build(deps): bump mlflow from 2.12.1 to 2.13.0 in /runtimes/mlflow

[dependabot]

Bumps mlflow from 2.12.1 to 2.13.0.

Release notes

Sourced from mlflow's releases.

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)

Small bug fixes and documentation updates:

#11928, @​apurva-koti; #11910, #11915, #11864, #11893, #11875, #11744, @​BenWilson2; #11913, #11918, #11869, #11873, #11867, @​sunishsheth2009; #11916, #11879, #11877, #11860, #11843, #11844, #11817, #11841, @​annzhang-db; #11822, #11861, @​serena-ruan; #11890, #11819, #11794, #11774, @​B-Step62; #11880, @​prithvikannan; #11833, #11818, #11954, @​harupy; #11831, @​dbczumar; #11812, #11816, #11800, @​daniellok-db; #11788, @​smurching; #11756, @​IgorMilavec; #11627, @​jessechancy

Changelog

Sourced from mlflow's changelog.

CHANGELOG

2.12.2 (2024-05-08)

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)

Small bug fixes and documentation updates:

#11928, @​apurva-koti; #11910, #11915, #11864, #11893, #11875, #11744, @​BenWilson2; #11913, #11918, #11869, #11873, #11867, @​sunishsheth2009; #11916, #11879, #11877, #11860, #11843, #11844, #11817, #11841, @​annzhang-db; #11822, #11861, @​serena-ruan; #11890, #11819, #11794, #11774, @​B-Step62; #11880, @​prithvikannan; #11833, #11818, #11954, @​harupy; #11831, @​dbczumar; #11812, #11816, #11800, @​daniellok-db; #11788, @​smurching; #11756, @​IgorMilavec; #11627, @​jessechancy

Commits

• 1b604e4 Run python3 dev/update_mlflow_versions.py pre-release ... (#12056)
• 43bddf7 [test] run test_langchain_tracer in cross_version tests (#12052)
• 22a5b53 [MLflow] Fix langchain tests (#12054)
• 9b36854 Rename function and fix iter (#12053)
• 3779805 [MLflow] Renaming vector search index to retriever (#12051)
• f7c420f LangChain tracing: only end spans if the trace is still active (#12049)
• b53cd2e [MLflow] Update mlflow langchain pyfunc.load_model to correctly write tags to...
• 2c7906a Bug fix: TraceStatus hydration from proto (#12044)
• fa6e185 [MLflow] Update mlflow langchain metadata to write dependencies_schemas (#12045)
• e18ba3f Run protos workflow if we change dependencies (#12047)
• Additional commits viewable in compare view

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