codecrucible-synth/src/core/agents/agent-ecosystem.ts

Production-Ready AI Development Platform with Multi-Voice Synthesis, Smithery MCP Integration, Enterprise Security, and Zero-Timeout Reliability

/**
 * Agent Ecosystem for CodeCrucible Synth
 * Production-ready specialized agents based on the multi-voice synthesis architecture
 * Each agent represents a different perspective and expertise domain
 */

import { EventEmitter } from 'events';
import { Logger } from '../logger.js';
// import { UnifiedModelClient } from '../../refactor/unified-model-client.js';
import { WorkflowOrchestrator } from '../workflow/workflow-orchestrator.js';
import { AdvancedToolOrchestrator } from '../tools/advanced-tool-orchestrator.js';
import { VectorRAGSystem } from '../rag/vector-rag-system.js';
import { IntelligentModelRouter } from '../routing/intelligent-model-router.js';

// Core Agent Interfaces
export interface Agent {
  id: string;
  name: string;
  role: AgentRole;
  personality: AgentPersonality;
  capabilities: AgentCapability[];
  expertise: ExpertiseDomain[];
  status: AgentStatus;
  configuration: AgentConfiguration;

  // Core methods
  initialize(): Promise<void>;
  process(request: AgentRequest): Promise<AgentResponse>;
  collaborate(agents: Agent[], task: CollaborativeTask): Promise<CollaborativeResponse>;
  learn(feedback: AgentFeedback): Promise<void>;
  shutdown(): Promise<void>;
}

export interface AgentRole {
  type:
    | 'explorer'
    | 'analyzer'
    | 'implementor'
    | 'maintainer'
    | 'security'
    | 'optimizer'
    | 'tester'
    | 'architect'
    | 'reviewer';
  description: string;
  responsibilities: string[];
  authority: 'advisory' | 'decision-making' | 'implementation' | 'review';
  scope: 'local' | 'project' | 'system' | 'global';
}

export interface AgentPersonality {
  approach:
    | 'methodical'
    | 'creative'
    | 'pragmatic'
    | 'perfectionist'
    | 'innovative'
    | 'conservative'
    | 'aggressive';
  communication: 'detailed' | 'concise' | 'technical' | 'narrative' | 'analytical';
  riskTolerance: 'low' | 'medium' | 'high';
  decisionStyle: 'quick' | 'deliberate' | 'collaborative' | 'independent';
  learningStyle: 'experiential' | 'theoretical' | 'collaborative' | 'observational';
}

export interface AgentCapability {
  name: string;
  level: 'novice' | 'intermediate' | 'expert' | 'master';
  description: string;
  tools: string[];
  prerequisites?: string[];
  learnable: boolean;
}

export interface ExpertiseDomain {
  area: string;
  level: number; // 0-100
  technologies: string[];
  frameworks: string[];
  patterns: string[];
  experience: ExperienceMetric[];
}

export interface ExperienceMetric {
  task: string;
  successRate: number;
  avgQuality: number;
  timeSpent: number;
  complexity: number;
  lastPerformed: Date;
}

export interface AgentStatus {
  state: 'idle' | 'busy' | 'learning' | 'collaborating' | 'offline' | 'error';
  currentTask?: string;
  workload: number; // 0-100
  availability: boolean;
  lastActivity: Date;
  health: AgentHealth;
}

export interface AgentHealth {
  performance: number; // 0-100
  errorRate: number;
  responseTime: number;
  memoryUsage: number;
  issueCount: number;
  lastHealthCheck: Date;
}

export interface AgentConfiguration {
  modelPreferences: ModelPreference[];
  behaviorSettings: BehaviorSettings;
  collaborationSettings: CollaborationSettings;
  learningSettings: LearningSettings;
  resourceLimits: ResourceLimits;
}

export interface ModelPreference {
  providerId: string;
  modelId: string;
  priority: number;
  useCase: string[];
  configuration: Record<string, any>;
}

export interface BehaviorSettings {
  verbosity: 'minimal' | 'normal' | 'detailed' | 'verbose';
  responseStyle: 'direct' | 'explanatory' | 'tutorial' | 'conversational';
  errorHandling: 'strict' | 'permissive' | 'adaptive';
  optimizationLevel: 'speed' | 'quality' | 'balanced';
}

export interface CollaborationSettings {
  preferredTeamSize: number;
  leadershipStyle: 'democratic' | 'authoritative' | 'laissez-faire' | 'situational';
  communicationFrequency: 'minimal' | 'regular' | 'frequent' | 'continuous';
  conflictResolution: 'consensus' | 'voting' | 'authority' | 'escalation';
}

export interface LearningSettings {
  adaptationRate: number; // 0-1
  feedbackSensitivity: number; // 0-1
  explorationRate: number; // 0-1
  memoryRetention: number; // days
  learningMethods: string[];
}

export interface ResourceLimits {
  maxMemoryUsage: number; // MB
  maxProcessingTime: number; // seconds
  maxConcurrentTasks: number;
  maxToolsPerTask: number;
  costBudget: number;
}

export interface AgentRequest {
  id: string;
  type:
    | 'analysis'
    | 'implementation'
    | 'review'
    | 'optimization'
    | 'testing'
    | 'documentation'
    | 'planning';
  content: string;
  context?: AgentContext;
  constraints?: AgentConstraints;
  priority: 'low' | 'medium' | 'high' | 'critical';
  deadline?: Date;
  requester: string;
}

export interface AgentContext {
  project?: ProjectContext;
  codebase?: CodebaseContext;
  session?: SessionContext;
  previous?: PreviousInteraction[];
  environment?: EnvironmentContext;
}

export interface ProjectContext {
  name: string;
  type: string;
  technologies: string[];
  architecture: string;
  conventions: Record<string, any>;
  constraints: string[];
}

export interface CodebaseContext {
  languages: string[];
  frameworks: string[];
  patterns: string[];
  size: number;
  complexity: number;
  quality: number;
  coverage: number;
}

export interface SessionContext {
  sessionId: string;
  duration: number;
  interactions: number;
  mood: 'positive' | 'neutral' | 'frustrated' | 'confused';
  goals: string[];
}

export interface PreviousInteraction {
  timestamp: Date;
  request: string;
  response: string;
  outcome: 'success' | 'partial' | 'failure';
  feedback?: string;
}

export interface EnvironmentContext {
  os: string;
  tools: string[];
  resources: ResourceAvailability;
  constraints: string[];
}

export interface ResourceAvailability {
  cpu: number;
  memory: number;
  disk: number;
  network: number;
}

export interface AgentConstraints {
  timeLimit?: number;
  memoryLimit?: number;
  costLimit?: number;
  qualityThreshold?: number;
  approvedTools?: string[];
  forbiddenActions?: string[];
}

export interface AgentResponse {
  id: string;
  requestId: string;
  agentId: string;
  content: string;
  confidence: number; // 0-1
  reasoning: string;
  suggestions?: string[];
  alternatives?: string[];
  warnings?: string[];
  metadata: ResponseMetadata;
  actions?: AgentAction[];
  collaboration?: CollaborationRequest;
}

export interface ResponseMetadata {
  processingTime: number;
  tokensUsed: number;
  toolsUsed: string[];
  modelsUsed: string[];
  qualityScore: number;
  complexity: number;
  resources: ResourceUsage;
}

export interface ResourceUsage {
  cpu: number;
  memory: number;
  cost: number;
  apiCalls: number;
}

export interface AgentAction {
  type:
    | 'file_create'
    | 'file_modify'
    | 'file_delete'
    | 'command_execute'
    | 'analysis_run'
    | 'test_run';
  target: string;
  parameters: Record<string, any>;
  confirmation?: boolean;
  reversible: boolean;
}

export interface CollaborationRequest {
  type: 'review' | 'assistance' | 'validation' | 'brainstorm' | 'implementation';
  targetAgents: string[];
  content: string;
  urgency: 'low' | 'medium' | 'high';
}

export interface CollaborativeTask {
  id: string;
  title: string;
  description: string;
  type: 'analysis' | 'implementation' | 'review' | 'architecture' | 'optimization';
  complexity: number;
  participants: string[];
  coordinator: string;
  phases: TaskPhase[];
  dependencies: string[];
  deadline?: Date;
}

export interface TaskPhase {
  id: string;
  name: string;
  description: string;
  assignedAgent: string;
  dependencies: string[];
  estimatedDuration: number;
  status: 'pending' | 'in_progress' | 'completed' | 'blocked';
  deliverables: string[];
}

export interface CollaborativeResponse {
  taskId: string;
  phases: PhaseResult[];
  synthesis: CollaborativeSynthesis;
  consensus: ConsensusMeasure;
  finalRecommendation: string;
  metadata: CollaborativeMetadata;
}

export interface PhaseResult {
  phaseId: string;
  agentId: string;
  result: AgentResponse;
  quality: number;
  confidence: number;
  issues?: string[];
}

export interface CollaborativeSynthesis {
  approach: 'consensus' | 'best_of' | 'hybrid' | 'weighted_average';
  weights: Record<string, number>;
  conflicts: ConflictResolution[];
  finalOutput: string;
  confidenceScore: number;
}

export interface ConflictResolution {
  issue: string;
  positions: Array<{ agent: string; position: string; reasoning: string }>;
  resolution: string;
  method: 'voting' | 'authority' | 'compromise' | 'expert_decision';
}

export interface ConsensusMeasure {
  agreement: number; // 0-1
  conflicts: number;
  convergence: number; // 0-1
  stability: number; // 0-1
}

export interface CollaborativeMetadata {
  totalTime: number;
  participationLevel: Record<string, number>;
  communicationRounds: number;
  decisionsReached: number;
  escalationsRequired: number;
}

export interface AgentFeedback {
  requestId: string;
  responseId: string;
  rating: number; // 1-5
  qualityAspects: QualityFeedback;
  suggestions: string[];
  issues: string[];
  timestamp: Date;
  feedbackProvider: string;
}

export interface QualityFeedback {
  accuracy: number; // 1-5
  completeness: number; // 1-5
  clarity: number; // 1-5
  relevance: number; // 1-5
  efficiency: number; // 1-5
}

// Main Agent Ecosystem
export class AgentEcosystem extends EventEmitter {
  private logger: Logger;
  private agents: Map<string, Agent> = new Map();
  // private workflowOrchestrator: WorkflowOrchestrator;
  private toolOrchestrator: AdvancedToolOrchestrator;
  private ragSystem: VectorRAGSystem;
  private modelRouter: IntelligentModelRouter;
  private collaborationManager: CollaborationManager;
  private learningEngine: AgentLearningEngine;
  private performanceMonitor: AgentPerformanceMonitor;

  constructor(
    _workflowOrchestrator: WorkflowOrchestrator,
    toolOrchestrator: AdvancedToolOrchestrator,
    ragSystem: VectorRAGSystem,
    modelRouter: IntelligentModelRouter
  ) {
    super();
    this.logger = new Logger({ level: 'info' });
    // this.workflowOrchestrator = workflowOrchestrator;
    this.toolOrchestrator = toolOrchestrator;
    this.ragSystem = ragSystem;
    this.modelRouter = modelRouter;

    this.collaborationManager = new CollaborationManager(this);
    this.learningEngine = new AgentLearningEngine();
    this.performanceMonitor = new AgentPerformanceMonitor();
  }

  /**
   * Initialize the agent ecosystem
   */
  async initialize(): Promise<void> {
    this.logger.info('Initializing Agent Ecosystem...');

    try {
      // Create specialized agents
      await this.createSpecializedAgents();

      // Initialize collaboration manager
      await this.collaborationManager.initialize();

      // Start performance monitoring
      this.performanceMonitor.start();

      this.logger.info('Agent Ecosystem initialized successfully');
      this.emit('ecosystem:initialized');
    } catch (error) {
      this.logger.error('Failed to initialize agent ecosystem:', error);
      throw error;
    }
  }

  /**
   * Process a request through the ecosystem
   */
  async processRequest(request: AgentRequest): Promise<AgentResponse> {
    this.logger.info(`Processing request ${request.id} of type ${request.type}`);

    try {
      // Select optimal agent for the request
      const selectedAgent = await this.selectAgent(request);

      // Process the request
      const response = await selectedAgent.process(request);

      // Monitor performance
      this.performanceMonitor.recordRequest(request, response);

      // Check if collaboration is needed
      if (response.collaboration) {
        const collaborativeResponse = await this.handleCollaboration(
          response.collaboration,
          request
        );
        return this.synthesizeCollaborativeResponse(response, collaborativeResponse);
      }

      this.emit('request:completed', { request, response });
      return response;
    } catch (error) {
      this.logger.error(`Failed to process request ${request.id}:`, error);
      throw error;
    }
  }

  /**
   * Execute a collaborative task
   */
  async executeCollaborativeTask(task: CollaborativeTask): Promise<CollaborativeResponse> {
    this.logger.info(`Executing collaborative task: ${task.title}`);

    return await this.collaborationManager.executeTask(task);
  }

  /**
   * Get agent by ID
   */
  getAgent(agentId: string): Agent | undefined {
    return this.agents.get(agentId);
  }

  /**
   * Get all agents
   */
  getAllAgents(): Agent[] {
    return Array.from(this.agents.values());
  }

  /**
   * Get agents by role
   */
  getAgentsByRole(role: string): Agent[] {
    return Array.from(this.agents.values()).filter(agent => agent.role.type === role);
  }

  /**
   * Get available agents
   */
  getAvailableAgents(): Agent[] {
    return Array.from(this.agents.values()).filter(
      agent => agent.status.availability && agent.status.state !== 'offline'
    );
  }

  /**
   * Add custom agent
   */
  async addAgent(agent: Agent): Promise<void> {
    await agent.initialize();
    this.agents.set(agent.id, agent);

    this.logger.info(`Added agent: ${agent.name} (${agent.role.type})`);
    this.emit('agent:added', agent);
  }

  /**
   * Remove agent
   */
  async removeAgent(agentId: string): Promise<void> {
    const agent = this.agents.get(agentId);
    if (agent) {
      await agent.shutdown();
      this.agents.delete(agentId);

      this.logger.info(`Removed agent: ${agent.name}`);
      this.emit('agent:removed', { agentId });
    }
  }

  /**
   * Get ecosystem statistics
   */
  getEcosystemStats(): EcosystemStats {
    const agents = Array.from(this.agents.values());

    return {
      totalAgents: agents.length,
      activeAgents: agents.filter(a => a.status.state !== 'offline').length,
      agentsByRole: this.getAgentDistribution(),
      averageWorkload: this.calculateAverageWorkload(),
      performanceMetrics: this.performanceMonitor.getStats(),
      collaborationStats: this.collaborationManager.getStats(),
      learningProgress: this.learningEngine.getStats(),
    };
  }

  /**
   * Shutdown the ecosystem
   */
  async shutdown(): Promise<void> {
    this.logger.info('Shutting down agent ecosystem...');

    // Shutdown all agents
    for (const agent of this.agents.values()) {
      try {
        await agent.shutdown();
      } catch (error) {
        this.logger.warn(`Failed to shutdown agent ${agent.id}:`, error);
      }
    }

    // Shutdown components
    await this.collaborationManager.shutdown();
    this.performanceMonitor.stop();

    this.logger.info('Agent ecosystem shutdown completed');
  }

  /**
   * Private Methods
   */

  private async createSpecializedAgents(): Promise<void> {
    // Explorer Agent - File discovery and scanning
    const explorerAgent = new ExplorerAgent(
      'explorer-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(explorerAgent);

    // Analyzer Agent - Deep code analysis
    const analyzerAgent = new AnalyzerAgent(
      'analyzer-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(analyzerAgent);

    // Implementor Agent - Code generation and implementation
    const implementorAgent = new ImplementorAgent(
      'implementor-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(implementorAgent);

    // Maintainer Agent - Code maintenance and refactoring
    const maintainerAgent = new MaintainerAgent(
      'maintainer-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(maintainerAgent);

    // Security Agent - Security analysis and hardening
    const securityAgent = new SecurityAgent(
      'security-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(securityAgent);

    // Optimizer Agent - Performance optimization
    const optimizerAgent = new OptimizerAgent(
      'optimizer-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(optimizerAgent);

    // Tester Agent - Testing and quality assurance
    const testerAgent = new TesterAgent(
      'tester-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(testerAgent);

    // Architect Agent - System architecture and design
    const architectAgent = new ArchitectAgent(
      'architect-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(architectAgent);

    // Reviewer Agent - Code review and quality assessment
    const reviewerAgent = new ReviewerAgent(
      'reviewer-001',
      this.ragSystem,
      this.toolOrchestrator,
      this.modelRouter
    );
    await this.addAgent(reviewerAgent);
  }

  private async selectAgent(request: AgentRequest): Promise<Agent> {
    const availableAgents = this.getAvailableAgents();

    // Simple selection based on request type
    const preferredRoles: Record<string, string> = {
      analysis: 'analyzer',
      implementation: 'implementor',
      review: 'reviewer',
      optimization: 'optimizer',
      testing: 'tester',
      documentation: 'maintainer',
      planning: 'architect',
    };

    const preferredRole = preferredRoles[request.type];
    let selectedAgent = availableAgents.find(agent => agent.role.type === preferredRole);

    // Fallback to any available agent
    if (!selectedAgent) {
      selectedAgent = availableAgents[0];
    }

    if (!selectedAgent) {
      throw new Error('No available agents to handle the request');
    }

    return selectedAgent;
  }

  private async handleCollaboration(
    collaborationRequest: CollaborationRequest,
    originalRequest: AgentRequest
  ): Promise<CollaborativeResponse> {
    // Create collaborative task
    const task: CollaborativeTask = {
      id: `collab_${Date.now()}`,
      title: `Collaborative ${collaborationRequest.type}`,
      description: collaborationRequest.content,
      type: originalRequest.type as any,
      complexity: 5, // Medium complexity
      participants: collaborationRequest.targetAgents,
      coordinator: 'system',
      phases: [],
      dependencies: [],
      deadline: originalRequest.deadline || new Date(),
    };

    return await this.executeCollaborativeTask(task);
  }

  private synthesizeCollaborativeResponse(
    originalResponse: AgentResponse,
    collaborativeResponse: CollaborativeResponse
  ): AgentResponse {
    // Combine individual and collaborative responses
    return {
      ...originalResponse,
      content: collaborativeResponse.finalRecommendation,
      confidence: Math.max(
        originalResponse.confidence,
        collaborativeResponse.synthesis.confidenceScore
      ),
      reasoning: `${originalResponse.reasoning}\n\nCollaborative Analysis: ${collaborativeResponse.synthesis.finalOutput}`,
    };
  }

  private getAgentDistribution(): Record<string, number> {
    const distribution: Record<string, number> = {};

    for (const agent of this.agents.values()) {
      const role = agent.role.type;
      distribution[role] = (distribution[role] || 0) + 1;
    }

    return distribution;
  }

  private calculateAverageWorkload(): number {
    const agents = Array.from(this.agents.values());
    if (agents.length === 0) return 0;

    const totalWorkload = agents.reduce((sum, agent) => sum + agent.status.workload, 0);
    return totalWorkload / agents.length;
  }
}

// Base Agent Implementation
abstract class BaseAgent implements Agent {
  id: string;
  name: string;
  role: AgentRole;
  personality: AgentPersonality;
  capabilities: AgentCapability[];
  expertise: ExpertiseDomain[];
  status: AgentStatus;
  configuration: AgentConfiguration;

  protected logger: Logger;
  protected ragSystem: VectorRAGSystem;
  protected toolOrchestrator: AdvancedToolOrchestrator;
  protected modelRouter: IntelligentModelRouter;

  constructor(
    id: string,
    name: string,
    role: AgentRole,
    personality: AgentPersonality,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    this.id = id;
    this.name = name;
    this.role = role;
    this.personality = personality;
    this.ragSystem = ragSystem;
    this.toolOrchestrator = toolOrchestrator;
    this.modelRouter = modelRouter;

    this.logger = new Logger({ level: 'info' });

    // Initialize default status
    this.status = {
      state: 'idle',
      workload: 0,
      availability: true,
      lastActivity: new Date(),
      health: {
        performance: 100,
        errorRate: 0,
        responseTime: 0,
        memoryUsage: 0,
        issueCount: 0,
        lastHealthCheck: new Date(),
      },
    };

    // Initialize default configuration
    this.configuration = this.getDefaultConfiguration();
    this.capabilities = this.getDefaultCapabilities();
    this.expertise = this.getDefaultExpertise();
  }

  async initialize(): Promise<void> {
    this.logger.info(`Initializing agent: ${this.name}`);
    await this.customInitialization();
    this.status.state = 'idle';
  }

  abstract process(request: AgentRequest): Promise<AgentResponse>;

  async collaborate(agents: Agent[], task: CollaborativeTask): Promise<CollaborativeResponse> {
    try {
      // Default collaboration implementation using round-robin approach
      const responses: AgentResponse[] = [];
      const participatingAgents = agents.filter(agent => agent !== this);

      this.logger.info(
        `Starting collaboration with ${participatingAgents.length} agents for task: ${task.type}`
      );

      const startTime = Date.now();

      // Execute task with each participating agent
      for (const agent of participatingAgents) {
        try {
          const response = await (agent as any).process({
            prompt: (task as any).prompt || task.description,
            context: (task as any).context,
            type: task.type,
            constraints: (task as any).constraints,
          });

          responses.push({
            id: `resp_${Date.now()}_${agent.id}`,
            requestId: (task as any).id || `task_${Date.now()}`,
            agentId: agent.id,
            content: response.content || response.result?.toString() || '',
            confidence: response.confidence || 0.8,
            reasoning:
              response.reasoning || `Response from ${(agent as any).type || 'unknown'} agent`,
            metadata: {
              processingTime: Date.now() - startTime,
              tokensUsed: 0,
              toolsUsed: [],
              modelsUsed: [(agent as any).model || 'unknown'],
              qualityScore: response.confidence || 0.8,
              complexity: 1,
              resources: {
                cpu: 0.1,
                memory: 0.1,
                cost: 0.01,
                apiCalls: 1,
              },
            },
          });
        } catch (error) {
          this.logger.warn(`Agent ${agent.id} failed in collaboration:`, error);
          responses.push({
            id: `resp_${Date.now()}_${agent.id}`,
            requestId: (task as any).id || `task_${Date.now()}`,
            agentId: agent.id,
            content: `Error: ${error instanceof Error ? error.message : String(error)}`,
            confidence: 0,
            reasoning: 'Agent execution failed',
            metadata: {
              processingTime: Date.now() - startTime,
              tokensUsed: 0,
              toolsUsed: [],
              modelsUsed: [],
              qualityScore: 0,
              complexity: 1,
              resources: {
                cpu: 0.1,
                memory: 0.1,
                cost: 0.01,
                apiCalls: 1,
              },
            },
          });
        }
      }

      // Synthesize collaborative response
      const synthesizedContent = this.synthesizeResponses(
        responses,
        (task as any).synthesis || 'consensus'
      );
      const averageConfidence =
        responses.reduce((sum, r) => sum + r.confidence, 0) / responses.length;

      return {
        taskId: (task as any).id || `task_${Date.now()}`,
        phases: responses.map(response => ({
          phaseId: `phase_${response.agentId}`,
          agentId: response.agentId,
          result: response,
          quality: response.confidence,
          confidence: response.confidence,
          issues: response.confidence < 0.5 ? ['Low confidence response'] : [],
        })),
        synthesis: {
          approach: 'consensus' as const,
          weights: responses.reduce((acc, r) => ({ ...acc, [r.agentId]: r.confidence }), {}),
          conflicts: [],
          finalOutput: synthesizedContent,
          confidenceScore: averageConfidence,
        },
        consensus: {
          agreement: averageConfidence,
          conflicts: responses.filter(r => r.confidence < 0.5).length,
          convergence: averageConfidence,
          stability: averageConfidence,
        },
        finalRecommendation: synthesizedContent,
        metadata: {
          totalTime: responses.reduce((sum, r) => sum + (r.metadata?.processingTime || 0), 0),
          participationLevel: responses.reduce(
            (acc, r) => ({ ...acc, [r.agentId]: r.confidence }),
            {}
          ),
          communicationRounds: 1,
          decisionsReached: 1,
          escalationsRequired: 0,
        },
      };
    } catch (error) {
      throw new Error(
        `Collaboration failed: ${error instanceof Error ? error.message : String(error)}`
      );
    }
  }

  private synthesizeResponses(
    responses: AgentResponse[],
    method: 'consensus' | 'best' | 'merge'
  ): string {
    if (responses.length === 0) {
      return 'No responses available for synthesis';
    }

    switch (method) {
      case 'best': {
        // Return the response with highest confidence
        const bestResponse = responses.reduce((best, current) =>
          current.confidence > best.confidence ? current : best
        );
        return bestResponse.content;
      }

      case 'merge':
        // Merge all responses with separators
        return responses.map(r => `**${r.agentId}**: ${r.content}`).join('\n\n---\n\n');

      case 'consensus':
      default: {
        // Simple consensus: use majority approach or highest confidence
        if (responses.length === 1) {
          return responses[0]?.content || '';
        }

        // For multiple responses, combine them intelligently
        const highConfidenceResponses = responses.filter(r => r.confidence > 0.7);
        if (highConfidenceResponses.length > 0) {
          return highConfidenceResponses.map(r => r.content).join('\n\n');
        }

        // Fallback to best response
        return responses.reduce((best, current) =>
          current.confidence > best.confidence ? current : best
        ).content;
      }
    }
  }

  async learn(feedback: AgentFeedback): Promise<void> {
    // Basic learning implementation
    this.logger.debug(`Received feedback for request ${feedback.requestId}: ${feedback.rating}/5`);

    // Update expertise based on feedback
    this.updateExpertiseFromFeedback(feedback);
  }

  async shutdown(): Promise<void> {
    this.logger.info(`Shutting down agent: ${this.name}`);
    this.status.state = 'offline';
    await this.customShutdown();
  }

  protected abstract customInitialization(): Promise<void>;
  protected abstract customShutdown(): Promise<void>;
  protected abstract getDefaultCapabilities(): AgentCapability[];
  protected abstract getDefaultExpertise(): ExpertiseDomain[];

  protected getDefaultConfiguration(): AgentConfiguration {
    return {
      modelPreferences: [
        {
          providerId: 'ollama',
          modelId: 'codellama:34b',
          priority: 1,
          useCase: ['analysis', 'reasoning'],
          configuration: {},
        },
      ],
      behaviorSettings: {
        verbosity: 'normal',
        responseStyle: 'explanatory',
        errorHandling: 'adaptive',
        optimizationLevel: 'balanced',
      },
      collaborationSettings: {
        preferredTeamSize: 3,
        leadershipStyle: 'situational',
        communicationFrequency: 'regular',
        conflictResolution: 'consensus',
      },
      learningSettings: {
        adaptationRate: 0.1,
        feedbackSensitivity: 0.8,
        explorationRate: 0.2,
        memoryRetention: 30,
        learningMethods: ['feedback', 'observation', 'experimentation'],
      },
      resourceLimits: {
        maxMemoryUsage: 512,
        maxProcessingTime: 300,
        maxConcurrentTasks: 3,
        maxToolsPerTask: 10,
        costBudget: 1.0,
      },
    };
  }

  protected updateExpertiseFromFeedback(feedback: AgentFeedback): void {
    // Simple expertise update based on feedback
    // In production, this would be more sophisticated
    for (const domain of this.expertise) {
      if (feedback.rating >= 4) {
        domain.level = Math.min(100, domain.level + 1);
      } else if (feedback.rating <= 2) {
        domain.level = Math.max(0, domain.level - 1);
      }
    }
  }

  protected async generateResponse(
    request: AgentRequest,
    analysis: string,
    actions?: AgentAction[]
  ): Promise<AgentResponse> {
    const response: AgentResponse = {
      id: `response_${Date.now()}`,
      requestId: request.id,
      agentId: this.id,
      content: analysis,
      confidence: 0.8, // Default confidence
      reasoning: `Processed as ${this.role.type} with ${this.personality.approach} approach`,
      metadata: {
        processingTime: 0,
        tokensUsed: 0,
        toolsUsed: [],
        modelsUsed: [],
        qualityScore: 0.8,
        complexity: this.assessComplexity(request),
        resources: {
          cpu: 0,
          memory: 0,
          cost: 0,
          apiCalls: 0,
        },
      },
      actions: actions || [],
    };

    return response;
  }

  protected assessComplexity(request: AgentRequest): number {
    // Simple complexity assessment
    let complexity = 0.5;

    if (request.content.length > 1000) complexity += 0.2;
    if (request.context?.codebase?.complexity) {
      complexity += request.context.codebase.complexity * 0.3;
    }
    if (request.priority === 'critical') complexity += 0.1;

    return Math.min(1.0, complexity);
  }
}

// Specialized Agent Implementations

class ExplorerAgent extends BaseAgent {
  constructor(
    id: string,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    super(
      id,
      'Code Explorer',
      {
        type: 'explorer',
        description: 'Discovers and maps code structures, dependencies, and patterns',
        responsibilities: [
          'file discovery',
          'dependency analysis',
          'pattern recognition',
          'code mapping',
        ],
        authority: 'advisory',
        scope: 'project',
      },
      {
        approach: 'methodical',
        communication: 'detailed',
        riskTolerance: 'low',
        decisionStyle: 'deliberate',
        learningStyle: 'observational',
      },
      ragSystem,
      toolOrchestrator,
      modelRouter
    );
  }

  async process(request: AgentRequest): Promise<AgentResponse> {
    this.status.state = 'busy';

    try {
      // Explorer-specific processing logic
      const analysis = await this.exploreCodebase(request);
      const actions = await this.generateExplorationActions(request);

      return await this.generateResponse(request, analysis, actions);
    } finally {
      this.status.state = 'idle';
    }
  }

  protected async customInitialization(): Promise<void> {
    // Explorer-specific initialization
  }

  protected async customShutdown(): Promise<void> {
    // Explorer-specific cleanup
  }

  protected getDefaultCapabilities(): AgentCapability[] {
    return [
      {
        name: 'file_discovery',
        level: 'expert',
        description: 'Discover and catalog files in a codebase',
        tools: ['file_scanner', 'dependency_analyzer'],
        learnable: true,
      },
      {
        name: 'pattern_recognition',
        level: 'expert',
        description: 'Identify architectural and code patterns',
        tools: ['ast_analyzer', 'pattern_matcher'],
        learnable: true,
      },
    ];
  }

  protected getDefaultExpertise(): ExpertiseDomain[] {
    return [
      {
        area: 'code_exploration',
        level: 90,
        technologies: ['git', 'ast', 'static_analysis'],
        frameworks: ['typescript', 'javascript', 'python'],
        patterns: ['mvc', 'repository', 'factory'],
        experience: [],
      },
    ];
  }

  private async exploreCodebase(request: AgentRequest): Promise<string> {
    // Implementation would perform actual codebase exploration
    return `Explored codebase structure for: ${request.content}`;
  }

  // eslint-disable-next-line @typescript-eslint/no-unused-vars
  private async generateExplorationActions(_request: AgentRequest): Promise<AgentAction[]> {
    return [
      {
        type: 'analysis_run',
        target: 'codebase',
        parameters: { type: 'structure_analysis' },
        reversible: true,
      },
    ];
  }
}

class AnalyzerAgent extends BaseAgent {
  constructor(
    id: string,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    super(
      id,
      'Code Analyzer',
      {
        type: 'analyzer',
        description: 'Performs deep analysis of code quality, complexity, and issues',
        responsibilities: [
          'quality analysis',
          'complexity assessment',
          'issue detection',
          'metrics calculation',
        ],
        authority: 'advisory',
        scope: 'project',
      },
      {
        approach: 'methodical',
        communication: 'analytical',
        riskTolerance: 'medium',
        decisionStyle: 'deliberate',
        learningStyle: 'theoretical',
      },
      ragSystem,
      toolOrchestrator,
      modelRouter
    );
  }

  async process(request: AgentRequest): Promise<AgentResponse> {
    this.status.state = 'busy';

    try {
      const analysis = await this.analyzeCode(request);
      const actions = await this.generateAnalysisActions(request);

      return await this.generateResponse(request, analysis, actions);
    } finally {
      this.status.state = 'idle';
    }
  }

  protected async customInitialization(): Promise<void> {
    // Analyzer-specific initialization
  }

  protected async customShutdown(): Promise<void> {
    // Analyzer-specific cleanup
  }

  protected getDefaultCapabilities(): AgentCapability[] {
    return [
      {
        name: 'quality_analysis',
        level: 'expert',
        description: 'Analyze code quality and identify issues',
        tools: ['linter', 'complexity_analyzer', 'security_scanner'],
        learnable: true,
      },
      {
        name: 'performance_analysis',
        level: 'expert',
        description: 'Identify performance bottlenecks and optimization opportunities',
        tools: ['profiler', 'benchmarker', 'memory_analyzer'],
        learnable: true,
      },
    ];
  }

  protected getDefaultExpertise(): ExpertiseDomain[] {
    return [
      {
        area: 'code_analysis',
        level: 95,
        technologies: ['static_analysis', 'dynamic_analysis', 'profiling'],
        frameworks: ['eslint', 'sonarqube', 'codecov'],
        patterns: ['solid', 'clean_code', 'design_patterns'],
        experience: [],
      },
    ];
  }

  private async analyzeCode(request: AgentRequest): Promise<string> {
    // Implementation would perform actual code analysis
    return `Analyzed code for: ${request.content}`;
  }

  // eslint-disable-next-line @typescript-eslint/no-unused-vars
  private async generateAnalysisActions(_request: AgentRequest): Promise<AgentAction[]> {
    return [
      {
        type: 'analysis_run',
        target: 'code',
        parameters: { type: 'quality_analysis' },
        reversible: true,
      },
    ];
  }
}

// Additional specialized agents would be implemented similarly...
class ImplementorAgent extends BaseAgent {
  constructor(
    id: string,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    super(
      id,
      'Code Implementor',
      {
        type: 'implementor',
        description: 'Generates and implements code solutions',
        responsibilities: ['code generation', 'feature implementation', 'bug fixes', 'prototyping'],
        authority: 'implementation',
        scope: 'local',
      },
      {
        approach: 'pragmatic',
        communication: 'concise',
        riskTolerance: 'medium',
        decisionStyle: 'quick',
        learningStyle: 'experiential',
      },
      ragSystem,
      toolOrchestrator,
      modelRouter
    );
  }

  async process(request: AgentRequest): Promise<AgentResponse> {
    this.status.state = 'busy';
    try {
      const implementation = await this.generateImplementation(request);
      const actions = await this.generateImplementationActions(request);
      return await this.generateResponse(request, implementation, actions);
    } finally {
      this.status.state = 'idle';
    }
  }

  protected async customInitialization(): Promise<void> {}
  protected async customShutdown(): Promise<void> {}

  protected getDefaultCapabilities(): AgentCapability[] {
    return [
      {
        name: 'code_generation',
        level: 'expert',
        description: 'Generate high-quality code solutions',
        tools: ['code_generator', 'template_engine', 'scaffolder'],
        learnable: true,
      },
    ];
  }

  protected getDefaultExpertise(): ExpertiseDomain[] {
    return [
      {
        area: 'software_implementation',
        level: 88,
        technologies: ['typescript', 'javascript', 'python', 'go'],
        frameworks: ['react', 'node', 'express', 'fastapi'],
        patterns: ['mvc', 'repository', 'factory', 'observer'],
        experience: [],
      },
    ];
  }

  private async generateImplementation(request: AgentRequest): Promise<string> {
    return `Generated implementation for: ${request.content}`;
  }

  // eslint-disable-next-line @typescript-eslint/no-unused-vars
  private async generateImplementationActions(_request: AgentRequest): Promise<AgentAction[]> {
    return [
      {
        type: 'file_create',
        target: 'implementation.ts',
        parameters: { content: 'generated code' },
        reversible: true,
      },
    ];
  }
}

class MaintainerAgent extends BaseAgent {
  constructor(
    id: string,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    super(
      id,
      'Code Maintainer',
      {
        type: 'maintainer',
        description: 'Maintains and refactors existing code',
        responsibilities: ['refactoring', 'documentation', 'dependency updates', 'code cleanup'],
        authority: 'implementation',
        scope: 'project',
      },
      {
        approach: 'conservative',
        communication: 'detailed',
        riskTolerance: 'low',
        decisionStyle: 'deliberate',
        learningStyle: 'observational',
      },
      ragSystem,
      toolOrchestrator,
      modelRouter
    );
  }

  async process(request: AgentRequest): Promise<AgentResponse> {
    this.status.state = 'busy';
    try {
      const maintenance = await this.performMaintenance(request);
      const actions = await this.generateMaintenanceActions(request);
      return await this.generateResponse(request, maintenance, actions);
    } finally {
      this.status.state = 'idle';
    }
  }

  protected async customInitialization(): Promise<void> {}
  protected async customShutdown(): Promise<void> {}

  protected getDefaultCapabilities(): AgentCapability[] {
    return [
      {
        name: 'refactoring',
        level: 'expert',
        description: 'Refactor code while preserving functionality',
        tools: ['refactoring_engine', 'test_runner', 'dependency_updater'],
        learnable: true,
      },
    ];
  }

  protected getDefaultExpertise(): ExpertiseDomain[] {
    return [
      {
        area: 'code_maintenance',
        level: 85,
        technologies: ['refactoring', 'legacy_systems', 'migration'],
        frameworks: ['jest', 'mocha', 'pytest'],
        patterns: ['refactoring_patterns', 'legacy_patterns'],
        experience: [],
      },
    ];
  }

  private async performMaintenance(request: AgentRequest): Promise<string> {
    return `Performed maintenance for: ${request.content}`;
  }

  // eslint-disable-next-line @typescript-eslint/no-unused-vars
  private async generateMaintenanceActions(_request: AgentRequest): Promise<AgentAction[]> {
    return [
      {
        type: 'file_modify',
        target: 'legacy_file.ts',
        parameters: { refactor: true },
        reversible: true,
      },
    ];
  }
}

class SecurityAgent extends BaseAgent {
  constructor(
    id: string,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    super(
      id,
      'Security Specialist',
      {
        type: 'security',
        description: 'Analyzes and improves security aspects of code',
        responsibilities: [
          'vulnerability scanning',
          'security hardening',
          'compliance checking',
          'threat modeling',
        ],
        authority: 'advisory',
        scope: 'system',
      },
      {
        approach: 'perfectionist',
        communication: 'technical',
        riskTolerance: 'low',
        decisionStyle: 'deliberate',
        learningStyle: 'theoretical',
      },
      ragSystem,
      toolOrchestrator,
      modelRouter
    );
  }

  async process(request: AgentRequest): Promise<AgentResponse> {
    this.status.state = 'busy';
    try {
      const securityAnalysis = await this.analyzeSecurity(request);
      const actions = await this.generateSecurityActions(request);
      return await this.generateResponse(request, securityAnalysis, actions);
    } finally {
      this.status.state = 'idle';
    }
  }

  protected async customInitialization(): Promise<void> {}
  protected async customShutdown(): Promise<void> {}

  protected getDefaultCapabilities(): AgentCapability[] {
    return [
      {
        name: 'vulnerability_detection',
        level: 'expert',
        description: 'Detect security vulnerabilities in code',
        tools: ['security_scanner', 'sast_tools', 'dependency_checker'],
        learnable: true,
      },
    ];
  }

  protected getDefaultExpertise(): ExpertiseDomain[] {
    return [
      {
        area: 'cybersecurity',
        level: 92,
        technologies: ['owasp', 'sast', 'dast', 'penetration_testing'],
        frameworks: ['snyk', 'sonarqube', 'checkmarx'],
        patterns: ['secure_coding', 'authentication', 'authorization'],
        experience: [],
      },
    ];
  }

  private async analyzeSecurity(request: AgentRequest): Promise<string> {
    return `Performed security analysis for: ${request.content}`;
  }

  // eslint-disable-next-line @typescript-eslint/no-unused-vars
  private async generateSecurityActions(_request: AgentRequest): Promise<AgentAction[]> {
    return [
      {
        type: 'analysis_run',
        target: 'security_scan',
        parameters: { type: 'vulnerability_scan' },
        reversible: true,
      },
    ];
  }
}

class OptimizerAgent extends BaseAgent {
  constructor(
    id: string,
    ragSystem: VectorRAGSystem,
    toolOrchestrator: AdvancedToolOrchestrator,
    modelRouter: IntelligentModelRouter
  ) {
    super(
      id,
      'Performance Optimizer',
      {
        type: 'optimizer',
        description: 'Optimizes code and system performance',
        responsibilities: [
          'performance tuning',
          'resource optimization',
          'bottleneck identification',
          'scaling recommendations',
        ],
        authority: 'implementation',
        scope: 'system',
      },
      {
        approach: 'innovative',
        communication: 'technical',
        riskTolerance: 'medium',
        decisionStyle: 'quick',
        learningStyle: 'experiential',
      },
      ragSystem,
      toolOrchestrator,
      modelRouter
    );
  }

  async process(request: AgentRequest): Promise<AgentResponse> {
    this.status.state = 'busy';
    try {
      const optimization = await this.optimizePerformance(request);
      const actions = await this.generateOptimizationActions(request);
      return await this.generateResponse(request, optimization, actions);
    } finally {
      this.status.state = 'idle';
    }
  }

  protected async customInitialization(): Promise<void> {}
  protected async customShutdown(): Promise<void> {}

  protected getDefaultCapabilities(): AgentCapability[] {
    return [
      {
        name: 'performance_optimization',
        level: 'expert',
        description: 'Optimize system and code performance',
        tools: ['profiler', 'benchmarker', 'optimizer'],
        learnable: true,
      },
      {
        name: 'memory_management',
        level: 'expert',
        description: 'Detect and prevent memory leaks',
        tools: ['memory_profiler', 'gc_analyzer', 'leak_detector'],
        learnable: true,
      },
      {
        name: 'algorithm_optimization',
        level: 'expert',
        description: 'Optimize algorithms and data structures',
        tools: ['complexity_analyzer', 'benchmark_suite', 'profiler'],
        learnable: true,
      },
      {
        name: 'async_optimization',
        level: 'expert',
        description: 'Optimize asynchronous operations',
        tools: ['concurrency_analyzer', 'event_loop_monitor', 'promise_tracker'],
        learnable: true,
      },
    ];
  }

  protected getDefaultExpertise(): ExpertiseDomain[] {
    return [
      {
        area: 'performance_engineering',
        level: 87,
        technologies: ['profiling', 'benchmarking', 'caching', 'optimization'],
        frameworks: ['performance_monitoring', 'apm_tools'],
        patterns: ['caching_patterns', 'optimization_patterns'],
        experience: [],
      },
    ];
  }

  private async optimizePerformance(request: AgentRequest): Promise<string> {
    try {
      // Analyze the request content for performance optimization opportunities
      const performanceAnalysis = await this.analyzePerformance(request.content);

      // Generate optimization recommendations
      const optimizations = [];

      // Check for common performance issues
      if (performanceAnalysis.hasMemoryLeaks) {
        optimizations.push('Memory leak detection and prevention');
      }

      if (performanceAnalysis.hasInefficientLoops) {
        optimizations.push('Loop optimization and algorithmic improvements');
      }

      if (performanceAnalysis.hasBlockingOperations) {
        optimizations.push('Async/await optimization for non-blocking operations');
      }

      if (performanceAnalysis.hasCachingOpportunities) {
        optimizations.push('Caching strategy implementation');
      }

      if (performanceAnalysis.hasLargePayloads) {
        optimizations.push('Data compression and payload optimization');
      }

      return `Performance optimization analysis complete:\n${optimizations.map(opt => `• ${opt}`).join('\n')}`;
    } catch (error) {
      return `Performance optimization failed: ${error instanceof Error ? error.message : 'Unknown error'}`;
    }
  }

  private async analyzePerformance(content: string): Promise<any> {
    const analysis = {
      hasMemoryLeaks: false,
      hasInefficientLoops: false,
      hasBlockingOperations: false,
      hasCachingOpportunities: false,
      hasLargePayloads: false,
    };

    // Check for memory leak patterns
    if (
      /new\s+\w+|setInterval|addEventListener/gi.test(content) &&
      !/cleanup|dispose|removeEventListener|clearInterval/gi.test(content)
    ) {
      analysis.hasMemoryLeaks = true;
    }

    // Check for inefficient loops
    if (/for\s*\([^)]*\.[^)]*length[^)]*\)|while\s*\([^)]*\.[^)]*length[^)]*\)/gi.test(content)) {
      analysis.hasInefficientLoops = true;
    }

    // Check for blocking operations
    if (/\.readFileSync|sleep\(|setTimeout\s*\([^,]*,\s*[5-9]\d{3,}/gi.test(content)) {
      analysis.hasBlockingOperations = true;
    }

    // Check for caching opportunities
    if (
      /fetch\(|axios\.|http\.|database\.|query\(/gi.test(content) &&
      !/cache|memoize|store/gi.test(content)
    ) {
      analysis.hasCachingOpportunities = true;
    }

    // Check for large payloads
    if (/JSON\.stringify|response\.data|largeObject/gi.test(content)) {
      analysis.hasLargePayloads = true;
    }

    return analysis;
  }

  private async generateOptimizationActions(request: AgentRequest): Promise<AgentAction[]> {
    const actions: AgentAction[] = [];

    try {
      const performanceAnalysis = await this.analyzePerformance(request.content);

      // Generate specific optimization actions based on analysis
      if (performanceAnalysis.hasMemoryLeaks) {
        actions.push({
          type: 'file_modify',
          target: 'memory-optimization.ts',
          parameters: {
            optimization: 'memory_leak_prevention',
            techniques: ['weak_references', 'disposal_patterns', 'gc_optimization'],
          },
          reversible: true,
        });
      }

      if (performanceAnalysis.hasInefficientLoops) {
        actions.push({
          type: