Orchestration Overview

Coordinate how agents work together to handle user requests.

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The orchestrator is the intelligence layer that manages agent interactions. It:

• Interprets user intent
• Selects the appropriate agent(s)
• Coordinates multi-agent workflows
• Resolves conflicts between outputs
• Delivers unified responses

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Orchestration Patterns

Choose a pattern based on your use case complexity.

• Single Agent: One agent handles all requests. Best for focused, well-defined domains.

• Supervisor: Central orchestrator coordinates multiple specialized agents. Best for complex, parallelizable tasks.

• Adaptive Network: Agents dynamically hand off to each other. Best for sequential, multi-domain workflows.

Pattern Comparison

Aspect	Single Agent	Supervisor	Adaptive Network
Complexity	Low	Medium	Medium-High
Agents	1	Multiple	Multiple
Coordination	None	Centralized	Decentralized
Execution	Sequential	Parallel	Sequential
Latency	Lowest	Medium	Variable	Low
Best for	Simple tasks	Complex decomposition	Dynamic hand-offs

How Orchestration Works

┌──────────────────────────────────────────────────────────────┐ │ User Request │ └──────────────────────────────────────────────────────────────┘ │ │ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ Intent Analysis │ │ • Parse user input │ │ • Identify required capabilities │ │ • Determine complexity │ └──────────────────────────────────────────────────────────────┘ │ │ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ Agent Selection │ │ • Match capabilities to agent descriptions │ │ • Consider agent availability and scope │ │ • Select single agent or multiple agents │ └──────────────────────────────────────────────────────────────┘ │ │ │ ┌───────────────┼───────────────┐ │ ▼ ▼ ▼ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ │ Agent A │ │ Agent B │ │ Agent C │ │ └────┬─────┘ └────┬─────┘ └────┬─────┘ │ │ │ │ │ └───────────────┼───────────────┘ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ Response Aggregation │ │ • Collect agent outputs │ │ • Resolve conflicts │ │ • Synthesize unified response │ └──────────────────────────────────────────────────────────────┘ │ │ │ ▼ ┌──────────────────────────────────────────────────────────────┐ │ User Response │ └──────────────────────────────────────────────────────────────┘

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Choosing the Right Pattern

Use Single Agent when:

• Your app has one primary capability
• Tasks don’t require coordination between specialists
• You want minimal orchestration overhead
• Response latency is critical

Example: A leave management bot where one agent handles all employee requests.

Use Supervisor when:

• Tasks can be broken into independent subtasks
• You need parallel execution for speed
• Multiple specialists should contribute to responses
• You want centralized control and conflict resolution

Example: A customer service app where billing, orders, and technical support agents work in parallel.

Use Adaptive Network when:

• Tasks flow naturally between domains
• You need dynamic routing based on context
• Agents should autonomously decide when to hand off
• Sequential expertise is required

Example: An employee onboarding app where HR, IT, and Finance agents hand off based on the current step.

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Orchestrator Responsibilities

Task Decomposition

Breaking complex requests into manageable subtasks:

User: "I need to cancel my order and get a refund"

Decomposition:
├── Subtask 1: Look up order details (Order Agent)
├── Subtask 2: Process cancellation (Order Agent)
└── Subtask 3: Initiate refund (Billing Agent)

Agent Delegation

Routing tasks to appropriate specialists:

Request: "What's my order status and can I upgrade my shipping?"

Delegation:
├── Order Agent: Retrieve order status
└── Shipping Agent: Process shipping upgrade

Conflict Resolution

Handling inconsistencies between agent outputs:

Conflict:
├── Agent A: "Item is in stock"
└── Agent B: "Item ships in 2 weeks"

Resolution: Check inventory system → Provide accurate status

Context Management

Maintaining conversation state across agents:

Context:
├── User ID: 12345
├── Session ID: abcde
└── Previous Turns:
    ├── Turn 1: User provides order number
    ├── Turn 2: Agent A uses order number
    └── Turn 3: Agent B receives context, doesn't ask again

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Configuration

Basic Configuration

orchestration:
  pattern: supervisor  # single_agent, supervisor, adaptive_network

  # Model for orchestration decisions
  model: gpt-4o

  # How agent selection works
  selection:
    strategy: description_match
    fallback_agent: default_support

Advanced Options

orchestration:
  # Maximum agents per request
  max_concurrent_agents: 3

  # Timeout for agent responses
  agent_timeout_ms: 30000

  # Conflict resolution strategy
  conflict_resolution: prefer_primary

  # Enable conversation summarization
  context_summarization: true