Overview
The PanRock node is designed to process and interpret a given message within a specified context using an AI-based interpreter. It leverages an external AI service (similar in concept to OpenAI) to evaluate the input message and produce a structured output based on user-defined output fields. This node is useful for scenarios where you want to analyze or transform textual data dynamically, such as extracting insights from messages, generating summaries, or mapping inputs to custom outputs.
Practical examples include:
- Analyzing customer feedback messages to extract key points.
- Interpreting commands or queries in a chatbot workflow.
- Transforming raw text into structured event descriptions or values for further automation.
Properties
| Name | Meaning |
|---|---|
| Mensaje | The message text that will be evaluated by the AI interpreter. |
| Contexto | The contextual information or background that guides how the message should be interpreted. Supports multiline input. |
| Salidas | A collection of output definitions where each output has: - Description: A label describing the output field. - Valor: The value extracted or generated for that output field. Multiple outputs can be defined. |
Output
The node outputs a JSON array with a single object containing a result field. This result holds the evaluation result returned by the AI interpreter based on the input message, context, and defined outputs.
Example structure of the output JSON:
[
{
"result": {
// The structure depends on the AI interpreter's response,
// typically matching the user-defined output fields.
}
}
]
No binary data output is produced by this node.
Dependencies
- Requires an API key credential for an AI service compatible with the OpenAI API interface.
- The node uses a helper method to authenticate requests to this AI service.
- No other external dependencies are indicated.
Troubleshooting
Common issues:
- Missing or invalid API key credential will cause authentication failures.
- Improperly formatted or empty message/context inputs may lead to unexpected or empty results.
- Defining outputs incorrectly (e.g., no outputs specified) might cause the node to return incomplete data.
Error messages:
- Authentication errors typically indicate problems with the provided API key; verify the credential configuration.
- Request failures may occur if the AI service is unreachable or returns an error; check network connectivity and service status.
- Validation errors if required parameters like "Mensaje" or "Contexto" are missing; ensure these fields are filled.
Links and References
- OpenAI API Documentation
- n8n documentation on Creating Custom Nodes