# Orchestrator Mode Workflow

## Overview

The Orchestrator mode serves as the central coordination hub for the SAFLA-aiGI integrated system. It manages complex multi-mode workflows, coordinates agent interactions, and ensures optimal resource utilization through meta-cognitive decision making.

## Core Workflow Phases

### 1. Initialization Phase

#### System State Assessment
```typescript
async function initializeOrchestration(request: OrchestrationRequest) {
  // Gather comprehensive system state
  const systemState = await gatherSystemState();
  
  // Analyze current goals and priorities
  const activeGoals = await analyzeActiveGoals(systemState.goals);
  
  // Select optimal strategy for the request
  const strategy = await selectOptimalStrategy(request.context, activeGoals);
  
  // Initialize meta-cognitive monitoring
  const cognitiveMonitor = await initializeCognitiveMonitoring(strategy);
  
  return {
    systemState,
    activeGoals,
    strategy,
    cognitiveMonitor
  };
}
```

#### Agent Provisioning
```typescript
async function provisionAgents(strategy: Strategy, requirements: Requirements) {
  // Determine required agent types based on strategy
  const agentRequirements = analyzeAgentRequirements(strategy, requirements);
  
  // Create specialized agent sessions
  const agents = await Promise.all(
    agentRequirements.map(req => createAgentSession(req))
  );
  
  // Establish inter-agent communication channels
  const communicationChannels = await establishAgentCommunication(agents);
  
  // Configure agent coordination protocols
  const coordinationProtocols = await configureCoordination(agents, strategy);
  
  return {
    agents,
    communicationChannels,
    coordinationProtocols
  };
}
```

### 2. Execution Phase

#### Workflow Orchestration
```typescript
async function executeWorkflow(workflow: Workflow, agents: Agent[], strategy: Strategy) {
  const executionContext = {
    workflow,
    agents,
    strategy,
    startTime: Date.now(),
    metrics: new MetricsCollector()
  };
  
  try {
    // Execute workflow phases sequentially with monitoring
    for (const phase of workflow.phases) {
      await executePhase(phase, executionContext);
    }
    
    // Validate workflow completion
    const validation = await validateWorkflowCompletion(executionContext);
    
    return {
      success: true,
      result: validation.result,
      metrics: executionContext.metrics.getMetrics()
    };
    
  } catch (error) {
    return await handleWorkflowError(error, executionContext);
  }
}
```

#### Phase Execution with Adaptive Learning
```typescript
async function executePhase(phase: WorkflowPhase, context: ExecutionContext) {
  // Pre-phase analysis and optimization
  const phaseStrategy = await optimizePhaseStrategy(phase, context);
  
  // Execute phase with real-time monitoring
  const phaseResult = await executePhaseWithMonitoring(phase, phaseStrategy, context);
  
  // Learn from phase execution
  await updateLearningFromPhase(phase, phaseResult, context);
  
  // Adapt strategy for next phase if needed
  await adaptStrategyBasedOnLearning(phaseResult, context);
  
  return phaseResult;
}
```

### 3. Monitoring and Adaptation Phase

#### Real-Time Monitoring
```typescript
async function continuousMonitoring(context: ExecutionContext) {
  const monitoringLoop = setInterval(async () => {
    try {
      // Collect real-time metrics
      const currentMetrics = await collectCurrentMetrics(context);
      
      // Analyze performance against baselines
      const performanceAnalysis = await analyzePerformance(currentMetrics);
      
      // Detect anomalies or degradation
      const anomalies = await detectAnomalies(performanceAnalysis);
      
      if (anomalies.length > 0) {
        await handleAnomalies(anomalies, context);
      }
      
      // Update meta-cognitive state
      await updateMetaCognitiveState(currentMetrics, performanceAnalysis);
      
    } catch (error) {
      console.error('Monitoring error:', error);
      await handleMonitoringError(error, context);
    }
  }, 10000); // Monitor every 10 seconds
  
  return monitoringLoop;
}
```

#### Adaptive Strategy Adjustment
```typescript
async function adaptiveStrategyAdjustment(context: ExecutionContext) {
  // Analyze current strategy effectiveness
  const effectiveness = await analyzeStrategyEffectiveness(context.strategy);
  
  if (effectiveness.score < context.strategy.minEffectiveness) {
    // Trigger strategy adaptation
    const adaptedStrategy = await adaptStrategy(context.strategy, effectiveness);
    
    // Update execution context
    context.strategy = adaptedStrategy;
    
    // Notify agents of strategy change
    await notifyAgentsOfStrategyChange(context.agents, adaptedStrategy);
    
    // Log adaptation for learning
    await logStrategyAdaptation(context.strategy, adaptedStrategy, effectiveness);
  }
}
```

## Mode Coordination Workflows

### Sequential Mode Execution
```typescript
async function executeSequentialModes(modeSequence: ModeDefinition[], context: any) {
  const results = [];
  let currentContext = context;
  
  for (const mode of modeSequence) {
    try {
      // Prepare mode-specific context
      const modeContext = await prepareModeContext(mode, currentContext);
      
      // Execute mode with monitoring
      const modeResult = await executeModeWithMonitoring(mode, modeContext);
      
      // Validate mode completion
      await validateModeCompletion(mode, modeResult);
      
      // Update context for next mode
      currentContext = await updateContextFromResult(currentContext, modeResult);
      
      results.push(modeResult);
      
    } catch (error) {
      return await handleModeExecutionError(error, mode, currentContext);
    }
  }
  
  return {
    success: true,
    results,
    finalContext: currentContext
  };
}
```

### Parallel Mode Execution
```typescript
async function executeParallelModes(modes: ModeDefinition[], context: any) {
  // Create isolated contexts for each mode
  const modeContexts = await Promise.all(
    modes.map(mode => prepareModeContext(mode, context))
  );
  
  // Execute modes in parallel with coordination
  const modePromises = modes.map((mode, index) => 
    executeModeWithCoordination(mode, modeContexts[index], modes)
  );
  
  try {
    const results = await Promise.all(modePromises);
    
    // Merge results and resolve conflicts
    const mergedResult = await mergeParallelResults(results, modes);
    
    return {
      success: true,
      result: mergedResult,
      individualResults: results
    };
    
  } catch (error) {
    return await handleParallelExecutionError(error, modes, modeContexts);
  }
}
```

## Agent Coordination Patterns

### Master-Worker Pattern
```typescript
async function masterWorkerCoordination(masterAgent: Agent, workerAgents: Agent[], task: Task) {
  // Master agent analyzes and distributes work
  const workDistribution = await masterAgent.analyzeAndDistribute(task);
  
  // Workers execute assigned subtasks
  const workerPromises = workerAgents.map((worker, index) =>
    worker.executeSubtask(workDistribution.subtasks[index])
  );
  
  // Master monitors worker progress
  const progressMonitor = await masterAgent.monitorWorkerProgress(workerPromises);
  
  // Collect and integrate results
  const workerResults = await Promise.all(workerPromises);
  const integratedResult = await masterAgent.integrateResults(workerResults);
  
  return integratedResult;
}
```

### Peer-to-Peer Coordination
```typescript
async function peerToPeerCoordination(agents: Agent[], task: Task) {
  // Establish consensus on task approach
  const consensus = await establishConsensus(agents, task);
  
  // Each agent contributes to different aspects
  const contributions = await Promise.all(
    agents.map(agent => agent.contribute(task, consensus))
  );
  
  // Collaborative result integration
  const collaborativeResult = await collaborativeIntegration(contributions, agents);
  
  return collaborativeResult;
}
```

## Error Handling and Recovery

### Graceful Degradation
```typescript
async function gracefulDegradation(error: Error, context: ExecutionContext) {
  // Assess error severity and impact
  const errorAnalysis = await analyzeError(error, context);
  
  if (errorAnalysis.severity === 'critical') {
    // Attempt system recovery
    return await attemptSystemRecovery(error, context);
  } else if (errorAnalysis.severity === 'moderate') {
    // Reduce functionality and continue
    return await reduceAndContinue(error, context);
  } else {
    // Log and continue with minimal impact
    await logAndContinue(error, context);
    return { success: true, degraded: true };
  }
}
```

### Automatic Recovery
```typescript
async function automaticRecovery(failure: Failure, context: ExecutionContext) {
  const recoveryStrategies = [
    () => retryWithBackoff(failure, context),
    () => fallbackToAlternativeStrategy(failure, context),
    () => redistributeToHealthyAgents(failure, context),
    () => rollbackToLastKnownGoodState(failure, context)
  ];
  
  for (const strategy of recoveryStrategies) {
    try {
      const result = await strategy();
      if (result.success) {
        await logSuccessfulRecovery(failure, strategy, result);
        return result;
      }
    } catch (recoveryError) {
      console.warn('Recovery strategy failed:', recoveryError);
    }
  }
  
  // All recovery strategies failed
  throw new Error('Automatic recovery failed for: ' + failure.message);
}
```

## Learning and Optimization Workflows

### Continuous Learning Integration
```typescript
async function continuousLearning(context: ExecutionContext) {
  // Collect learning data from execution
  const learningData = await collectLearningData(context);
  
  // Trigger incremental learning cycle
  await triggerLearningCycle({
    type: 'incremental',
    data: learningData,
    focus: ['performance', 'quality', 'efficiency']
  });
  
  // Update strategies based on learning
  const updatedStrategies = await updateStrategiesFromLearning(learningData);
  
  // Apply learned optimizations
  await applyLearnedOptimizations(updatedStrategies, context);
}
```

### Performance Optimization Loop
```typescript
async function performanceOptimizationLoop(context: ExecutionContext) {
  const optimizationCycle = setInterval(async () => {
    try {
      // Analyze current performance
      const performanceMetrics = await analyzeCurrentPerformance(context);
      
      // Generate optimization recommendations
      const recommendations = await generateOptimizationRecommendations(performanceMetrics);
      
      // Apply safe optimizations automatically
      const safeOptimizations = recommendations.filter(r => r.risk === 'low');
      await applySafeOptimizations(safeOptimizations, context);
      
      // Queue risky optimizations for review
      const riskyOptimizations = recommendations.filter(r => r.risk !== 'low');
      await queueForReview(riskyOptimizations);
      
    } catch (error) {
      console.error('Optimization loop error:', error);
    }
  }, 60000); // Optimize every minute
  
  return optimizationCycle;
}
```

## Workflow Completion and Handoff

### Result Validation and Quality Assurance
```typescript
async function validateAndQualityAssure(result: any, context: ExecutionContext) {
  // Comprehensive result validation
  const validation = await comprehensiveValidation(result, context);
  
  if (!validation.isValid) {
    // Attempt automatic correction
    const correctedResult = await attemptAutoCorrection(result, validation.issues);
    
    if (correctedResult.success) {
      result = correctedResult.result;
    } else {
      throw new Error('Result validation failed: ' + validation.issues.join(', '));
    }
  }
  
  // Quality assurance checks
  const qualityCheck = await performQualityAssurance(result, context);
  
  return {
    result,
    validation,
    qualityCheck
  };
}
```

### Workflow Handoff
```typescript
async function handoffToNextPhase(result: any, nextPhase: WorkflowPhase, context: ExecutionContext) {
  // Prepare handoff package
  const handoffPackage = await prepareHandoffPackage(result, context);
  
  // Update system state for next phase
  await updateSystemStateForHandoff(handoffPackage, nextPhase);
  
  // Notify relevant agents and systems
  await notifyHandoff(handoffPackage, nextPhase);
  
  // Log handoff for audit trail
  await logWorkflowHandoff(context.workflow, nextPhase, handoffPackage);
  
  return handoffPackage;
}
```

## Integration Points

### External System Integration
```typescript
async function integrateWithExternalSystems(context: ExecutionContext) {
  // Identify required external integrations
  const integrations = await identifyRequiredIntegrations(context);
  
  // Establish secure connections
  const connections = await establishSecureConnections(integrations);
  
  // Synchronize data and state
  await synchronizeWithExternalSystems(connections, context);
  
  // Monitor integration health
  const healthMonitor = await monitorIntegrationHealth(connections);
  
  return {
    connections,
    healthMonitor
  };
}
```

### MCP Server Coordination
```typescript
async function coordinateWithMCPServers(context: ExecutionContext) {
  // Discover available MCP servers
  const mcpServers = await discoverMCPServers();
  
  // Coordinate tool usage across servers
  const toolCoordination = await coordinateToolUsage(mcpServers, context);
  
  // Load balance requests across servers
  const loadBalancer = await setupMCPLoadBalancing(mcpServers);
  
  // Monitor MCP server health and performance
  const mcpMonitor = await monitorMCPServers(mcpServers);
  
  return {
    mcpServers,
    toolCoordination,
    loadBalancer,
    mcpMonitor
  };
}