Bump mlflow from 2.8.1 to 2.14.2 in /session_nmf

[dependabot]

Bumps mlflow from 2.8.1 to 2.14.2.

Release notes

Sourced from mlflow's releases.

MLflow 2.14.2 is a patch release that includes several important bug fixes and documentation enhancements.

Bug fixes:

• [Models] Fix an issue with requirements inference error handling when disabling the default warning-only behavior (#12547, @​B-Step62)
• [Models] Fix dependency inference issues with Transformers models saved with the unified API llm/v1/xxx task definitions. (#12551, @​B-Step62)
• [Models / Databricks] Fix an issue with MLlfow log_model introduced in MLflow 2.13.0 that causes Databricks DLT service to crash in some situations (#12514, @​WeichenXu123)
• [Models] Fix an output data structure issue with the predict_stream implementation for LangChain AgentExecutor and other non-Runnable chains (#12518, @​B-Step62)
• [Tracking] Fix an issue with the predict_proba inference method in the sklearn flavor when loading an sklearn pipeline object as pyfunc (#12554, @​WeichenXu123)
• [Tracking] Fix an issue with the Tracing implementation where other services usage of OpenTelemetry would activate MLflow tracing and cause errors (#12457, @​B-Step62)
• [Tracking / Databricks] Correct an issue when running dependency inference in Databricks that can cause duplicate dependency entries to be logged (#12493, @​sunishsheth2009)

Documentation updates:

• [Docs] Add documentation and guides for the MLflow tracing schema (#12521, @​BenWilson2)

Small bug fixes and documentation updates:

#12311, #12285, #12535, #12543, #12320, #12444, @​B-Step62; #12310, #12340, @​serena-ruan; #12409, #12432, #12471, #12497, #12499, @​harupy; #12555, @​nojaf; #12472, #12431, @​xq-yin; #12530, #12529, #12528, #12527, #12526, #12524, #12531, #12523, #12525, #12522, @​dbczumar; #12483, @​jsuchome; #12465, #12441, @​BenWilson2; #12450, @​StarryZhang-whu

MLflow 2.14.1 is a patch release that contains several bug fixes and documentation improvements

Bug fixes:

• [Models] Fix params and model_config handling for llm/v1/xxx Transformers model (#12401, @​B-Step62)
• [UI] Fix dark mode user preference (#12386, @​daniellok-db)
• [Docker] Fix docker image failing to build with install_mlflow=False (#12388, @​daniellok-db)

Documentation updates:

• [Docs] Add link to langchain autologging page in doc (#12398, @​xq-yin)
• [Docs] Add documentation for Models from Code (#12381, @​BenWilson2)

Small bug fixes and documentation updates:

#12415, #12396, #12394, @​harupy; #12403, #12382, @​BenWilson2; #12397, @​B-Step62

v2.14.0

2.14.0 (2024-06-17)

MLflow 2.14.0 includes several major features and improvements that we're very excited to announce!

Major features:

• MLflow Tracing: Tracing is powerful tool designed to enhance your ability to monitor, analyze, and debug GenAI applications by allowing you to inspect the intermediate outputs generated as your application handles a request. This update comes with an automatic LangChain integration to make it as easy as possible to get started, but we've also implemented high-level fluent APIs, and low-level client APIs for users who want more control over their trace instrumentation. For more information, check out the guide in our docs!
• Unity Catalog Integration: The MLflow Deployments server now has an integration with Unity Catalog, allowing you to leverage registered functions as tools for enhancing your chat application. For more information, check out this guide!
• OpenAI Autologging: Autologging support has now been added for the OpenAI model flavor. With this feature, MLflow will automatically log a model upon calling the OpenAI API. Each time a request is made, the inputs and outputs will be logged as artifacts. Check out the guide for more information!

Other Notable Features:

... (truncated)

Changelog

Sourced from mlflow's changelog.

2.14.2 (2024-07-03)

MLflow 2.14.2 is a patch release that includes several important bug fixes and documentation enhancements.

Bug fixes:

• [Models] Fix an issue with requirements inference error handling when disabling the default warning-only behavior (#12547, @​B-Step62)
• [Models] Fix dependency inference issues with Transformers models saved with the unified API llm/v1/xxx task definitions. (#12551, @​B-Step62)
• [Models / Databricks] Fix an issue with MLlfow log_model introduced in MLflow 2.13.0 that causes Databricks DLT service to crash in some situations (#12514, @​WeichenXu123)
• [Models] Fix an output data structure issue with the predict_stream implementation for LangChain AgentExecutor and other non-Runnable chains (#12518, @​B-Step62)
• [Tracking] Fix an issue with the predict_proba inference method in the sklearn flavor when loading an sklearn pipeline object as pyfunc (#12554, @​WeichenXu123)
• [Tracking] Fix an issue with the Tracing implementation where other services usage of OpenTelemetry would activate MLflow tracing and cause errors (#12457, @​B-Step62)
• [Tracking / Databricks] Correct an issue when running dependency inference in Databricks that can cause duplicate dependency entries to be logged (#12493, @​sunishsheth2009)

Documentation updates:

• [Docs] Add documentation and guides for the MLflow tracing schema (#12521, @​BenWilson2)

Small bug fixes and documentation updates:

#12311, #12285, #12535, #12543, #12320, #12444, @​B-Step62; #12310, #12340, @​serena-ruan; #12409, #12432, #12471, #12497, #12499, @​harupy; #12555, @​nojaf; #12472, #12431, @​xq-yin; #12530, #12529, #12528, #12527, #12526, #12524, #12531, #12523, #12525, #12522, @​dbczumar; #12483, @​jsuchome; #12465, #12441, @​BenWilson2; #12450, @​StarryZhang-whu

2.14.1 (2024-06-20)

MLflow 2.14.1 is a patch release that contains several bug fixes and documentation improvements

Bug fixes:

• [Models] Fix params and model_config handling for llm/v1/xxx Transformers model (#12401, @​B-Step62)
• [UI] Fix dark mode user preference (#12386, @​daniellok-db)
• [Docker] Fix docker image failing to build with install_mlflow=False (#12388, @​daniellok-db)

Documentation updates:

• [Docs] Add link to langchain autologging page in doc (#12398, @​xq-yin)
• [Docs] Add documentation for Models from Code (#12381, @​BenWilson2)

Small bug fixes and documentation updates:

#12415, #12396, #12394, @​harupy; #12403, #12382, @​BenWilson2; #12397, @​B-Step62

2.14.0 (2024-06-17)

MLflow 2.14.0 includes several major features and improvements that we're very excited to announce!

Major features:

• MLflow Tracing: Tracing is powerful tool designed to enhance your ability to monitor, analyze, and debug GenAI applications by allowing you to inspect the intermediate outputs generated as your application handles a request. This update comes with an automatic LangChain integration to make it as easy as possible to get started, but we've also implemented high-level fluent APIs, and low-level client APIs for users who want more control over their trace instrumentation. For more information, check out the guide in our docs!
• Unity Catalog Integration: The MLflow Deployments server now has an integration with Unity Catalog, allowing you to leverage registered functions as tools for enhancing your chat application. For more information, check out this guide!
• OpenAI Autologging: Autologging support has now been added for the OpenAI model flavor. With this feature, MLflow will automatically log a model upon calling the OpenAI API. Each time a request is made, the inputs and outputs will be logged as artifacts. Check out the guide for more information!

... (truncated)

Commits

• 20c31eb Run python3 dev/update_mlflow_versions.py pre-release ... (#12566)
• 5b95867 fix reversion
• e1d5f97 Update get_trace() fluent API to fetch trace from backend too (#12311)
• b0cb71d Revert "Databricks SDK doc / error message improvement (#12552)"
• a3f9024 Skip conversational tests for transformers dev (#12310)
• b9956d4 Refactor @trace_disabled implementation (#12285)
• d742cef Update pyfunc_serve_and_score_model to kill process after scoring (#12409)
• 3462aa0 Pin xgboost for FLAML (#12432)
• 0d6086d Document code_paths limitation when loading multiple models (#12471)
• e9bf530 Use editable install in autoformat workflow (#12497)
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