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Node Details

  • Name: Supervisor
  • Type: Supervisor
  • Category: Multi Agents
  • Version: 3.0

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Base Classes

  • Supervisor
  • (Additional base classes from Supervisor implementation)

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Parameters

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Inputs

  1. Supervisor Name
    • Type: string
    • Default: “Supervisor”
    • Description: The name of the supervisor agent
  2. Supervisor Prompt
    • Type: string
    • Description: Custom prompt for the supervisor, must contain {team_members}
    • Default: System-provided prompt template
  3. Tool Calling Chat Model (Required)
    • Type: BaseChatModel
    • Description: Language model used for decision-making (must support function calling)
    • Compatible Models:
      • ChatOpenAI
      • ChatMistral
      • ChatAnthropic
      • ChatGoogleGenerativeAI
      • GroqChat
  4. Agent Memory (Optional)
    • Type: BaseCheckpointSaver
    • Description: Used to save and restore the agent’s state
  5. Summarization (Optional)
    • Type: boolean
    • Description: Enables final output as a conversation summary
  6. Recursion Limit
    • Type: number
    • Default: 100
    • Description: Maximum number of recursive calls allowed
  7. Input Moderation (Optional)
    • Type: Moderation[]
    • Description: Filters for detecting potentially harmful text

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Functionality

  1. Coordination
    • Manages worker agent selection
    • Orchestrates conversation flow
    • Monitors task progress
    • Optimizes task completion
  2. Decision Making
    • Analyzes conversation state
    • Selects appropriate workers
    • Provides worker instructions
    • Ensures task coherence
  3. Process Management
    • Handles conversation initialization
    • Manages state transitions
    • Controls recursion depth
    • Provides optional summarization

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Use Cases

  1. Project Management
    • Coordinate multiple specialists
    • Break down complex tasks
    • Monitor progress
    • Ensure goal alignment
  2. Problem Solving
    • Distribute subtasks
    • Combine expert knowledge
    • Synthesize solutions
    • Maintain solution quality
  3. Research Coordination
    • Assign research tasks
    • Manage information gathering
    • Validate findings
    • Compile results

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Integration Notes

  • Best performance achieved with GPT-4
  • Requires function-calling capable models
  • Supports multi-modal inputs for compatible models
  • Special handling for various model types

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Best Practices

  1. Configuration
    • Set clear supervisor prompts
    • Choose appropriate models
    • Configure memory settings
    • Set reasonable recursion limits
  2. Monitoring
    • Track conversation progress
    • Monitor worker performance
    • Watch for recursion issues
    • Evaluate task completion
  3. Optimization
    • Fine-tune prompts
    • Adjust memory settings
    • Optimize model selection
    • Balance task distribution