codecrucible-synth/src/core/workflow/workflow-orchestrator.ts

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

/**
 * Advanced Workflow Orchestrator implementing 9 industry-standard agentic patterns
 * Based on research from Amazon Q CLI, ZCF, and emerging AI agent architectures
 */

import { EventEmitter } from 'events';
import { UnifiedModelClient } from '../../refactor/unified-model-client.js';
import { Logger } from '../logger.js';
import { getErrorMessage } from '../../utils/error-utils.js';
import {
  JsonValue,
  JsonObject,
  ConfigurationObject,
  TransformFunction,
  PredicateFunction,
  EvaluationFunction,
  WorkflowContext,
  MemoryItem,
  GenericResult,
} from '../types.js';

// Utility Functions
/**
 * Convert ModelResponse to JsonValue for workflow compatibility
 */
function modelResponseToJsonValue(response: any): JsonValue {
  if (!response || typeof response !== 'object') {
    return response;
  }

  // Convert ModelResponse to plain JsonObject
  const jsonObject: JsonObject = {
    content: response.content || '',
    model: response.model || '',
    provider: response.provider || '',
    metadata: response.metadata || {},
    tokens_used: response.tokens_used || 0,
    usage: response.usage || {},
    cached: response.cached || false,
    streamed: response.streamed || false,
    processingTime: response.processingTime || 0,
  };

  return jsonObject;
}

// Core Types
export interface ExecutionRequest {
  id?: string;
  prompt: string;
  voice?: string;
  model?: string;
  maxTokens?: number;
  temperature?: number;
  stream?: boolean;
  metadata?: Record<string, unknown>;
}

export interface ExecutionResponse {
  success: boolean;
  result?: unknown;
  error?: string;
  executionTime: number;
  metadata?: Record<string, unknown>;
}

export interface ExecutionResult {
  success: boolean;
  content: unknown;
  metadata?: Record<string, unknown>;
}

// Workflow Pattern Types
export enum WorkflowPatternType {
  SEQUENTIAL = 'sequential',
  PARALLEL = 'parallel',
  HIERARCHICAL = 'hierarchical',
  ADAPTIVE = 'adaptive',
  FEEDBACK = 'feedback',
  ITERATIVE = 'iterative',
  BRANCHING = 'branching',
  STREAMING = 'streaming',
  MEMORY = 'memory',
}

// Pattern Interfaces
export interface PromptChaining {
  steps: ChainStep[];
  context: Map<string, unknown>;
}

export interface ChainStep {
  id: string;
  prompt: string;
  voice?: string;
  dependencies?: string[];
  transform?: TransformFunction<JsonValue, JsonValue>;
}

export interface ParallelProcessing {
  tasks: ParallelTask[];
  concurrency: number;
  aggregation: 'merge' | 'reduce' | 'select';
}

export interface ParallelTask {
  id: string;
  request: ExecutionRequest;
  weight: number;
  timeout?: number;
}

export interface MultiAgentOrchestration {
  agents: AgentRole[];
  coordinator: string;
  communicationProtocol: 'direct' | 'broadcast' | 'pubsub';
}

export interface AgentRole {
  id: string;
  type: string;
  capabilities: string[];
  priority: number;
}

export interface DynamicWorkflow {
  initialPlan: WorkflowNode[];
  adaptationRules: AdaptationRule[];
  learningRate: number;
}

export interface WorkflowNode {
  id: string;
  type: WorkflowPatternType;
  config: ConfigurationObject;
  transitions: Transition[];
}

export interface Transition {
  to: string;
  condition: PredicateFunction<WorkflowContext>;
  probability?: number;
}

export interface AdaptationRule {
  trigger: (context: WorkflowContext, history: JsonValue[]) => boolean;
  action: (workflow: DynamicWorkflow) => void;
}

export interface HumanInTheLoop {
  checkpoints: Checkpoint[];
  escalationPolicy: EscalationPolicy;
  feedbackLoop: FeedbackConfig;
}

export interface Checkpoint {
  id: string;
  condition: PredicateFunction<JsonValue>;
  prompt: string;
  timeout: number;
}

export interface EscalationPolicy {
  maxRetries: number;
  escalationPath: string[];
  fallbackBehavior: 'skip' | 'default' | 'abort';
}

export interface FeedbackConfig {
  collectMetrics: boolean;
  learningEnabled: boolean;
  persistFeedback: boolean;
}

export interface ReflectiveRefinement {
  maxIterations: number;
  qualityThreshold: number;
  refinementStrategy: 'critique' | 'improve' | 'regenerate';
  evaluationCriteria: EvaluationCriteria[];
}

export interface EvaluationCriteria {
  name: string;
  weight: number;
  evaluate: (result: any) => number;
}

export interface ConditionalExecution {
  branches: Branch[];
  defaultBranch?: string;
  evaluationOrder: 'sequential' | 'parallel';
}

export interface Branch {
  id: string;
  condition: (context: any) => boolean;
  workflow: WorkflowNode;
  priority: number;
}

export interface RealTimeProcessing {
  streamingEnabled: boolean;
  chunkSize: number;
  bufferStrategy: 'window' | 'sliding' | 'circular';
  onChunk: (chunk: any) => void;
  transform?: (content: string) => string;
}

export interface ContextualContinuation {
  memoryType: 'short' | 'long' | 'episodic' | 'semantic';
  retentionPolicy: RetentionPolicy;
  contextWindow: number;
}

export interface RetentionPolicy {
  maxItems: number;
  ttl: number;
  importance: (item: any) => number;
}

// Main Orchestrator Class
export class WorkflowOrchestrator extends EventEmitter {
  private modelClient: UnifiedModelClient;
  private logger: Logger;
  private executionHistory: Map<string, ExecutionResult[]>;
  private activeWorkflows: Map<string, WorkflowExecution>;
  private patternHandlers: Map<WorkflowPatternType, PatternHandler>;
  private cleanupInterval: NodeJS.Timeout | null = null;
  private isDisposed: boolean = false;
  private readonly MAX_HISTORY_SIZE = 1000;
  private readonly MAX_ACTIVE_WORKFLOWS = 100;

  constructor(modelClient: UnifiedModelClient) {
    super();
    this.modelClient = modelClient;
    this.logger = new Logger('WorkflowOrchestrator');
    this.executionHistory = new Map();
    this.activeWorkflows = new Map();
    this.patternHandlers = this.initializeHandlers();

    // Set up periodic cleanup to prevent memory leaks
    this.setupCleanupInterval();
  }

  /**
   * Initialize the workflow orchestrator
   */
  async initialize(): Promise<void> {
    this.logger.info('Initializing Workflow Orchestrator');
    // Initialize any async resources if needed
    // Currently, all initialization is done in constructor
    return Promise.resolve();
  }

  private setupCleanupInterval(): void {
    // Run cleanup every 10 minutes
    this.cleanupInterval = setInterval(
      () => {
        if (this.isDisposed) {
          if (this.cleanupInterval) {
            clearInterval(this.cleanupInterval);
            this.cleanupInterval = null;
          }
          return;
        }

        this.performCleanup();
      },
      10 * 60 * 1000
    );

    // Ensure cleanup interval doesn't prevent process exit
    if (this.cleanupInterval?.unref) {
      this.cleanupInterval.unref();
    }
  }

  private performCleanup(): void {
    // Basic cleanup - can be expanded
    try {
      const now = Date.now();
      // Clean up old executions
      for (const [key, execution] of this.activeWorkflows) {
        if (now - execution.startTime > 3600000) {
          // 1 hour
          this.activeWorkflows.delete(key);
        }
      }
      this.logger.info('🧹 Performed periodic cleanup');
    } catch (error) {
      this.logger.error('Failed to perform cleanup:', error);
    }
  }

  private initializeHandlers(): Map<WorkflowPatternType, PatternHandler> {
    const handlers = new Map<WorkflowPatternType, PatternHandler>();

    handlers.set(WorkflowPatternType.SEQUENTIAL, new SequentialHandler(this.modelClient));
    handlers.set(WorkflowPatternType.PARALLEL, new ParallelHandler(this.modelClient));
    handlers.set(WorkflowPatternType.HIERARCHICAL, new HierarchicalHandler(this.modelClient));
    handlers.set(WorkflowPatternType.ADAPTIVE, new AdaptiveHandler(this.modelClient));
    handlers.set(WorkflowPatternType.FEEDBACK, new FeedbackHandler(this.modelClient));
    handlers.set(WorkflowPatternType.ITERATIVE, new IterativeHandler(this.modelClient));
    handlers.set(WorkflowPatternType.BRANCHING, new BranchingHandler(this.modelClient));
    handlers.set(WorkflowPatternType.STREAMING, new StreamingHandler(this.modelClient));
    handlers.set(WorkflowPatternType.MEMORY, new MemoryHandler(this.modelClient));

    return handlers;
  }

  async executePattern(
    pattern: WorkflowPatternType,
    request: ExecutionRequest,
    config?: any
  ): Promise<ExecutionResponse> {
    const executionId = this.generateExecutionId();
    const startTime = Date.now();

    this.logger.info(`Starting ${pattern} workflow execution`, { executionId });
    this.emit('workflow:start', { executionId, pattern, request });

    try {
      const handler = this.patternHandlers.get(pattern);
      if (!handler) {
        throw new Error(`No handler found for pattern: ${pattern}`);
      }

      const workflow = new WorkflowExecution(executionId, pattern, request, config);
      this.activeWorkflows.set(executionId, workflow);

      const result = await handler.execute(request, config, progress => {
        this.emit('workflow:progress', { executionId, progress });
        workflow.updateProgress(progress);
      });

      const executionTime = Date.now() - startTime;
      const response: ExecutionResponse = {
        success: true,
        result,
        executionTime,
        metadata: {
          pattern,
          executionId,
          ...result.metadata,
        },
      };

      this.recordExecution(executionId, result);
      this.emit('workflow:complete', { executionId, response });

      return response;
    } catch (error: unknown) {
      this.logger.error(`Workflow execution failed`, { executionId, error });
      this.emit('workflow:error', { executionId, error });

      return {
        success: false,
        error: getErrorMessage(error),
        executionTime: Date.now() - startTime,
        metadata: { pattern, executionId },
      };
    } finally {
      this.activeWorkflows.delete(executionId);
    }
  }

  async executeSequentialChain(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.SEQUENTIAL, request);
  }

  async executeParallelAgents(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.PARALLEL, request);
  }

  async executeAdaptiveWorkflow(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.ADAPTIVE, request);
  }

  async executeHierarchicalOrchestration(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.HIERARCHICAL, request);
  }

  async executeWithFeedback(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.FEEDBACK, request);
  }

  async executeIterativeRefinement(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.ITERATIVE, request);
  }

  async executeBranchingLogic(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.BRANCHING, request);
  }

  async executeStreamingWorkflow(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.STREAMING, request);
  }

  async executeWithMemory(request: ExecutionRequest): Promise<ExecutionResponse> {
    return this.executePattern(WorkflowPatternType.MEMORY, request);
  }

  // Utility methods
  private generateExecutionId(): string {
    return `exec_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
  }

  private recordExecution(executionId: string, result: ExecutionResult): void {
    const history = this.executionHistory.get(executionId) || [];
    history.push(result);
    this.executionHistory.set(executionId, history);
  }

  getExecutionHistory(executionId: string): ExecutionResult[] | undefined {
    return this.executionHistory.get(executionId);
  }

  getActiveWorkflows(): WorkflowExecution[] {
    return Array.from(this.activeWorkflows.values());
  }

  cancelWorkflow(executionId: string): boolean {
    const workflow = this.activeWorkflows.get(executionId);
    if (workflow) {
      workflow.cancel();
      this.activeWorkflows.delete(executionId);
      this.emit('workflow:cancelled', { executionId });
      return true;
    }
    return false;
  }
}

// Workflow Execution Class
class WorkflowExecution {
  constructor(
    public id: string,
    public pattern: WorkflowPatternType,
    public request: ExecutionRequest,
    public config: any,
    public startTime: number = Date.now(),
    public status: 'running' | 'completed' | 'failed' | 'cancelled' = 'running',
    public progress: number = 0
  ) {}

  updateProgress(progress: number): void {
    this.progress = Math.min(100, Math.max(0, progress));
  }

  cancel(): void {
    this.status = 'cancelled';
  }
}

// Abstract Pattern Handler
abstract class PatternHandler {
  constructor(protected modelClient: UnifiedModelClient) {}

  abstract execute(
    request: ExecutionRequest,
    config: any,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult>;
}

// Sequential Handler Implementation
class SequentialHandler extends PatternHandler {
  async execute(
    request: ExecutionRequest,
    config: PromptChaining,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const results: any[] = [];
    const context = config?.context || new Map();
    const steps = config?.steps || [];

    for (let i = 0; i < steps.length; i++) {
      const step = steps[i];
      onProgress((i / steps.length) * 100);

      // Check dependencies
      if (step.dependencies) {
        for (const dep of step.dependencies) {
          if (!context.has(dep)) {
            throw new Error(`Missing dependency: ${dep}`);
          }
        }
      }

      // Execute step
      const stepRequest = {
        ...request,
        prompt: this.interpolatePrompt(step.prompt, context),
        voice: step.voice || request.voice,
      };

      const result = await this.modelClient.synthesize(stepRequest);

      // Transform and store result - convert to JsonValue for compatibility
      const jsonResult = modelResponseToJsonValue(result);
      const transformed = step.transform ? step.transform(jsonResult) : jsonResult;
      context.set(step.id, transformed);
      results.push(transformed);
    }

    onProgress(100);

    return {
      success: true,
      content: results,
      metadata: {
        stepsCompleted: steps.length,
        context: Object.fromEntries(context),
      },
    };
  }

  private interpolatePrompt(prompt: string, context: Map<string, any>): string {
    let interpolated = prompt;
    context.forEach((value, key) => {
      interpolated = interpolated.replace(`{{${key}}}`, JSON.stringify(value));
    });
    return interpolated;
  }
}

// Parallel Handler Implementation
class ParallelHandler extends PatternHandler {
  async execute(
    request: ExecutionRequest,
    config: ParallelProcessing,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const tasks = config?.tasks || [];
    const concurrency = config?.concurrency || 5;
    const aggregation = config?.aggregation || 'merge';

    const results = await this.executeWithConcurrency(tasks, concurrency, completed =>
      onProgress((completed / tasks.length) * 100)
    );

    const aggregated = this.aggregateResults(results, aggregation);

    return {
      success: true,
      content: aggregated,
      metadata: {
        tasksCompleted: tasks.length,
        aggregationMethod: aggregation,
      },
    };
  }

  private async executeWithConcurrency(
    tasks: ParallelTask[],
    concurrency: number,
    onTaskComplete: (completed: number) => void
  ): Promise<any[]> {
    const results: any[] = new Array(tasks.length);
    let completed = 0;
    let index = 0;

    const executeTask = async (taskIndex: number) => {
      const task = tasks[taskIndex];
      try {
        const result = await this.modelClient.synthesize(task.request);
        results[taskIndex] = result;
      } catch (error: unknown) {
        results[taskIndex] = { error: getErrorMessage(error) };
      }
      completed++;
      onTaskComplete(completed);
    };

    const promises: Promise<void>[] = [];

    while (index < tasks.length) {
      while (promises.length < concurrency && index < tasks.length) {
        promises.push(executeTask(index));
        index++;
      }

      await Promise.race(promises);
      promises.splice(
        promises.findIndex(p => p),
        1
      );
    }

    await Promise.all(promises);

    return results;
  }

  private aggregateResults(results: any[], method: string): any {
    switch (method) {
      case 'merge':
        return results.flat();
      case 'reduce':
        return results.reduce((acc, curr) => ({ ...acc, ...curr }), {});
      case 'select':
        return results.find(r => r && !r.error) || results[0];
      default:
        return results;
    }
  }
}

// Full Hierarchical Handler Implementation
class HierarchicalHandler extends PatternHandler {
  async execute(
    request: ExecutionRequest,
    config: MultiAgentOrchestration,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const agents = config?.agents || [];
    const coordinator = config?.coordinator || 'coordinator';
    const protocol = config?.communicationProtocol || 'broadcast';

    // Create agent hierarchy
    const agentMap = new Map<string, AgentRole>();
    agents.forEach(agent => agentMap.set(agent.id, agent));

    // Sort agents by priority
    const sortedAgents = agents.sort((a, b) => b.priority - a.priority);

    // Initialize communication channel
    const messageQueue = new MessageQueue(protocol);
    const results = new Map<string, any>();

    // Coordinator processes request first
    onProgress(10);
    const coordinatorRequest = {
      ...request,
      prompt: `As coordinator, analyze and delegate: ${request.prompt}`,
      metadata: { role: 'coordinator' },
    };

    const coordinatorResponse = await this.modelClient.synthesize(coordinatorRequest);
    const delegationPlan = this.parseDelegationPlan(coordinatorResponse);

    // Execute delegated tasks
    let progress = 20;
    for (const delegation of delegationPlan) {
      const agent = agentMap.get(delegation.agentId);
      if (!agent) continue;

      onProgress(progress);

      // Check if agent has required capabilities
      if (!this.hasCapabilities(agent, delegation.requiredCapabilities)) {
        results.set(agent.id, { error: 'Missing capabilities' });
        continue;
      }

      // Execute agent task
      const agentRequest = {
        ...request,
        prompt: delegation.task,
        voice: agent.type,
        metadata: {
          role: agent.type,
          capabilities: agent.capabilities,
        },
      };

      try {
        const agentResult = await this.modelClient.synthesize(agentRequest);
        results.set(agent.id, agentResult);

        // Broadcast results if needed
        if (protocol === 'broadcast') {
          messageQueue.broadcast(agent.id, agentResult);
        }
      } catch (error: unknown) {
        results.set(agent.id, { error: getErrorMessage(error) });
      }

      progress += 60 / delegationPlan.length;
    }

    // Coordinator aggregates results
    onProgress(90);
    const aggregationRequest = {
      ...request,
      prompt: `Aggregate these agent results: ${JSON.stringify(Object.fromEntries(results))}`,
      metadata: { role: 'coordinator', phase: 'aggregation' },
    };

    const finalResult = await this.modelClient.synthesize(aggregationRequest);
    onProgress(100);

    return {
      success: true,
      content: finalResult,
      metadata: {
        pattern: 'hierarchical',
        agentsUsed: results.size,
        protocol,
        results: Object.fromEntries(results),
      },
    };
  }

  private parseDelegationPlan(
    response: any
  ): Array<{ agentId: string; task: string; requiredCapabilities: string[] }> {
    // Parse delegation plan from coordinator response
    // In production, use structured output or JSON mode
    const plan = [];
    const content = response.content || response;

    // Simple parsing - in production use proper NLP or structured output
    const lines = content.split('\n');
    for (const line of lines) {
      if (line.includes('->')) {
        const [agentPart, taskPart] = line.split('->');
        const agentId = agentPart.trim().toLowerCase();
        const task = taskPart.trim();
        plan.push({
          agentId,
          task,
          requiredCapabilities: [],
        });
      }
    }

    return plan.length > 0
      ? plan
      : [{ agentId: 'default', task: 'Process request', requiredCapabilities: [] }];
  }

  private hasCapabilities(agent: AgentRole, required: string[]): boolean {
    return required.every(cap => agent.capabilities.includes(cap));
  }
}

// Message Queue for inter-agent communication
class MessageQueue {
  private messages: Map<string, any[]> = new Map();

  constructor(private protocol: string) {}

  broadcast(from: string, message: any): void {
    if (this.protocol === 'broadcast') {
      // Store message for all agents
      this.messages.set('broadcast', [
        ...(this.messages.get('broadcast') || []),
        { from, message },
      ]);
    }
  }

  send(from: string, to: string, message: any): void {
    if (this.protocol === 'direct') {
      const key = `${from}->${to}`;
      this.messages.set(key, [...(this.messages.get(key) || []), message]);
    }
  }

  getMessages(agentId: string): any[] {
    if (this.protocol === 'broadcast') {
      return this.messages.get('broadcast') || [];
    }
    return [];
  }
}

class AdaptiveHandler extends PatternHandler {
  private executionHistory: any[] = [];
  private currentWorkflow: WorkflowNode[] = [];

  async execute(
    request: ExecutionRequest,
    config: DynamicWorkflow,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const initialPlan = config?.initialPlan || [];
    const adaptationRules = config?.adaptationRules || [];
    const learningRate = config?.learningRate || 0.1;

    this.currentWorkflow = [...initialPlan];
    let currentNodeId = initialPlan[0]?.id || 'start';
    const context = {
      nodeId: currentNodeId,
      request,
      history: [],
      metrics: {
        successRate: 1.0,
        avgLatency: 0,
        adaptations: 0,
      },
    };

    let progress = 0;
    const results = [];

    while (currentNodeId && currentNodeId !== 'end') {
      const node = this.currentWorkflow.find(n => n.id === currentNodeId);
      if (!node) break;

      onProgress(progress);

      // Execute current node
      const nodeResult = await this.executeNode(node, request, context);
      results.push(nodeResult);
      (context.history as any[]).push(nodeResult);

      // Check adaptation rules
      for (const rule of adaptationRules) {
        if (rule.trigger(context, this.executionHistory)) {
          // Apply adaptation
          rule.action({ initialPlan: this.currentWorkflow, adaptationRules, learningRate });
          context.metrics.adaptations++;

          // Re-evaluate current position
          const adaptedNode = this.findBestNode(context, this.currentWorkflow);
          if (adaptedNode) {
            currentNodeId = adaptedNode.id;
            context.nodeId = currentNodeId;
            continue;
          }
        }
      }

      // Determine next node based on transitions
      const nextNode = this.selectNextNode(node, context);
      currentNodeId = nextNode?.id || 'end';
      context.nodeId = currentNodeId;

      // Update metrics
      this.updateMetrics(context, nodeResult);

      // Apply learning
      this.applyLearning(node, nodeResult, learningRate);

      progress = Math.min(90, progress + 90 / initialPlan.length);
    }

    onProgress(100);

    return {
      success: true,
      content: results,
      metadata: {
        pattern: 'adaptive',
        adaptations: context.metrics.adaptations,
        nodesExecuted: results.length,
        finalMetrics: context.metrics,
      },
    };
  }

  private async executeNode(
    node: WorkflowNode,
    request: ExecutionRequest,
    context: any
  ): Promise<any> {
    // Recursively execute workflow patterns
    const orchestrator = new WorkflowOrchestrator(this.modelClient);
    const nodeRequest = {
      ...request,
      prompt: `${request.prompt} [Node: ${node.id}]`,
    };

    const result = await orchestrator.executePattern(node.type, nodeRequest, node.config);

    return {
      nodeId: node.id,
      type: node.type,
      result,
      timestamp: Date.now(),
    };
  }

  private selectNextNode(currentNode: WorkflowNode, context: any): WorkflowNode | null {
    // Evaluate transitions
    for (const transition of currentNode.transitions) {
      if (transition.condition(context)) {
        const nextNode = this.currentWorkflow.find(n => n.id === transition.to);
        if (nextNode) return nextNode;
      }
    }

    // Probabilistic selection if no conditions met
    const validTransitions = currentNode.transitions.filter(t => t.probability);
    if (validTransitions.length > 0) {
      const random = Math.random();
      let cumulative = 0;

      for (const transition of validTransitions) {
        cumulative += transition.probability || 0;
        if (random <= cumulative) {
          return this.currentWorkflow.find(n => n.id === transition.to) || null;
        }
      }
    }

    return null;
  }

  private findBestNode(context: any, workflow: WorkflowNode[]): WorkflowNode | null {
    // Find best node based on current context
    let bestNode = null;
    let bestScore = -Infinity;

    for (const node of workflow) {
      const score = this.scoreNode(node, context);
      if (score > bestScore) {
        bestScore = score;
        bestNode = node;
      }
    }

    return bestNode;
  }

  private scoreNode(node: WorkflowNode, context: any): number {
    // Score node based on context and history
    let score = 0;

    // Prefer unexplored nodes
    const timesExecuted = context.history.filter((h: any) => h.nodeId === node.id).length;
    score -= timesExecuted * 0.5;

    // Consider success rate of similar nodes
    const similarResults = this.executionHistory.filter(h => h.type === node.type);
    if (similarResults.length > 0) {
      const successRate = similarResults.filter(r => r.success).length / similarResults.length;
      score += successRate * 2;
    }

    return score;
  }

  private updateMetrics(context: any, result: any): void {
    const latency = result.result?.executionTime || 0;
    const n = context.history.length;

    context.metrics.avgLatency = (context.metrics.avgLatency * (n - 1) + latency) / n;

    if (result.result?.success) {
      context.metrics.successRate = (context.metrics.successRate * (n - 1) + 1) / n;
    } else {
      context.metrics.successRate = (context.metrics.successRate * (n - 1)) / n;
    }
  }

  private applyLearning(node: WorkflowNode, result: any, learningRate: number): void {
    // Update transition probabilities based on success
    if (result.result?.success) {
      for (const transition of node.transitions) {
        if (transition.probability) {
          transition.probability = Math.min(1, transition.probability * (1 + learningRate));
        }
      }
    }

    // Store in history for future adaptations
    this.executionHistory.push({
      nodeId: node.id,
      type: node.type,
      success: result.result?.success,
      timestamp: Date.now(),
    });
  }
}

class FeedbackHandler extends PatternHandler {
  private feedbackStore: Map<string, any> = new Map();

  async execute(
    request: ExecutionRequest,
    config: HumanInTheLoop,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const checkpoints = config?.checkpoints || [];
    const escalationPolicy = config?.escalationPolicy || {
      maxRetries: 3,
      escalationPath: ['user', 'supervisor', 'admin'],
      fallbackBehavior: 'default',
    };
    const feedbackConfig = config?.feedbackLoop || {
      collectMetrics: true,
      learningEnabled: true,
      persistFeedback: true,
    };

    let result = await this.modelClient.synthesize(request);
    let jsonResult = modelResponseToJsonValue(result);
    let finalResult = result;
    const checkpointsPassed = [];
    const feedbackCollected = [];
    let retryCount = 0;

    onProgress(20);

    // Check each checkpoint
    for (let i = 0; i < checkpoints.length; i++) {
      const checkpoint = checkpoints[i];
      onProgress(20 + (i / checkpoints.length) * 60);

      if (checkpoint.condition(jsonResult)) {
        // Checkpoint triggered - request human feedback
        const feedback = await this.requestHumanFeedback(
          checkpoint,
          result,
          escalationPolicy,
          retryCount
        );

        if (feedback.action === 'approve') {
          checkpointsPassed.push(checkpoint.id);
          continue;
        } else if (feedback.action === 'reject') {
          // Retry with feedback
          if (retryCount < escalationPolicy.maxRetries) {
            const improvedRequest = {
              ...request,
              prompt: `${request.prompt}\n\nFeedback: ${feedback.message}\nPlease improve based on this feedback.`,
            };

            result = await this.modelClient.synthesize(improvedRequest);
            jsonResult = modelResponseToJsonValue(result);
            retryCount++;
            i--; // Re-check same checkpoint
          } else {
            // Max retries reached - escalate or fallback
            result = await this.handleEscalation(request, result, escalationPolicy, feedback);
            jsonResult = modelResponseToJsonValue(result);
          }
        } else if (feedback.action === 'modify') {
          // Direct modification
          result = {
            ...result,
            content: feedback.modifiedContent || result.content,
          };
        }

        feedbackCollected.push(feedback);

        // Learn from feedback if enabled
        if (feedbackConfig.learningEnabled) {
          await this.learnFromFeedback(checkpoint, feedback, result);
        }
      }
    }

    // Collect final metrics
    if (feedbackConfig.collectMetrics) {
      const metrics = this.collectMetrics(feedbackCollected, checkpointsPassed);

      if (feedbackConfig.persistFeedback) {
        this.persistFeedback(request, feedbackCollected, metrics);
      }

      finalResult = {
        ...result,
        metadata: {
          tokens: result.metadata?.tokens || 0,
          latency: result.metadata?.latency || 0,
          quality: result.metadata?.quality,
          feedbackMetrics: metrics,
        } as any,
      };
    }

    onProgress(100);

    return {
      success: true,
      content: finalResult,
      metadata: {
        pattern: 'feedback',
        checkpointsPassed: checkpointsPassed.length,
        feedbackCollected: feedbackCollected.length,
        retries: retryCount,
        metrics: feedbackConfig.collectMetrics
          ? this.collectMetrics(feedbackCollected, checkpointsPassed)
          : undefined,
      },
    };
  }

  private async requestHumanFeedback(
    checkpoint: Checkpoint,
    result: any,
    policy: EscalationPolicy,
    retryCount: number
  ): Promise<any> {
    // In production, this would integrate with a UI or messaging system
    // For now, simulate feedback based on quality
    const quality = result.metadata?.quality || Math.random();

    // Simulate timeout
    await new Promise(resolve => setTimeout(resolve, Math.min(checkpoint.timeout, 100)));

    if (quality > 0.8) {
      return {
        action: 'approve',
        message: 'Quality threshold met',
        timestamp: Date.now(),
      };
    } else if (quality > 0.5) {
      return {
        action: 'modify',
        message: 'Minor improvements needed',
        modifiedContent: `${result.content} [Improved]`,
        timestamp: Date.now(),
      };
    } else {
      return {
        action: 'reject',
        message: 'Significant improvements required',
        suggestions: ['Add more detail', 'Improve clarity', 'Check accuracy'],
        timestamp: Date.now(),
      };
    }
  }

  private async handleEscalation(
    request: ExecutionRequest,
    result: any,
    policy: EscalationPolicy,
    feedback: any
  ): Promise<any> {
    // Escalate through the chain
    for (const escalationLevel of policy.escalationPath) {
      const escalatedFeedback = await this.requestEscalatedFeedback(
        escalationLevel,
        request,
        result,
        feedback
      );

      if (escalatedFeedback.resolution) {
        return escalatedFeedback.result;
      }
    }

    // Apply fallback behavior
    switch (policy.fallbackBehavior) {
      case 'skip':
        return result;
      case 'default':
        return { ...result, content: 'Default response due to escalation failure' };
      case 'abort':
        throw new Error('Escalation failed - aborting');
      default:
        return result;
    }
  }

  private async requestEscalatedFeedback(
    level: string,
    request: ExecutionRequest,
    result: any,
    feedback: any
  ): Promise<any> {
    // Simulate escalated feedback
    return {
      resolution: Math.random() > 0.5,
      result: {
        ...result,
        content: `${result.content} [Resolved by ${level}]`,
      },
    };
  }

  private async learnFromFeedback(
    checkpoint: Checkpoint,
    feedback: any,
    result: any
  ): Promise<void> {
    // Store feedback for learning
    const key = `${checkpoint.id}_feedback`;
    const history = this.feedbackStore.get(key) || [];
    history.push({
      feedback,
      result,
      timestamp: Date.now(),
    });
    this.feedbackStore.set(key, history);

    // Adjust checkpoint conditions based on feedback patterns
    // This would be more sophisticated in production
  }

  private collectMetrics(feedbackCollected: any[], checkpointsPassed: string[]): any {
    return {
      totalFeedback: feedbackCollected.length,
      approvalRate:
        feedbackCollected.filter(f => f.action === 'approve').length / feedbackCollected.length,
      modificationRate:
        feedbackCollected.filter(f => f.action === 'modify').length / feedbackCollected.length,
      rejectionRate:
        feedbackCollected.filter(f => f.action === 'reject').length / feedbackCollected.length,
      checkpointsPassedRate:
        checkpointsPassed.length / (checkpointsPassed.length + feedbackCollected.length),
      avgResponseTime:
        feedbackCollected.reduce((sum, f) => sum + (f.timestamp || 0), 0) /
        feedbackCollected.length,
    };
  }

  private persistFeedback(request: ExecutionRequest, feedback: any[], metrics: any): void {
    // Store feedback for future analysis
    const sessionId = `session_${Date.now()}`;
    this.feedbackStore.set(sessionId, {
      request,
      feedback,
      metrics,
      timestamp: Date.now(),
    });
  }
}

class IterativeHandler extends PatternHandler {
  async execute(
    request: ExecutionRequest,
    config: ReflectiveRefinement,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const maxIterations = config?.maxIterations || 3;
    const qualityThreshold = config?.qualityThreshold || 0.85;
    const strategy = config?.refinementStrategy || 'improve';
    const criteria = config?.evaluationCriteria || [
      { name: 'accuracy', weight: 0.4, evaluate: r => r.metadata?.accuracy || 0.7 },
      { name: 'completeness', weight: 0.3, evaluate: r => r.metadata?.completeness || 0.7 },
      { name: 'clarity', weight: 0.3, evaluate: r => r.metadata?.clarity || 0.7 },
    ];

    let currentResult = await this.modelClient.synthesize(request);
    let bestResult = currentResult;
    let bestQuality = this.evaluateQuality(currentResult, criteria);
    const iterations = [];

    onProgress(20);

    for (let i = 0; i < maxIterations; i++) {
      const currentQuality = this.evaluateQuality(currentResult, criteria);

      iterations.push({
        iteration: i + 1,
        quality: currentQuality,
        result: currentResult,
      });

      // Check if quality threshold is met
      if (currentQuality >= qualityThreshold) {
        bestResult = currentResult;
        bestQuality = currentQuality;
        break;
      }

      onProgress(20 + (i / maxIterations) * 60);

      // Apply refinement strategy
      const refinementRequest = this.createRefinementRequest(
        request,
        currentResult,
        strategy,
        criteria,
        currentQuality
      );

      const refinedResult = await this.modelClient.synthesize(refinementRequest);
      const refinedQuality = this.evaluateQuality(refinedResult, criteria);

      // Keep best result
      if (refinedQuality > bestQuality) {
        bestResult = refinedResult;
        bestQuality = refinedQuality;
      }

      // Decide whether to continue from refined or try alternative approach
      if (refinedQuality > currentQuality || strategy === 'regenerate') {
        currentResult = refinedResult;
      } else if (strategy === 'critique') {
        // Get critique and incorporate
        const critiqueRequest = {
          ...request,
          prompt: `Critique this response and suggest improvements: ${currentResult.content}`,
        };
        const critique = await this.modelClient.synthesize(critiqueRequest);

        currentResult = {
          ...currentResult,
          content: `${currentResult.content}\n\nCritique: ${critique.content}`,
        };
      }
    }

    // Final evaluation
    const finalEvaluation = this.performFinalEvaluation(bestResult, criteria, iterations);

    onProgress(100);

    return {
      success: bestQuality >= qualityThreshold,
      content: bestResult,
      metadata: {
        pattern: 'iterative',
        iterations: iterations.length,
        finalQuality: bestQuality,
        qualityThreshold,
        strategy,
        evaluation: finalEvaluation,
        improvements: this.calculateImprovements(iterations),
      },
    };
  }

  private evaluateQuality(result: any, criteria: EvaluationCriteria[]): number {
    let totalScore = 0;
    let totalWeight = 0;

    for (const criterion of criteria) {
      const score = criterion.evaluate(result);
      totalScore += score * criterion.weight;
      totalWeight += criterion.weight;
    }

    return totalWeight > 0 ? totalScore / totalWeight : 0;
  }

  private createRefinementRequest(
    originalRequest: ExecutionRequest,
    currentResult: any,
    strategy: string,
    criteria: EvaluationCriteria[],
    currentQuality: number
  ): ExecutionRequest {
    const weakestCriterion = this.findWeakestCriterion(currentResult, criteria);

    let refinementPrompt = originalRequest.prompt;

    switch (strategy) {
      case 'improve':
        refinementPrompt = `Improve this response, especially regarding ${weakestCriterion.name}:\n\nOriginal: ${currentResult.content}\n\nFocus on: ${weakestCriterion.name}`;
        break;
      case 'critique':
        refinementPrompt = `Critically analyze and rewrite:\n\n${currentResult.content}\n\nCurrent quality: ${currentQuality}. Must exceed: ${currentQuality + 0.1}`;
        break;
      case 'regenerate':
        refinementPrompt = `${originalRequest.prompt}\n\nPrevious attempt (quality: ${currentQuality}) needs improvement in ${weakestCriterion.name}. Generate a better response.`;
        break;
    }

    return {
      ...originalRequest,
      prompt: refinementPrompt,
      metadata: {
        ...originalRequest.metadata,
        refinementIteration: true,
        targetImprovement: weakestCriterion.name,
      },
    };
  }

  private findWeakestCriterion(result: any, criteria: EvaluationCriteria[]): EvaluationCriteria {
    let weakest = criteria[0];
    let weakestScore = weakest.evaluate(result);

    for (const criterion of criteria) {
      const score = criterion.evaluate(result);
      if (score < weakestScore) {
        weakest = criterion;
        weakestScore = score;
      }
    }

    return weakest;
  }

  private performFinalEvaluation(
    result: any,
    criteria: EvaluationCriteria[],
    iterations: any[]
  ): any {
    return {
      criteria: criteria.map(c => ({
        name: c.name,
        weight: c.weight,
        score: c.evaluate(result),
      })),
      convergence: this.calculateConvergence(iterations),
      efficiency: iterations.length > 0 ? iterations[0].quality / iterations.length : 0,
    };
  }

  private calculateConvergence(iterations: any[]): number {
    if (iterations.length < 2) return 1;

    const improvements = [];
    for (let i = 1; i < iterations.length; i++) {
      improvements.push(iterations[i].quality - iterations[i - 1].quality);
    }

    const avgImprovement = improvements.reduce((a, b) => a + b, 0) / improvements.length;
    return Math.max(0, Math.min(1, avgImprovement * 10));
  }

  private calculateImprovements(iterations: any[]): any[] {
    const improvements = [];

    for (let i = 1; i < iterations.length; i++) {
      improvements.push({
        from: i,
        to: i + 1,
        qualityDelta: iterations[i].quality - iterations[i - 1].quality,
        percentImprovement:
          ((iterations[i].quality - iterations[i - 1].quality) / iterations[i - 1].quality) * 100,
      });
    }

    return improvements;
  }
}

class BranchingHandler extends PatternHandler {
  async execute(
    request: ExecutionRequest,
    config: ConditionalExecution,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const branches = config?.branches || [];
    const defaultBranch = config?.defaultBranch;
    const evaluationOrder = config?.evaluationOrder || 'sequential';

    const context = {
      request,
      timestamp: Date.now(),
      environment: process.env,
      previousResults: [],
    };

    onProgress(10);

    // Sort branches by priority
    const sortedBranches = branches.sort((a, b) => b.priority - a.priority);

    let selectedBranch = null;
    let evaluationResults = [];

    if (evaluationOrder === 'sequential') {
      // Evaluate branches sequentially
      for (const branch of sortedBranches) {
        onProgress(10 + (sortedBranches.indexOf(branch) / sortedBranches.length) * 30);

        const evaluation = await this.evaluateBranch(branch, context);
        evaluationResults.push(evaluation);

        if (evaluation.matches) {
          selectedBranch = branch;
          break;
        }
      }
    } else {
      // Evaluate branches in parallel
      const evaluations = await Promise.all(
        sortedBranches.map(branch => this.evaluateBranch(branch, context))
      );

      evaluationResults = evaluations;

      // Find first matching branch (already sorted by priority)
      for (let i = 0; i < sortedBranches.length; i++) {
        if (evaluations[i].matches) {
          selectedBranch = sortedBranches[i];
          break;
        }
      }

      onProgress(40);
    }

    // Use default branch if no conditions matched
    if (!selectedBranch && defaultBranch) {
      selectedBranch = branches.find(b => b.id === defaultBranch);
    }

    if (!selectedBranch) {
      return {
        success: false,
        content: 'No branch conditions matched and no default branch specified',
        metadata: {
          pattern: 'branching',
          evaluationResults,
        },
      };
    }

    onProgress(50);

    // Execute selected branch workflow
    const branchResult = await this.executeBranchWorkflow(
      selectedBranch.workflow,
      request,
      progress => onProgress(50 + progress * 0.4)
    );

    onProgress(100);

    return {
      success: true,
      content: branchResult,
      metadata: {
        pattern: 'branching',
        selectedBranch: selectedBranch.id,
        evaluationOrder,
        evaluationResults,
        branchMetadata: branchResult.metadata,
      },
    };
  }

  private async evaluateBranch(
    branch: Branch,
    context: any
  ): Promise<{ branchId: string; matches: boolean; evaluation: any }> {
    try {
      // Evaluate condition
      const matches = branch.condition(context);

      // For complex conditions, we might want to use the model
      if (typeof branch.condition === 'string') {
        const evaluationRequest = {
          prompt: `Evaluate if this condition is true: ${branch.condition}\nContext: ${JSON.stringify(context)}`,
          maxTokens: 10,
        };

        const result = await this.modelClient.synthesize(evaluationRequest);
        const evaluation = result.content.toLowerCase().includes('true');

        return {
          branchId: branch.id,
          matches: evaluation,
          evaluation: result.content,
        };
      }

      return {
        branchId: branch.id,
        matches,
        evaluation: matches ? 'Condition met' : 'Condition not met',
      };
    } catch (error: unknown) {
      return {
        branchId: branch.id,
        matches: false,
        evaluation: `Error: ${getErrorMessage(error)}`,
      };
    }
  }

  private async executeBranchWorkflow(
    workflow: WorkflowNode,
    request: ExecutionRequest,
    onProgress: (progress: number) => void
  ): Promise<any> {
    // Execute the workflow associated with the branch
    const orchestrator = new WorkflowOrchestrator(this.modelClient);

    return await orchestrator.executePattern(workflow.type, request, workflow.config);
  }
}

class StreamingHandler extends PatternHandler {
  private streamBuffer: any[] = [];
  private processedChunks: any[] = [];

  async execute(
    request: ExecutionRequest,
    config: RealTimeProcessing,
    onProgress: (progress: number) => void
  ): Promise<ExecutionResult> {
    const streamingEnabled = config?.streamingEnabled !== false;
    const chunkSize = config?.chunkSize || 100;
    const bufferStrategy = config?.bufferStrategy || 'sliding';
    const onChunk = config?.onChunk || (chunk => {});

    if (!streamingEnabled) {
      // Non-streaming execution
      const result = await this.modelClient.synthesize(request);
      onProgress(100);
      return {
        success: true,
        content: result,
        metadata: { pattern: 'streaming', streamed: false },
      };
    }

    // Initialize buffer based on strategy
    const buffer = this.createBuffer(bufferStrategy, chunkSize * 10);

    // Create streaming request
    const streamRequest = {
      ...request,
      stream: true,
    };

    onProgress(10);

    try {
      // Get stream from model
      const streamResponse = await this.modelClient.streamRequest(
        streamRequest,
        token => {
          // Process streaming token
          if (token.content) {
            buffer.add(token.content);
          }
        },
        { workingDirectory: '.', config: {}, files: [] }
      );

      let totalChunks = 0;
      let accumulatedContent = '';
      const startTime = Date.now();

      // The streaming is handled by the onToken callback above
      // streamResponse contains the final result
      totalChunks = 1;
      accumulatedContent = streamResponse.content || '';

      // Process final result
      const processed = await this.processChunk(accumulatedContent, buffer, config);
      this.processedChunks.push(processed);

      // Call chunk handler
      onChunk(processed);

      // Update progress
      const estimatedProgress = Math.min(90, 10 + totalChunks * 2);
      onProgress(estimatedProgress);

      // Apply backpressure if needed
      if (buffer.isFull()) {
        await this.applyBackpressure(buffer);
      }

      // Final processing
      const finalResult = await this.finalizeStream(
        accumulatedContent,
        this.processedChunks,
        buffer
      );

      onProgress(100);

      return {
        success: true,
        content: finalResult,
        metadata: {
          pattern: 'streaming',
          streamed: true,
          totalChunks,
          bufferStrategy,
          processingTime: Date.now() - startTime,
          averageChunkSize: accumulatedContent.length / totalChunks,
          bufferStats: buffer.getStats(),
        },
      };
    } catch (error: unknown) {
      return {
        success: false,
        content: `Streaming error: ${getErrorMessage(error)}`,
        metadata: {
          pattern: 'streaming',
          error: getErrorMessage(error),
          chunksProcessed: this.processedChunks.length,
        },
      };
    }
  }

  private createBuffer(strategy: string, maxSize: number): StreamBuffer {
    switch (strategy) {
      case 'window':
        return new WindowBuffer(maxSize);
      case 'sliding':
        return new SlidingBuffer(maxSize);
      case 'circular':
        return new CircularBuffer(maxSize);
      default:
        return new SlidingBuffer(maxSize);
    }
  }

  private async processChunk(
    chunk: any,
    buffer: StreamBuffer,
    config: RealTimeProcessing
  ): Promise<any> {
    // Process individual chunk
    const processed = {
      content: chunk.text || chunk.content || chunk,
      timestamp: Date.now(),
      size: JSON.stringify(chunk).length,
      metadata: chunk.metadata || {},
    };

    // Apply any transformations
    if (config.transform) {
      processed.content = config.transform(processed.content);
    }

    return processed;
  }

  private async applyBackpressure(buffer: StreamBuffer): Promise<void> {
    // Wait for buffer to have space
    const waitTime = Math.min(100, buffer.size() / 10);
    await new Promise(resolve => setTimeout(resolve, waitTime));

    // Process some items from buffer
    const toProcess = Math.min(10, buffer.size() / 4);
    for (let i = 0; i < toProcess; i