MLflow 2.22.0 brings important bug fixes and improvements to the UI and tracking capabilities.
Features:
- [Tracking[ Supported tracing for OpenAI Responses API.
(#15240, @B-Step62) - [Tracking[ Introduced
get_last_active_trace, which affects model serving/monitoring logic.
(#15233, @B-Step62) - [Tracking[ Introduced async export for Databricks traces (default behavior).
(#15163, @B-Step62) - [AI Gateway[ Added Gemini embeddings support with corresponding unit tests.
(#15017, @joelrobin18) - [Tracking / SQLAlchemy[ MySQL SSL connections are now supported with client certs.
(#14839, @aksylumoed) - [Models[ Added Optuna storage utility for enabling parallel hyperparameter tuning.
(#15243, @XiaohanZhangCMU) - [Artifacts[ Added support for Azure Data Lake Storage (ADLS) artifact repositories.
(#14723, @serena-ruan) - [UI[ Artifact views for text now auto-refresh in the UI.
(#14939, @joelrobin18)
Bug Fixes:
- [Tracking / UI[ Fixed serialization for structured output in
langchain_tracer+ added unit tests.
(#14971, @joelrobin18) - [Server-infra[ Enforced password validation for authentication (min. 8 characters).
(#15287, @WeichenXu123) - [Deployments[ Resolved an issue with the OpenAI Gateway adapter.
(#15286, @WeichenXu123) - [Artifacts / Tracking / Server-infra[ Normalized paths by stripping trailing slashes.
(#15016, @tarek7669) - [Tags[ Fixed a bug where tag values containing
": "were being truncated.
(#14896, @harupy)
For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.