Version 0.14.0

• Add retry strategy to delete_data, get_data and update_data (#222)
• Deployment parameter disk_folder defaults to the current working directory for both Docker and Cloud deployment (#225)
• Vespa connection now accepts cert and key as separate arguments. Using both certificate and key values in the cert file continue to work as before. (#226)

Version 0.13.0

• Infer schema name whenever possible for batch document operations (#210)
  • When we have application package information containing just one schema, it is possible to simplify the batch document operations by not specifying the schema name. For those cases, we can for example use app.feed_batch(docs) instead of app.feed_batch(docs, schema = "sentence") when we know there is only one schema named "sentence".
• Introduce TextSearch use case (#212)
• Create a convenience function to feed df to a Vespa app (#213)
• Allow a data frame to be used when collecting training data (#215)
• Allow default query model to be specified and define it for TextSearch (#217)

Version 0.12.0

Removes vespa.package module dependency on the vespa.ml module. The main goal is to avoid installing vespa.ml specific dependencies through pip install pyvespa[ml] unless the user explicitly wants to use vespa.ml classes.

Version 0.11.0

• Use tasks instead of models as argument name for ModelServer to align with the fact this argument takes instances of type TextTask.
• Use model_id instead of model_name to identify a model since model_id is what we use when defining a Task.

Version 0.10.0

Introduce stateless model evaluation with SequenceClassification task.

• Adapt ApplicationPackage to allow for simpler configurations, e.g. no schema.
• Implement ModelServer, which is a simplified ApplicationPackage focused on stateless model evaluation.
• ApplicationPackage is now included on the Vespa instance when deploying apps with pyvespa.
  • This helps to process input/output involved when using stateless model evaluations through app.predict.
• Vespa now has get_model_endpoint and predict to use for stateless model evaluation mode.
• Both VespaDocker and VespaCloud now work with ModelServer deployment to deploy stateless model evaluation apps.
• Created SequenceClassification task that inherits from the base class TextTask.

Version 0.9.0

VespaDocker and VespaCloud are now only available via the vespa.deployment module.

Version 0.8.1

• VespaDocker and VespaCloud will move to the deployment module
  • v 0.8.1 still works with vespa.package.VespaDocker and vespa.package.VespaCloud but it will issue a deprecation warning informing users to use vespa.deployment.VespaDocker and vespa.deployment.VespaCloud instead.
  • v 0.9.0 will remove vespa.package.VespaDocker and vespa.package.VespaCloud and users must use vespa.deployment.VespaDocker and vespa.deployment.VespaCloud