Supervisor

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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