Enabling and disabling WCM content AI analysis

This document outlines configurations to enable and disable artificial intelligence (AI) analysis for Web Content Management (WCM) content in a Kubernetes deployment using the values.yaml file. You can also configure a content AI provider to be used for AI analysis.

WCM Content AI configuration

Refer to the following sample snippet for configuring the Digital Experience (DX) WebEngine server to enable Content AI analysis:

configuration:
  #Configuration for webEngine
  webEngine:
    contentAI:
      className: com.ai.sample.CustomerAI
      enabled: true
      provider: OPEN_AI
security:
  # Security configuration for webEngine
  webEngine:
      webEngineContentAIProviderAPIKey: ""
      customWebEngineContentAISecret: custom-credentials-webengine-ai-secret

To disable Content AI Analysis, refer to the following sample configuration:

configuration:
  #Configuration for webEngine
  webEngine:
    contentAI:
      enabled: true
      provider: ""

Content AI configuration parameters

In the provided configuration, the following parameters are used:

• className: Provide the custom AI class name. The default value is com.hcl.workplace.wcm.restv2.ai.ChatGPTAnalyzerService if the AI analysis is enabled with provider OPEN_AI.
• enabled: Set to true to enable content AI or to false to disable. By default, this parameter is set to false.
• provider: If content AI is enabled, provide the content AI provider in this parameter. Valid values are OPEN_AI and CUSTOM.
• webEngineContentAIProviderAPIKey: Enter the API key for the AI Provider. The AI provider provides an API key to access its API.
• customWebEngineContentAISecret: Provide a secret name that will be used to set the AI API Key.

To create a custom secret, run the following command:

kubectl create secret generic WEBENGINE_AI_CUSTOM_SECRET --from-literal=apiKey=API_KEY --namespace=NAME_SERVER

Replace API_KEY and NAME_SERVER with the actual values. For example:

kubectl create secret generic custom-credentials-webengine-ai-secret --from-literal=apiKey=your-API-Key --namespace=dxns

Note

If a custom secret is used instead of an API key directly in the values.yaml file, then you must create the custom secret using the content AI provider's API key. You must then refer to the secret name in the customWebEngineContentAISecret property and leave the webEngineContentAIProviderAPIKey blank and vice versa.

Validation

After updating the values.yaml file, perform the following actions:

• If running the server for the first time, refer to Installing WebEngine.
• If upgrading previous configurations, refer to Upgrading the Helm deployment.

After enabling the Content AI analysis, refer to the steps in WCM REST V2 AI Analysis API to call the AI Analyzer APIs of the configured Content AI Provider.