Briefly, this error occurs when the Elasticsearch zero-shot classification model is unable to find any data to classify. This could be due to an empty or non-existent index, or the data does not match the model’s requirements. To resolve this, ensure that the index you’re querying contains data and that the data is compatible with the zero-shot classification model. Also, check your query syntax and parameters to ensure they are correct. If the problem persists, consider retraining your model with appropriate data.
This guide will help you check for common problems that cause the log ” Zero shot classification result has no data ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.
Log Context
Log “Zero shot classification result has no data” class name is ZeroShotClassificationProcessor.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
NlpTask.ResultProcessor { @Override
public InferenceResults processResult(TokenizationResult tokenization; PyTorchInferenceResult pyTorchResult) {
if (pyTorchResult.getInferenceResult().length < 1) {
throw new ElasticsearchStatusException("Zero shot classification result has no data"; RestStatus.INTERNAL_SERVER_ERROR);
}
// TODO only the first entry in the batch result is verified and
// checked. Implement for all in batch
if (pyTorchResult.getInferenceResult()[0].length != labels.length) {
throw new ElasticsearchStatusException(
