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MLflow 2.12.2

· 2 min read
MLflow maintainers

MLflow 2.12.2 is a patch release that includes several bug fixes and integration improvements to existing features.

New features that are introduced in this patch release are intended to provide a foundation to further major features that will be released in the next 2 minor releases.

Features:

  • [Models] Add an environment configuration flag to enable raising an exception instead of a warning for failures in model dependency inference (#11903, @BenWilson2)
  • [Models] Add support for the llm/v1/embeddings task in the Transformers flavor to unify the input and output structures for embedding models (#11795, @B-Step62)
  • [Models] Introduce model streaming return via predict_stream() for custom pyfunc models capable of returning a stream response (#11791, #11895, @WeichenXu123)
  • [Evaluate] Add support for overriding the entire model evaluation judgment prompt within mlflow.evaluate for GenAI models (#11912, @apurva-koti)
  • [Tracking] Add support for defining deployment resource metadata to configure deployment resources within pyfunc models (#11832, #11825, #11804, @sunishsheth2009)
  • [Tracking] Add support for logging LangChain and custom pyfunc models as code (#11855, #11842, @sunishsheth2009)
  • [Tracking] Modify MLflow client's behavior to read from a global asynchronous configuration state (#11778, #11780, @chenmoneygithub)
  • [Tracking] Enhance system metrics data collection to include a GPU power consumption metric (#11747, @chenmoneygithub)

Bug fixes:

  • [Models] Fix a validation issue when performing signature validation if params are specified (#11838, @WeichenXu123)
  • [Databricks] Fix an issue where models cannot be loaded in the Databricks serverless runtime (#11758, @WeichenXu123)
  • [Databricks] Fix an issue with the Databricks serverless runtime where scaled workers do not have authorization to read from the driver NFS mount (#11757, @WeichenXu123)
  • [Databricks] Fix an issue in the Databricks serverless runtime where a model loaded via a spark_udf for inference fails due to a configuration issue (#11752, @WeichenXu123)
  • [Server-infra] Upgrade the gunicorn dependency to version 22 to address a third-party security issue (#11742, @maitreyakv)

Documentation updates:

  • [Docs] Add additional guidance on search syntax restrictions for search APIs (#11892, @BenWilson2)
  • [Docs] Fix an issue with the quickstart guide where the Keras example model is defined incorrectly (#11848, @horw)
  • [Docs] Provide fixes and updates to LangChain tutorials and guides (#11802, @BenWilson2)
  • [Docs] Fix the model registry example within the docs for correct type formatting (#11789, @80rian)

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.