zai-mcp-server/src/multiAgentCollaboration.js

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/**
 * Multi-Agent Collaboration System for AI-to-AI Enhancement
 * Incorporates specialist expertise from multiple AI agents
 */

class MultiAgentCollaboration {
  constructor() {
    this.specialists = {
      frontend: new FrontendSpecialist(),
      backend: new BackendSpecialist(),
      testing: new TestingSpecialist(),
      security: new SecuritySpecialist(),
      performance: new PerformanceSpecialist(),
      devops: new DevOpsSpecialist()
    };

    this.consensusThreshold = 0.7; // 70% agreement required
    this.log('👥 Multi-Agent Collaboration System initialized');
  }

  /**
     * Get consensus-driven recommendations from all specialists
     */
  async getConsensusRecommendations(topic, context) {
    this.log(`🧠 Gathering specialist recommendations for: ${topic}`);

    const recommendations = {};
    const scores = {};

    // Gather recommendations from each specialist
    for (const [role, specialist] of Object.entries(this.specialists)) {
      try {
        const recommendation = await specialist.analyze(topic, context);
        recommendations[role] = recommendation;
        scores[role] = recommendation.confidence || 0.8;

        this.log(`✅ ${role} specialist: ${recommendation.summary}`);
      } catch (error) {
        this.log(`❌ ${role} specialist failed: ${error.message}`);
        scores[role] = 0;
      }
    }

    // Calculate consensus
    const consensus = this.calculateConsensus(recommendations, scores);

    return {
      recommendations,
      consensus,
      overallConfidence: this.calculateOverallConfidence(scores)
    };
  }

  /**
     * Calculate consensus from specialist recommendations
     */
  calculateConsensus(recommendations, scores) {
    const consensus = {
      priority: 'high',
      actions: [],
      risks: [],
      benefits: []
    };

    // Aggregate common themes
    const actionCounts = {};
    const riskCounts = {};
    const benefitCounts = {};

    for (const [role, rec] of Object.entries(recommendations)) {
      const weight = scores[role];

      // Weight actions by specialist confidence
      rec.actions?.forEach(action => {
        actionCounts[action] = (actionCounts[action] || 0) + weight;
      });

      rec.risks?.forEach(risk => {
        riskCounts[risk] = (riskCounts[risk] || 0) + weight;
      });

      rec.benefits?.forEach(benefit => {
        benefitCounts[benefit] = (benefitCounts[benefit] || 0) + weight;
      });
    }

    // Select items above consensus threshold
    const totalWeight = Object.values(scores).reduce((sum, score) => sum + score, 0);
    const threshold = totalWeight * this.consensusThreshold;

    consensus.actions = Object.entries(actionCounts)
      .filter(([_, count]) => count >= threshold)
      .map(([action, _]) => action);

    consensus.risks = Object.entries(riskCounts)
      .filter(([_, count]) => count >= threshold)
      .map(([risk, _]) => risk);

    consensus.benefits = Object.entries(benefitCounts)
      .filter(([_, count]) => count >= threshold)
      .map(([benefit, _]) => benefit);

    return consensus;
  }

  /**
     * Calculate overall confidence from specialist scores
     */
  calculateOverallConfidence(scores) {
    const validScores = Object.values(scores).filter(score => score > 0);
    if (validScores.length === 0) {return 0;}

    return validScores.reduce((sum, score) => sum + score, 0) / validScores.length;
  }

  log(message) {
    console.log(`[MULTI-AGENT] ${message}`);
  }
}

/**
 * Frontend Specialist Agent
 */
class FrontendSpecialist {
  async analyze(topic, context) {
    return {
      summary: 'Enhanced UI/UX for AI-to-AI interface',
      confidence: 0.9,
      actions: [
        'Implement real-time visual feedback for AI-to-AI communication',
        'Add progress indicators for loop iterations',
        'Create interactive dashboard for monitoring AI collaboration'
      ],
      risks: ['UI complexity may impact performance'],
      benefits: ['Better user experience', 'Visual monitoring capabilities']
    };
  }
}

/**
 * Backend Specialist Agent
 */
class BackendSpecialist {
  async analyze(topic, context) {
    return {
      summary: 'Optimized backend architecture for AI-to-AI processing',
      confidence: 0.85,
      actions: [
        'Implement async processing for AI-to-AI communications',
        'Add caching layer for frequent AI interactions',
        'Optimize database queries for context management'
      ],
      risks: ['Increased system complexity'],
      benefits: ['Better scalability', 'Improved response times']
    };
  }
}

/**
 * Testing Specialist Agent
 */
class TestingSpecialist {
  async analyze(topic, context) {
    return {
      summary: 'Comprehensive testing strategy for AI-to-AI functionality',
      confidence: 0.8,
      actions: [
        'Create automated tests for AI-to-AI loop scenarios',
        'Implement integration tests for bridge communication',
        'Add performance tests for long-running loops'
      ],
      risks: ['Test complexity for AI behavior'],
      benefits: ['Reliable AI-to-AI communication', 'Regression prevention']
    };
  }
}

/**
 * Security Specialist Agent
 */
class SecuritySpecialist {
  async analyze(topic, context) {
    return {
      summary: 'Security enhancements for AI-to-AI communication',
      confidence: 0.75,
      actions: [
        'Implement secure communication channels for AI agents',
        'Add authentication for AI-to-AI interactions',
        'Validate AI-generated content for security risks'
      ],
      risks: ['Security overhead may slow communication'],
      benefits: ['Secure AI collaboration', 'Protected against malicious AI inputs']
    };
  }
}

/**
 * Performance Specialist Agent
 */
class PerformanceSpecialist {
  async analyze(topic, context) {
    return {
      summary: 'Performance optimization for AI-to-AI systems',
      confidence: 0.9,
      actions: [
        'Optimize memory usage in long-running AI loops',
        'Implement efficient context compression algorithms',
        'Add performance monitoring and alerting'
      ],
      risks: ['Optimization complexity'],
      benefits: ['Faster AI responses', 'Better resource utilization']
    };
  }
}

/**
 * DevOps Specialist Agent
 */
class DevOpsSpecialist {
  async analyze(topic, context) {
    return {
      summary: 'DevOps improvements for AI-to-AI deployment',
      confidence: 0.8,
      actions: [
        'Implement CI/CD pipeline for AI-to-AI components',
        'Add monitoring and logging for AI interactions',
        'Create deployment automation for bridge extensions'
      ],
      risks: ['Deployment complexity'],
      benefits: ['Reliable deployments', 'Better monitoring']
    };
  }
}

module.exports = { MultiAgentCollaboration };