Agent Orchestration

A2A enables powerful orchestration capabilities for coordinating multiple agents to solve complex tasks. This guide covers the key orchestration patterns and implementation considerations.

Understanding Agent Orchestration

Agent orchestration refers to the coordination of multiple specialized agents to collaboratively accomplish tasks that would be difficult for a single agent. With A2A, you can create sophisticated workflows where agents:

Work simultaneously on different aspects of a problem
Build on each other's outputs in sequence
Provide specialized capabilities as needed
Maintain shared context across interactions

Orchestration Patterns

Sequential Chaining

In sequential chaining, output from one agent becomes input for the next in a predefined sequence.

// Example: Research → Planning → Content Generation → Review
async function sequentialOrchestration(query: string) {
  const researchAgent = new A2AClient("research-agent");
  const plannerAgent = new A2AClient("planning-agent");
  const writerAgent = new A2AClient("writing-agent");
  
  // Step 1: Research phase
  const researchResult = await researchAgent.createTask({
    input: { query }
  });
  
  // Step 2: Planning phase using research
  const planResult = await plannerAgent.createTask({
    input: { 
      query,
      research: researchResult.output.research
    }
  });
  
  // Step 3: Writing phase using plan
  const contentResult = await writerAgent.createTask({
    input: {
      query,
      plan: planResult.output.outline,
      research: researchResult.output.research
    }
  });
  
  return contentResult;
}

Parallel Processing

Multiple agents work simultaneously on different aspects of a task, with results combined later.

// Example: Simultaneous research from multiple sources
async function parallelOrchestration(query: string) {
  const academicAgent = new A2AClient("academic-research");
  const newsAgent = new A2AClient("news-research");
  const socialAgent = new A2AClient("social-trends");
  const synthesisAgent = new A2AClient("synthesis-agent");
  
  // Launch parallel tasks
  const [academicResults, newsResults, socialResults] = await Promise.all([
    academicAgent.createTask({ input: { query, source: "academic" }}),
    newsAgent.createTask({ input: { query, source: "news" }}),
    socialAgent.createTask({ input: { query, source: "social" }})
  ]);
  
  // Synthesize parallel results
  const finalResult = await synthesisAgent.createTask({
    input: {
      query,
      academicData: academicResults.output,
      newsData: newsResults.output,
      socialData: socialResults.output
    }
  });
  
  return finalResult;
}

Adaptive Routing

Tasks are dynamically routed to specialized agents based on content or requirements.

// Example: Route to appropriate specialist based on query type
async function adaptiveOrchestration(query: string) {
  const routerAgent = new A2AClient("router-agent");
  
  // Determine appropriate specialist
  const routingResult = await routerAgent.createTask({
    input: { query }
  });
  
  // Connect to the recommended specialist
  const specialistId = routingResult.output.recommendedAgent;
  const specialistAgent = new A2AClient(specialistId);
  
  // Process with the specialist
  const result = await specialistAgent.createTask({
    input: { 
      query,
      context: routingResult.output.context
    }
  });
  
  return result;
}

Recursive Decomposition

Complex tasks are broken down into subtasks that are recursively processed.

// Example: Break complex task into manageable components
async function recursiveOrchestration(task: any, depth = 0) {
  if (depth > 3) return { result: "Max depth reached" };
  
  const plannerAgent = new A2AClient("planner-agent");
  const solverAgent = new A2AClient("solver-agent");
  
  // Analyze task complexity
  const planResult = await plannerAgent.createTask({
    input: { task }
  });
  
  if (planResult.output.isSimple) {
    // Direct solution for simple tasks
    return solverAgent.createTask({
      input: { task, plan: planResult.output.approach }
    });
  } else {
    // Break down complex tasks
    const subResults = await Promise.all(
      planResult.output.subtasks.map(subtask => 
        recursiveOrchestration(subtask, depth + 1)
      )
    );
    
    // Combine subtask results
    return solverAgent.createTask({
      input: { 
        task,
        subtaskResults: subResults.map(r => r.output),
        plan: planResult.output.integrationPlan
      }
    });
  }
}

Implementing Orchestration

State Management

Effective orchestration requires managing state across agent interactions:

Task Contexts: Pass context between agents for continuity
External State: Use databases or key-value stores for persistent state
Memory Systems: Implement short and long-term memory for agents

Error Handling

Robust orchestration includes strategies for handling failures:

Retry Logic: Attempt failed operations with exponential backoff
Fallback Agents: Designate alternative agents for critical functions
Circuit Breakers: Prevent cascading failures when services degrade

Monitoring and Observability

Track orchestration performance:

Trace IDs: Propagate identifiers across agent calls
Execution Graphs: Visualize the flow of tasks between agents
Timeout Management: Handle long-running operations appropriately

Advanced Orchestration Techniques

Human-in-the-Loop

Incorporate human expertise at strategic points:

async function humanAugmentedOrchestration(query: string) {
  const draftAgent = new A2AClient("draft-agent");
  const humanReviewClient = new HumanReviewClient();
  const finalizingAgent = new A2AClient("finalizing-agent");
  
  // Generate initial draft
  const draftResult = await draftAgent.createTask({ input: { query } });
  
  // Human review and feedback
  const humanFeedback = await humanReviewClient.requestReview({
    content: draftResult.output.draft,
    instructions: "Please review this draft and provide feedback"
  });
  
  // Incorporate human feedback
  const finalResult = await finalizingAgent.createTask({
    input: {
      query,
      draft: draftResult.output.draft,
      feedback: humanFeedback
    }
  });
  
  return finalResult;
}

Feedback Loops

Create systems that improve through iteration:

async function feedbackOrchestration(query: string, maxIterations = 3) {
  const generatorAgent = new A2AClient("generator-agent");
  const evaluatorAgent = new A2AClient("evaluator-agent");
  
  let currentDraft = null;
  let feedback = null;
  
  for (let i = 0; i < maxIterations; i++) {
    // Generate or refine content
    const generationResult = await generatorAgent.createTask({
      input: { 
        query,
        previousDraft: currentDraft,
        feedback
      }
    });
    
    currentDraft = generationResult.output.content;
    
    // Evaluate the draft
    const evaluationResult = await evaluatorAgent.createTask({
      input: { content: currentDraft, query }
    });
    
    // Check if quality threshold is met
    if (evaluationResult.output.qualityScore >= 0.9) {
      return { 
        content: currentDraft, 
        iterations: i + 1,
        finalScore: evaluationResult.output.qualityScore
      };
    }
    
    // Otherwise capture feedback for next iteration
    feedback = evaluationResult.output.improvement;
  }
  
  return { 
    content: currentDraft, 
    iterations: maxIterations,
    note: "Max iterations reached"
  };
}

Best Practices

Design for Resilience: Anticipate and gracefully handle failures
Maintain Context: Ensure important information flows between agents
Minimize Coupling: Design agents to function independently when possible
Version Compatibility: Maintain compatibility across agent versions
Security First: Implement proper authentication between agents
Avoid Cyclical Dependencies: Prevent infinite loops in agent interactions
Test Complex Scenarios: Thoroughly test edge cases in orchestration flows

Conclusion

Effective agent orchestration is key to unlocking the full potential of the A2A protocol. By combining specialized agents into coherent workflows, you can create systems that match or exceed human capabilities for complex tasks while maintaining clear boundaries and responsibilities between components.

Agent Orchestration

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