Worker

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Node Details

• Name: worker
• Type: Worker
• Version: 2.0
• Category: Multi Agents

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Base Classes

• Worker_MultiAgents
• (Additional base classes from Worker implementation)

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Parameters

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Inputs

1. Worker Name (Required)
   • Type: string
   • Description: Unique identifier for the worker agent
2. Worker Prompt (Required)
   • Type: string
   • Default: “You are a research assistant who can search for up-to-date info using search engine.”
   • Description: Defines the worker’s behavior and specialization
3. Tools (Optional)
   • Type: Tool[]
   • Description: List of tools available to the worker for task execution
4. Supervisor (Required)
   • Type: Supervisor
   • Description: Reference to the supervising node
5. Tool Calling Chat Model (Optional)
   • Type: BaseChatModel
   • Description: Language model for tool interactions
   • Default: Uses supervisor’s model if not specified
   • Compatible Models:
     • ChatOpenAI
     • ChatMistral
     • ChatAnthropic
     • ChatGoogleGenerativeAI
     • ChatVertexAI
     • GroqChat
6. Format Prompt Values (Optional)
   • Type: json
   • Description: Values for input variables in the worker prompt
7. Max Iterations (Optional)
   • Type: number
   • Description: Maximum execution iterations allowed

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Functionality

1. Task Execution
   • Autonomous operation
   • Tool utilization
   • Task specialization
   • Multi-modal support
2. Integration Features
   • Supervisor coordination
   • Tool management
   • State handling
   • Error management
3. Process Control
   • Iteration management
   • Abort handling
   • Progress tracking
   • Resource optimization

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Use Cases

1. Specialized Research
   • Information gathering
   • Data analysis
   • Source verification
   • Report generation
2. Tool-Based Tasks
   • API interactions
   • Data processing
   • Resource management
   • System integration
3. Collaborative Work
   • Team coordination
   • Task specialization
   • Result sharing
   • Progress reporting

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Integration Notes

• Requires proper supervisor configuration
• Supports multi-modal content
• Handles tool integration seamlessly
• Manages state persistence

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Best Practices

1. Configuration
   • Clear role definition
   • Appropriate tool selection
   • Optimal prompt design
   • Resource allocation
2. Error Handling
   • Input validation
   • Tool error management
   • State recovery
   • Graceful degradation
3. Performance Optimization
   • Tool usage efficiency
   • Prompt optimization
   • Iteration control
   • Resource management
4. Maintenance
   • Regular prompt updates
   • Tool verification
   • Performance monitoring
   • Error pattern analysis