The Call Neuron node enables you to invoke other neurons within your workflow, passing the current input and context. This allows for modular workflow design and reuse of common functionality.

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Functionality

The Call Neuron node:

  • Executes another neuron using the current input
  • Passes all context from the current workflow
  • Returns the called neuron’s response
  • Enables workflow modularity and reuse

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Usage Examples

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Scenario: Modular Processing

In this example, separate neurons handle text formatting and analysis, making the components reusable across different workflows.

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Scenario: Conditional Neuron Selection

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Tips and Best Practices

  • Design neurons to be modular and reusable
  • Use meaningful neuron names for better workflow readability
  • Consider creating utility neurons for common operations
  • Remember that called neurons inherit the context of the calling workflow
  • Avoid deep nesting of neuron calls to maintain clarity
  • Use the same input/output format conventions across related neurons

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Common Use Cases

  • Language-specific processing
  • Reusable validation workflows
  • Standard formatting operations
  • Complex multi-step analyses
  • Error handling patterns
  • Template-based generation