CO - Análise de Personalidade icon

CO - Análise de Personalidade

Analise o texto e preveja o tipo de personalidade Myers-Briggs

Overview

This node performs personality analysis on a given text input by sending the text to an external prediction service. It predicts the Myers-Briggs personality type based on the analyzed text. This node is useful in scenarios where you want to infer personality traits from written content, such as analyzing customer feedback, social media posts, or any textual data to gain insights into personality types.

For example, you could use this node to analyze user reviews to tailor marketing strategies according to personality profiles or to better understand audience segments.

Properties

Name Meaning
Texto Para Analisar The text string that will be analyzed to predict the Myers-Briggs personality type. This property is required.

Output

The node outputs JSON data with the following structure:

  • predictedClass: Contains the predicted Myers-Briggs personality type(s) returned by the external prediction service.

Example output JSON:

{
  "predictedClass": "INTJ"
}

If the node encounters an error and is configured to continue on failure, it outputs the original input JSON along with an error object.

Dependencies

  • Requires access to an external HTTP API endpoint at http://192.168.0.105:9000/predict which performs the personality prediction.
  • No internal API keys or credentials are handled by the node itself; however, network access to the prediction service must be available.
  • The node uses standard HTTP POST requests with JSON payloads.

Troubleshooting

  • Connection errors: If the node cannot reach the prediction service (e.g., due to network issues or incorrect URL), it will throw an error unless configured to continue on failure.
  • Invalid response format: The node expects the response to contain a predicted_classes field. If the external service changes its response format, the node may fail.
  • Empty or invalid input text: Since the text input is required, providing empty or non-string values may cause unexpected results or errors.
  • To resolve these issues, ensure the prediction service is running and accessible, verify the input text is valid, and check the service's response format matches expectations.

Links and References

Discussion