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Agent Orchestration

Agent orchestration manages the coordination, communication, and workflow between multiple AI agents in the MOOD MNKY ecosystem.

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Overview

The orchestration system enables:
  • Multi-agent collaboration - Agents working together on complex tasks
  • Workflow management - Coordinated task execution
  • Load balancing - Optimal agent assignment
  • Conflict resolution - Handling agent disagreements

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Architecture

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Orchestration Engine

The central orchestration engine coordinates agent activities:
  • Task Routing: Directs tasks to appropriate agents
  • State Management: Tracks multi-agent conversation state
  • Event Bus: Facilitates inter-agent communication
  • Scheduler: Manages asynchronous task execution

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Agent Communication

Agents communicate through:
  • Message Passing: Direct agent-to-agent messages
  • Shared Context: Common knowledge base access
  • Event System: Pub/sub event notifications
  • API Gateway: Standardized communication protocols

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Agent Roles

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MOOD MNKY

  • Primary customer interaction agent
  • Coordinates with SAGE and CODE for complex requests
  • Manages customer journey orchestration

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CODE MNKY

  • Technical task execution
  • Receives technical requests from MOOD
  • Provides automation and development support

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SAGE MNKY

  • Emotional intelligence support
  • Assists MOOD with empathy and understanding
  • Provides psychological insights

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Workflow Patterns

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Sequential Workflow

Tasks flow from one agent to another in sequence: 
User → MOOD → CODE → Result → MOOD → User

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Parallel Processing

Multiple agents work simultaneously: 
User Request → MOOD (orchestrates)
              ├─→ CODE (technical analysis)
              └─→ SAGE (emotional context)
              → MOOD (synthesizes) → User

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Hierarchical Delegation

MOOD delegates to specialized agents: 
MOOD (receives request)
  ├─→ CODE (if technical)
  └─→ SAGE (if emotional)

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Configuration

Orchestration is configured through the agent infrastructure: 
orchestration:
  engine: "langchain"
  max_agents: 3
  timeout: 30s
  retry_policy: "exponential_backoff"