v2.21.1
📦 mlflowView on GitHub →
✨ 3 features🐛 5 fixes🔧 8 symbols
Summary
MLflow 2.21.1 adds DSPy evaluation logging, run creation on DSPy compile, and a Java‑less SageMaker container option, while fixing several tracing, tracking, and UI bugs.
✨ New Features
- Introduce support for logging evaluations within DSPy (Tracking).
- Add support for run creation when DSPy compile is executed (Tracking).
- Add support for building a SageMaker serving container without Java via the `--install-java` option (Docker / Sagemaker).
🐛 Bug Fixes
- Fix an issue with trace ordering due to a timestamp conversion timezone bug (Tracing).
- Fix a typo in the environment variable `OTEL_EXPORTER_OTLP_PROTOCOL` definition (Tracking).
- Fix an issue in shared and serverless clusters on Databricks when logging Spark Datasources using the evaluate API (Tracking).
- Fix a rendering issue with displaying images from within the metric tab in the UI (UI).
- Various small bug fixes and documentation updates (see issue numbers #15009, #14995, #15039, #15040, #15010, #15053, #15014, #15025, #15030, #15050, #15070, #15035, #15064, #15058, #14945).