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h2oGPTe

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Overview

This node operation provides a helper function to generate reasonable and easy-to-use default settings for guardrails related to Personally Identifiable Information (PII) detection and handling. It is designed to assist users in configuring guardrails or PII settings for AI models, particularly those that enforce data privacy and compliance by detecting sensitive information.

Typical use cases include:

  • Automatically generating default configurations for PII detection in AI model prompts.
  • Simplifying the setup of guardrails to redact or fail on detection of sensitive data.
  • Customizing which types of PII entities (sensitive or non-sensitive) should be included in the guardrails.
  • Enabling safer AI deployments by enforcing data privacy policies with minimal manual configuration.

For example, a user can request defaults that redact all detected PII or fail the operation if PII is found, while specifying whether to include sensitive entities like social security numbers or just non-sensitive ones like email addresses.

Properties

Name Meaning
Action What action to take when detecting PII. Options: "redact" (remove PII), "fail" (fail the operation). Note: Guardrails models always fail on PII detection; "allow" is not supported here.
All Guardrails Boolean flag indicating whether to include all possible PII entity types for prompt guard and guardrails models, or just system default entities.
Guardrails Settings JSON object allowing further customization of guardrails settings beyond the defaults provided.
Non Sensitive Boolean flag to include all non-sensitive PII entities such as IP addresses, locations, names, email addresses, etc.
Sensitive Boolean flag to include the most sensitive PII entities like Social Security Numbers (SSN), bank account information, etc.

Output

The output JSON contains the generated guardrails/PII settings based on the input parameters. This typically includes structured configuration data specifying which PII entities are monitored and what actions are taken upon detection. The exact structure depends on the API response but generally provides a ready-to-use guardrails configuration object for further use in model operations.

No binary data output is involved.

Dependencies

  • Requires an API key credential for authentication to the external service providing the guardrails settings.
  • The node sends a POST request to the /guardrails_settings endpoint of the configured API base URL.
  • Proper network connectivity and valid credentials are necessary.

Troubleshooting

  • Invalid Action Value: If the action property is set to an unsupported value (e.g., "allow"), the API may reject the request. Use only "redact" or "fail".
  • Missing Credentials: Ensure that the API key credential is correctly configured and has permissions to access the guardrails settings endpoint.
  • Malformed JSON in Guardrails Settings: If custom JSON is provided in guardrails_settings, ensure it is valid JSON to avoid request errors.
  • Timeouts or Network Issues: Check network connectivity and API availability if requests time out or fail.
  • Conflicting Flags: Setting both all_guardrails and specific flags (non_sensitive, sensitive) might cause unexpected results; review the combination of options used.

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