
      feedback: this.generateSpecialistFeedback(specialist, improvement),
      recommendations: this.generateSpecialistRecommendations(specialist, improvement),
      concerns: this.generateSpecialistConcerns(specialist, improvement),
      approval: null // Will be set based on score
    };
    
    // Set approval based on score
    review.approval = review.score >= 0.7 ? 'approve' : 
                     review.score >= 0.5 ? 'conditional' : 'reject';
    
    // Update agent workload
    specialist.workload += 1;
    
    return review;
  }

  /**
   * Generate specialist score
   * @param {Object} specialist - Specialist agent
   * @param {Object} improvement - Improvement
   * @returns {number} - Score (0-1)
   */
  generateSpecialistScore(specialist, improvement) {
    let score = 0.5; // Base score
    
    // Check if improvement aligns with specialist expertise
    const improvementText = (improvement.description || '').toLowerCase();
    
    specialist.expertise.forEach(expertise => {
      if (improvementText.includes(expertise)) {
        score += 0.1;
      }
    });
    
    specialist.strengths.forEach(strength => {
      if (improvementText.includes(strength.split(' ')[0])) {
        score += 0.15;
      }
    });
    
    // Add some randomness for realistic variation
    score += (Math.random() - 0.5) * 0.2;
    
    return Math.max(0, Math.min(1, score));
  }

  /**
   * Generate specialist feedback
   * @param {Object} specialist - Specialist agent
   * @param {Object} improvement - Improvement
   * @returns {string} - Feedback
   */
  generateSpecialistFeedback(specialist, improvement) {
    const feedbackTemplates = {
      frontend: [
        'The UI/UX improvements look promising and should enhance user experience.',
        'Consider accessibility implications and responsive design principles.',
        'The component structure could benefit from better separation of concerns.'
      ],
      backend: [
        'The API design follows good practices and should scale well.',
        'Database optimization strategies are sound and performance-focused.',
        'Consider implementing proper error handling and validation.'
      ],
      testing: [
        'Test coverage should be expanded to include edge cases.',
        'The testing strategy aligns with best practices for quality assurance.',
        'Consider adding integration tests for better coverage.'
      ],
      security: [
        'Security considerations are adequate but could be strengthened.',
        'Authentication and authorization mechanisms need review.',
        'Consider implementing additional security headers and validation.'
      ],
      performance: [
        'Performance optimizations are well-targeted and should yield good results.',
        'Caching strategies could be improved for better efficiency.',
        'Consider implementing lazy loading and code splitting.'
      ],
      devops: [
        'Deployment strategy is solid and follows DevOps best practices.',
        'CI/CD pipeline could benefit from additional automation.',
        'Monitoring and alerting mechanisms should be enhanced.'
      ]
    };
    
    const templates = feedbackTemplates[specialist.id] || ['The improvement looks reasonable and well-structured.'];
    return templates[Math.floor(Math.random() * templates.length)];
  }

  /**
   * Generate specialist recommendations
   * @param {Object} specialist - Specialist agent
   * @param {Object} improvement - Improvement
   * @returns {Array} - Recommendations
   */
  generateSpecialistRecommendations(specialist, improvement) {
    const recommendationTemplates = {
      frontend: [
        'Implement responsive design patterns',
        'Add accessibility features (ARIA labels, keyboard navigation)',
        'Optimize component rendering performance',
        'Consider using CSS-in-JS for better maintainability'
      ],
      backend: [
        'Implement proper error handling and logging',
        'Add input validation and sanitization',
        'Consider implementing caching mechanisms',
        'Optimize database queries and indexing'
      ],
      testing: [
        'Increase test coverage to at least 80%',
        'Add integration and end-to-end tests',
        'Implement automated testing in CI/CD pipeline',
        'Consider property-based testing for edge cases'
      ],
      security: [
        'Implement proper authentication and authorization',
        'Add security headers and CSRF protection',
        'Conduct security audit and vulnerability assessment',
        'Implement secure coding practices'
      ],
      performance: [
        'Implement code splitting and lazy loading',
        'Optimize bundle size and loading times',
        'Add performance monitoring and metrics',
        'Consider implementing service workers for caching'
      ],
      devops: [
        'Automate deployment process with CI/CD',
        'Implement monitoring and alerting',
        'Add containerization with Docker',
        'Consider implementing blue-green deployment'
      ]
    };
    
    const templates = recommendationTemplates[specialist.id] || ['Follow best practices for the domain'];
    return templates.slice(0, 2 + Math.floor(Math.random() * 2)); // Return 2-3 recommendations
  }

  /**
   * Generate specialist concerns
   * @param {Object} specialist - Specialist agent
   * @param {Object} improvement - Improvement
   * @returns {Array} - Concerns
   */
  generateSpecialistConcerns(specialist, improvement) {
    const concerns = [];
    
    // Generate concerns based on specialist expertise
    if (specialist.id === 'security' && Math.random() > 0.7) {
      concerns.push('Potential security vulnerabilities need to be addressed');
    }
    
    if (specialist.id === 'performance' && Math.random() > 0.6) {
      concerns.push('Performance impact should be measured and monitored');
    }
    
    if (specialist.id === 'testing' && Math.random() > 0.5) {
      concerns.push('Test coverage may be insufficient for the changes');
    }
    
    return concerns;
  }

  /**
   * Calculate consensus from reviews
   * @param {Array} reviews - Specialist reviews
   * @returns {Object} - Consensus result
   */
  calculateConsensus(reviews) {
    if (reviews.length === 0) {
      return { agreement: 0, recommendation: 'no_reviews', confidence: 0 };
    }
    
    const approvals = reviews.filter(r => r.approval === 'approve').length;
    const conditionals = reviews.filter(r => r.approval === 'conditional').length;
    const rejections = reviews.filter(r => r.approval === 'reject').length;
    
    const totalReviews = reviews.length;
    const approvalRate = approvals / totalReviews;
    const conditionalRate = conditionals / totalReviews;
    
    // Calculate weighted agreement
    const weightedAgreement = (approvals * 1.0 + conditionals * 0.5) / totalReviews;
    
    // Calculate average confidence
    const avgConfidence = reviews.reduce((sum, r) => sum + r.confidence, 0) / totalReviews;
    
    // Calculate average score
    const avgScore = reviews.reduce((sum, r) => sum + r.score, 0) / totalReviews;
    
    let recommendation;
    if (weightedAgreement >= this.consensusThreshold) {
      recommendation = 'proceed';
    } else if (weightedAgreement >= 0.5) {
      recommendation = 'proceed_with_caution';
    } else {
      recommendation = 'revise';
    }
    
    return {
      agreement: Math.round(weightedAgreement * 100),
      recommendation,
      confidence: avgConfidence,
      averageScore: avgScore,
      breakdown: {
        approvals,
        conditionals,
        rejections,
        totalReviews
      },
      topConcerns: this.extractTopConcerns(reviews),
      topRecommendations: this.extractTopRecommendations(reviews)
    };
  }

  /**
   * Extract top concerns from reviews
   * @param {Array} reviews - Specialist reviews
   * @returns {Array} - Top concerns
   */
  extractTopConcerns(reviews) {
    const allConcerns = reviews.flatMap(r => r.concerns || []);
    const concernCounts = {};
    
    allConcerns.forEach(concern => {
      concernCounts[concern] = (concernCounts[concern] || 0) + 1;
    });
    
    return Object.entries(concernCounts)
      .sort((a, b) => b[1] - a[1])
      .slice(0, 3)
      .map(([concern, count]) => ({ concern, mentions: count }));
  }

  /**
   * Extract top recommendations from reviews
   * @param {Array} reviews - Specialist reviews
   * @returns {Array} - Top recommendations
   */
  extractTopRecommendations(reviews) {
    const allRecommendations = reviews.flatMap(r => r.recommendations || []);
    const recCounts = {};
    
    allRecommendations.forEach(rec => {
      recCounts[rec] = (recCounts[rec] || 0) + 1;
    });
    
    return Object.entries(recCounts)
      .sort((a, b) => b[1] - a[1])
      .slice(0, 5)
      .map(([recommendation, count]) => ({ recommendation, mentions: count }));
  }

  /**
   * Update agent performance metrics
   * @param {Array} specialists - Specialist agents
   * @param {Array} reviews - Reviews
   * @param {Object} consensus - Consensus result
   */
  updateAgentPerformance(specialists, reviews, consensus) {
    reviews.forEach(review => {
      const agentId = review.agentId;
      
      if (!this.agentPerformance.has(agentId)) {
        this.agentPerformance.set(agentId, {
          totalReviews: 0,
          averageScore: 0,
          averageConfidence: 0,
          consensusAlignment: 0,
          responseTime: 0
        });
      }
      
      const performance = this.agentPerformance.get(agentId);
      
      // Update metrics
      performance.totalReviews++;
      performance.averageScore = (performance.averageScore * (performance.totalReviews - 1) + review.score) / performance.totalReviews;
      performance.averageConfidence = (performance.averageConfidence * (performance.totalReviews - 1) + review.confidence) / performance.totalReviews;
      performance.responseTime = (performance.responseTime * (performance.totalReviews - 1) + review.analysisTime) / performance.totalReviews;
      
      // Calculate consensus alignment
      const alignsWithConsensus = (review.approval === 'approve' && consensus.recommendation === 'proceed') ||
                                 (review.approval === 'conditional' && consensus.recommendation === 'proceed_with_caution') ||
                                 (review.approval === 'reject' && consensus.recommendation === 'revise');
      
      performance.consensusAlignment = (performance.consensusAlignment * (performance.totalReviews - 1) + (alignsWithConsensus ? 1 : 0)) / performance.totalReviews;
      
      // Update agent workload
      const specialist = specialists.find(s => s.id === agentId);
      if (specialist) {
        specialist.workload = Math.max(0, specialist.workload - 1);
      }
    });
  }

  /**
   * Get collaboration report
   * @param {string} loopId - Loop ID (optional)
   * @returns {Object} - Collaboration report
   */
  getCollaborationReport(loopId = null) {
    const sessions = Array.from(this.collaborationSessions.values());
    const relevantSessions = loopId ? sessions.filter(s => s.loopId === loopId) : sessions;
    
    const report = {
      timestamp: new Date(),
      totalSessions: relevantSessions.length,
      agentPerformance: Object.fromEntries(this.agentPerformance),
      consensusStats: this.calculateConsensusStats(relevantSessions),
      agentUtilization: this.calculateAgentUtilization(),
      recommendations: this.generateCollaborationRecommendations()
    };
    
    return report;
  }

  /**
   * Calculate consensus statistics
   * @param {Array} sessions - Collaboration sessions
   * @returns {Object} - Consensus statistics
   */
  calculateConsensusStats(sessions) {
    if (sessions.length === 0) return { averageAgreement: 0, consensusRate: 0 };
    
    const completedSessions = sessions.filter(s => s.consensus);
    const totalAgreement = completedSessions.reduce((sum, s) => sum + s.consensus.agreement, 0);
    const consensusReached = completedSessions.filter(s => s.consensus.agreement >= this.consensusThreshold * 100).length;
    
    return {
      averageAgreement: completedSessions.length > 0 ? totalAgreement / completedSessions.length : 0,
      consensusRate: completedSessions.length > 0 ? consensusReached / completedSessions.length : 0,
      totalSessions: sessions.length,
      completedSessions: completedSessions.length
    };
  }

  /**
   * Calculate agent utilization
   * @returns {Object} - Agent utilization
   */
  calculateAgentUtilization() {
    const utilization = {};
    
    for (const [agentId, agent] of this.specialists.entries()) {
      const performance = this.agentPerformance.get(agentId);
      
      utilization[agentId] = {
        name: agent.name,
        currentWorkload: agent.workload,
        totalReviews: performance?.totalReviews || 0,
        availability: agent.availability,
        efficiency: performance?.averageScore || 0
      };
    }
    
    return utilization;
  }

  /**
   * Generate collaboration recommendations
   * @returns {Array} - Recommendations
   */
  generateCollaborationRecommendations() {
    const recommendations = [];
    
    // Check agent performance
    for (const [agentId, performance] of this.agentPerformance.entries()) {
      if (performance.averageScore < 0.6) {
        recommendations.push({
          type: 'agent_performance',
          agentId,
          priority: 'medium',
          description: `${agentId} agent performance is below average`,
          action: 'Review and improve agent expertise or replace'
        });
      }
      
      if (performance.consensusAlignment < 0.5) {
        recommendations.push({
          type: 'consensus_alignment',
          agentId,
          priority: 'low',
          description: `${agentId} agent often disagrees with consensus`,
          action: 'Review agent decision criteria'
        });
      }
    }
    
    // Check workload distribution
    const workloads = Array.from(this.specialists.values()).map(a => a.workload);
    const maxWorkload = Math.max(...workloads);
    const minWorkload = Math.min(...workloads);
    
    if (maxWorkload - minWorkload > 2) {
      recommendations.push({
        type: 'workload_balance',
        priority: 'medium',
        description: 'Uneven workload distribution among agents',
        action: 'Implement better load balancing'
      });
    }
    
    return recommendations;
  }
}