Bump mlflow from 1.26.1 to 2.6.0

Open dependabot[bot] opened this issue 2 years ago • 1 comments

Bumps mlflow from 1.26.1 to 2.6.0.

Release notes

MLflow 2.6.0 includes several major features and improvements

Features:

[Models / Scoring] Add support for passing extra params during inference for PyFunc models (#9068, @serena-ruan)

[Gateway] Add support for MLflow serving to MLflow AI Gateway (#9199, @BenWilson2)

[Tracking] Support save_kwargs for mlflow.log_figure to specify extra options when saving a figure (#9179, @stroblme)

[Artifacts] Display progress bars when uploading/download artifacts (#9195, @serena-ruan)

[Models] Add support for logging LangChain's retriever models (#8808, @liangz1)

[Tracking] Add support to log customized tags to runs created by autologging (#9114, @thinkall)

Bug fixes:

[Models] Fix text_pair functionality for transformers TextClassification pipelines (#9215, @BenWilson2)

[Models] Fix LangChain compatibility with SQLDatabase (#9192, @dbczumar)

[Tracking] Remove patching sklearn.metrics.get_scorer_names in mlflow.sklearn.autolog to avoid duplicate logging (#9095, @WeichenXu123)

Documentation updates:

[Docs / Examples] Add examples and documentation for MLflow AI Gateway support for MLflow model serving (#9281, @BenWilson2)

[Docs / Examples] Add sentence-transformers doc & example (#9047, @es94129)

Deprecation:

[Models] The mlflow.mleap module has been marked as deprecated and will be removed in a future release (#9311, @BenWilson2)

Small bug fixes and documentation updates:

#9309, #9252, #9198, #9189, #9186, #9184, @BenWilson2; #9307, @AmirAflak; #9285, #9126, @dependabot[bot]; #9302, #9209, #9194, #9187, #9175, #9177, #9163, #9161, #9129, #9123, #9053, @serena-ruan; #9305, #9303, #9271, @KekmaTime; #9300, #9299, @itsajay1029; #9294, #9293, #9274, #9268, #9264, #9246, #9255, #9253, #9254, #9245, #9202, #9243, #9238, #9234, #9233, #9227, #9226, #9223, #9224, #9222, #9225, #9220, #9208, #9212, #9207, #9203, #9201, #9200, #9154, #9146, #9147, #9153, #9148, #9145, #9136, #9132, #9131, #9128, #9121, #9124, #9125, #9108, #9103, #9100, #9098, #9101, @harupy; #9292, @Aman123lug; #9290, #9164, #9157, #9086, @Bncer; #9291, @kunal642; #9284, @NavneetSinghArora; #9286, #9262, #9142, @smurching; #9267, @tungbq; #9258, #9250, @Kunj125; #9167, #9139, #9120, #9118, #9097, @viktoriussuwandi; #9244, #9240, #9239, @Sai-Suraj-27; #9221, #9168, #9130, @gabrielfu; #9218, @tjni; #9216, @Rukiyav; #9158, #9051, @EdAbati; #9211, @scarlettrobe; #9049, @annzhang-db; #9140, @kriscon-db; #9141, @xAIdrian; #9135, @liangz1; #9067, @jmmonteiro; #9112, @WeichenXu123; #9106, @shaikmoeed; #9105, @Ankit8848; #9104, @arnabrahman

MLflow 2.5.0 includes several major features and improvements:

[MLflow AI Gateway] We are excited to announce the release of MLflow AI Gateway, a powerful tool designed to streamline the usage and management of various large language model (LLM) providers, such as OpenAI and Anthropic, within an organization. It offers a standardized interface that simplifies the interaction with these services and delivers centralized, secure management of credentials. To get started with MLflow AI Gateway, check out the docs at https://mlflow.org/docs/latest/gateway/index.html. (#8694, @harupy, @BenWilson2, @dbczumar)

[Auth] We are excited to announce the release of authentication and authorization support for MLflow Tracking and the MLflow Model Registry, providing integrated access control capabilities to both services. To get started, check out the docs at https://mlflow.org/docs/latest/auth/index.html. (#9000, #8975, #8626, #8837, #8841, @gabrielfu, @harupy)

Features:

[Models] Add Support to the LangChain flavor for chains that contain unserializable components (#8736, @liangz1)

[Scoring] Infer spark udf return type from model output schema (#8934, @WeichenXu123)

[Models] Add support for automated signature inference (#8860, #8782 #8795, #8725, @jerrylian-db)

Bug fixes:

[Security] Improve robustness to LFI attacks on Windows by enhancing path validation (#8999, @serena-ruan)

If you are using mlflow server or mlflow ui on Windows, we recommend upgrading to MLflow 2.5.0 as soon as possible.

[Scoring] Support nullable array type values as spark_udf return values (#9014, @WeichenXu123)

[Models] Revert cache deletion of system modules when adding custom model code to the system path (#8722, @trungn1)

[Models] add micro version to mlflow version pinning (#8687, @C-K-Loan)

[Artifacts] Prevent manually deleted artifacts from causing artifact garbage collection to fail (#8498, @PenHsuanWang)

... (truncated)

Changelog

Sourced from mlflow's changelog.

2.6.0 (2023-08-15)

MLflow 2.6.0 includes several major features and improvements

Features:

[Models / Scoring] Add support for passing extra params during inference for PyFunc models (#9068, @serena-ruan)

[Gateway] Add support for MLflow serving to MLflow AI Gateway (#9199, @BenWilson2)

[Tracking] Support save_kwargs for mlflow.log_figure to specify extra options when saving a figure (#9179, @stroblme)

[Artifacts] Display progress bars when uploading/download artifacts (#9195, @serena-ruan)

[Models] Add support for logging LangChain's retriever models (#8808, @liangz1)

[Tracking] Add support to log customized tags to runs created by autologging (#9114, @thinkall)

Bug fixes:

[Models] Fix text_pair functionality for transformers TextClassification pipelines (#9215, @BenWilson2)

[Models] Fix LangChain compatibility with SQLDatabase (#9192, @dbczumar)

[Tracking] Remove patching sklearn.metrics.get_scorer_names in mlflow.sklearn.autolog to avoid duplicate logging (#9095, @WeichenXu123)

Documentation updates:

[Docs / Examples] Add examples and documentation for MLflow AI Gateway support for MLflow model serving (#9281, @BenWilson2)

[Docs / Examples] Add sentence-transformers doc & example (#9047, @es94129)

Deprecation:

[Models] The mlflow.mleap module has been marked as deprecated and will be removed in a future release (#9311, @BenWilson2)

Small bug fixes and documentation updates:

#9309, #9252, #9198, #9189, #9186, #9184, @BenWilson2; #9307, @AmirAflak; #9285, #9126, @dependabot[bot]; #9302, #9209, #9194, #9187, #9175, #9177, #9163, #9161, #9129, #9123, #9053, @serena-ruan; #9305, #9303, #9271, @KekmaTime; #9300, #9299, @itsajay1029; #9294, #9293, #9274, #9268, #9264, #9246, #9255, #9253, #9254, #9245, #9202, #9243, #9238, #9234, #9233, #9227, #9226, #9223, #9224, #9222, #9225, #9220, #9208, #9212, #9207, #9203, #9201, #9200, #9154, #9146, #9147, #9153, #9148, #9145, #9136, #9132, #9131, #9128, #9121, #9124, #9125, #9108, #9103, #9100, #9098, #9101, @harupy; #9292, @Aman123lug; #9290, #9164, #9157, #9086, @Bncer; #9291, @kunal642; #9284, @NavneetSinghArora; #9286, #9262, #9142, @smurching; #9267, @tungbq; #9258, #9250, @Kunj125; #9167, #9139, #9120, #9118, #9097, @viktoriussuwandi; #9244, #9240, #9239, @Sai-Suraj-27; #9221, #9168, #9130, @gabrielfu; #9218, @tjni; #9216, @Rukiyav; #9158, #9051, @EdAbati; #9211, @scarlettrobe; #9049, @annzhang-db; #9140, @kriscon-db; #9141, @xAIdrian; #9135, @liangz1; #9067, @jmmonteiro; #9112, @WeichenXu123; #9106, @shaikmoeed; #9105, @Ankit8848; #9104, @arnabrahman

2.5.0 (2023-07-17)

MLflow 2.5.0 includes several major features and improvements:

[MLflow AI Gateway] We are excited to announce the release of MLflow AI Gateway, a powerful tool designed to streamline the usage and management of various large language model (LLM) providers, such as OpenAI and Anthropic, within an organization. It offers a standardized interface that simplifies the interaction with these services and delivers centralized, secure management of credentials. To get started with MLflow AI Gateway, check out the docs at https://mlflow.org/docs/latest/gateway/index.html. (#8694, @harupy, @BenWilson2, @dbczumar)

[Auth]: We are excited to announce the release of authentication and authorization support for MLflow Tracking and the MLflow Model Registry, providing integrated access control capabilities to both services. To get started, check out the docs at https://mlflow.org/docs/latest/auth/index.html. (#9000, #8975, #8626, #8837, #8841, @gabrielfu, @harupy)

Features:

[Models] Add Support to the LangChain flavor for chains that contain unserializable components (#8736, @liangz1)

[Scoring] Infer spark udf return type from model output schema (#8934, @WeichenXu123)

[Models] Add support for automated signature inference (#8860, #8782 #8795, #8725, @jerrylian-db)

Bug fixes:

[Security] Improve robustness to LFI attacks on Windows by enhancing path validation (#8999, @serena-ruan)

If you are using mlflow server or mlflow ui on Windows, we recommend upgrading to MLflow 2.5.0 as soon as possible.

[Scoring] Support nullable array type values as spark_udf return values (#9014, @WeichenXu123)

... (truncated)

Commits

693b694 Run python3 dev/update_mlflow_versions.py pre-release ... (#9320)
a311052 Run python3 dev/update_pypi_package_index.py (#9317)
cb360c9 Run python3 dev/update_ml_package_versions.py (#9318)
45421d7 Mark mleap as deprecated (#9311)
9dfdbc8 fix docker example to work on OSX (#9309)
3781457 Add examples and documentation for MLflow AI Gateway support for MLflow model...
666cdf3 update: Enable RUF010 (#9307)
d415b9a Bump gitpython from 3.1.29 to 3.1.32 in /.devcontainer (#9285)
0c8e315 Fix link and the example (#9302)
7533642 Enable F402 (#9305)
Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

@dependabot rebase will rebase this PR
@dependabot recreate will recreate this PR, overwriting any edits that have been made to it
@dependabot merge will merge this PR after your CI passes on it
@dependabot squash and merge will squash and merge this PR after your CI passes on it
@dependabot cancel merge will cancel a previously requested merge and block automerging
@dependabot reopen will reopen this PR if it is closed
@dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
@dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
@dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
@dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
@dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

Aug 21 '23 18:08 dependabot[bot]

All committers have signed the CLA.

Nov 27 '23 20:11 CLAassistant