OrcaSDK Release Notes#

This document tracks notable changes to the OrcaSDK.

v0.1.5#

Added use_gpu parameter to prediction methods to allow CPU-based predictions
Added support for using string columns as label columns
Added sample parameter to memoryset creation methods and model evaluate methods to allow sampling of rows
Added ignore_unlabeled parameter to prediction and evaluate methods
Added method to query datasource rows
Added support to finetune embedding models for regression tasks
Added support for querying prediction telemetry on memories
Updated SDK to use new job endpoints
Improved prediction caching
Fixed dependency vulnerability

Added async ClassificationModel.apredict and Memoryset.ainsert methods.
Added batching to Memoryset.insert, Memoryset.update, and Memoryset.delete methods to reduce network issues.
Renamed "neighbor" analysis to "distribution" analysis.
Allowed injecting custom httpx clients via context to cleanly override api keys and controll client lifecycle.
Fixed creation of orphaned datasources when using the if_exists="open" option during memoryset creation.
Removed deprecated Memoryset.run_embedding_evaluation method, use EmbeddingModel.evaluate instead.

Added support for None labels and scores to memorysets and models.
Added automatic retrying of requests to improve mitigate transient network and service issues.
Fixed bug when receiving additional field in API responses for metrics
Updated dependencies to resolve vulnerabilities