How To Fix WGDS_PROCESS766 - An issue has occured with the inference processing of model &1 version &2

SAP Error Message - Details

• Message type: E = Error

• Message class: WGDS_PROCESS - Global data synchronisation

• Message number: 766

• Message text: An issue has occured with the inference processing of model &1 version &2

Self-Explanatory Message

Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

Unfortunately, there isn't any extra information in this error notice.

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Smart SAP Assistant

• What is the cause and solution for SAP error message WGDS_PROCESS766 - An issue has occured with the inference processing of model &1 version &2 ?

  The SAP error message:
  WGDS_PROCESS766: An issue has occurred with the inference processing of model &1 version &2
  typically relates to problems encountered during the inference (prediction) phase of a machine learning model within SAP's AI or predictive analytics framework, such as SAP Data Intelligence, SAP AI Core, or SAP Predictive Analytics.
  
  Cause
  
  Model Inference Failure: The error indicates that the system encountered an issue while trying to run inference (prediction) using the specified model and version.
  Model Corruption or Incompatibility: The model version &2 might be corrupted, incomplete, or incompatible with the current runtime environment.
  Resource or Environment Issues: Insufficient resources (memory, CPU), missing dependencies, or misconfigured runtime environments can cause inference to fail.
  Input Data Issues: The input data provided to the model for inference might be malformed, missing required features, or not matching the expected schema.
  Version Mismatch: The model version &2 might not be properly deployed or registered in the system.
  Software Bugs or Configuration Errors: There could be bugs in the inference engine or incorrect configuration parameters.
  
  
  Solution
  
  
  Check Model Deployment:
  
  Verify that the model &1 version &2 is correctly deployed and registered in the system.
  Redeploy the model if necessary.
  
  
  
  Validate Input Data:
  
  Ensure that the input data for inference matches the expected format and schema.
  Check for missing or invalid data fields.
  
  
  
  Review Logs and Trace:
  
  Check detailed logs for the inference process to identify specific errors or stack traces.
  Use SAP diagnostic tools or trace options to get more information.
  
  
  
  Resource Availability:
  
  Confirm that the system has sufficient resources (CPU, memory) to run the inference.
  Check for any resource constraints or limits.
  
  
  
  Update or Rebuild Model:
  
  If the model is corrupted or outdated, retrain and rebuild the model.
  Test the new model version before deployment.
  
  
  
  Check Environment and Dependencies:
  
  Verify that all required libraries, runtime environments, and dependencies are installed and compatible.
  Update or patch the inference engine if needed.
  
  
  
  SAP Notes and Support:
  
  Search for relevant SAP Notes related to WGDS_PROCESS766.
  If the problem persists, raise a support ticket with SAP, providing model details, version, logs, and environment information.
  
  
  
  
  Related Information
  
  SAP AI Core / AI Foundation: This error is common in SAP AI Core or AI Foundation when running model inference pipelines.
  SAP Predictive Analytics: Similar errors can occur in SAP Predictive Analytics or SAP Data Intelligence when models are deployed and used for scoring.
  SAP Notes: Check SAP Support Portal for notes related to WGDS_PROCESS766 or inference processing errors.
  Documentation: Review SAP Help Portal documentation on model deployment, inference, and troubleshooting in the relevant SAP AI or predictive analytics product.
  
  
  If you provide more context (e.g., product name, scenario, logs), I can help with more specific guidance.