How To Fix WGDS_PROCESS771 - Unable to parse the inference results for model &1 version &2

SAP Error Message - Details

• Message type: E = Error

• Message class: WGDS_PROCESS - Global data synchronisation

• Message number: 771

• Message text: Unable to parse the inference results for 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.

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Smart SAP Assistant

• What is the cause and solution for SAP error message WGDS_PROCESS771 - Unable to parse the inference results for model &1 version &2 ?

  The SAP error message:
  WGDS_PROCESS771 Unable to parse the inference results for model &1 version &2
  typically occurs in the context of SAP's machine learning or predictive services, where a model inference (prediction) is executed, but the system fails to correctly interpret or parse the results returned by the model.
  
  Cause
  
  Malformed or unexpected inference output: The model's output format does not match the expected structure that SAP's inference engine or service is designed to parse.
  Version mismatch: The model version (&2) might be incompatible with the current inference engine or the consuming application.
  Serialization/Deserialization issues: The data returned by the model might be corrupted, incomplete, or serialized in an unexpected format.
  Configuration errors: Incorrect configuration of the model deployment or inference service, such as wrong endpoint, wrong model version, or incorrect data schema.
  Network or communication issues: Partial or corrupted data transfer during inference request/response.
  Model runtime errors: The model itself might have runtime errors causing it to return invalid or incomplete results.
  
  
  Solution
  
  
  Check the model output format:
  
  Verify that the model's inference output matches the expected schema or format required by SAP.
  If you have access to the model code or deployment, test the inference output independently to ensure it is valid.
  
  
  
  Validate model version:
  
  Confirm that the model version (&2) deployed is compatible with the SAP system and inference engine.
  If multiple versions exist, try using a different version to see if the problem persists.
  
  
  
  Review configuration:
  
  Check the configuration of the model deployment in SAP (e.g., SAP AI Core, SAP Data Intelligence, or SAP Predictive Analytics).
  Ensure the correct model ID (&1) and version (&2) are referenced.
  Verify endpoint URLs, authentication, and data schema mappings.
  
  
  
  Inspect logs and traces:
  
  Look into detailed logs of the inference service or SAP system to find more clues about the parsing failure.
  Check for any serialization/deserialization exceptions or communication errors.
  
  
  
  Test inference independently:
  
  Run the model inference outside SAP (e.g., via REST API or command line) to verify the output.
  If the output is invalid, fix the model or its serving infrastructure.
  
  
  
  Update or redeploy the model:
  
  If the model is corrupted or outdated, retrain, update, or redeploy it.
  Ensure the deployment process completes successfully.
  
  
  
  SAP Notes and Support:
  
  Search for SAP Notes related to WGDS_PROCESS771 for any patches or known issues.
  If unresolved, raise a support ticket with SAP, providing model details, version, and logs.
  
  
  
  
  Related Information
  
  **WGDS_PROCESS* messages are related to SAP's SAP AI Core, SAP Data Intelligence, or SAP Predictive Analytics** components where machine learning models are managed and executed.
  The error indicates a failure in the inference result parsing step, which is critical for downstream processing.
  Proper model versioning and deployment practices help avoid such errors.
  Ensure that the model serving infrastructure (e.g., TensorFlow Serving, ONNX Runtime, or custom inference service) is stable and compatible.
  Check SAP documentation on Model Deployment and Inference for your specific SAP ML product.
  
  
  If you provide more context (e.g., which SAP product you are using, model type, deployment method), I can help tailor the troubleshooting steps further.