SeldonIO / MLServer

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
https://mlserver.readthedocs.io/en/latest/
Apache License 2.0
726 stars 183 forks source link

build(deps): bump mlflow from 2.16.2 to 2.17.0 in /runtimes/mlflow #1924

Closed dependabot[bot] closed 1 month ago

dependabot[bot] commented 1 month ago

Bumps mlflow from 2.16.2 to 2.17.0.

Release notes

Sourced from mlflow's releases.

MLflow 2.17.0rc0 is a release candidate for 2.17.0. To install, run the following command:

pip install mlflow==2.17.0rc0

We are excited to announce the release candidate for MLflow 2.17.0. This release includes several enhancements to extend the functionality of MLflow's ChatModel interface to further extend its versatility for handling custom GenAI application use cases. We're also starting the work on improving both the utility and the versatility of MLflow's evaluate functionality for GenAI, initially with support for callable GenAI evaluation metrics.

Please try it out and report any issues on the issue tracker.

Major Features and notifications

  • ChatModel enhancements - As the GenAI-focused 'cousin' of PythonModel, ChatModel is getting some sizable functionality extensions. From native support for tool calling (a requirement for creating a custom agent), simpler conversions to the internal dataclass constructs needed to interface with ChatModel via the introduction of from_dict methods to all data structures, the addition of a metadata field to allow for full input payload customization, handling of the new refusal response type, to the inclusion of the interface type to the response structure to allow for greater integration compatibility. (#13191, #13180, #13143, @​daniellok-db, #13102, #13071, @​BenWilson2)

  • Callable GenAI Evaluation Metrics - As the intial step in a much broader expansion of the functionalities of mlflow.evaluate for GenAI use cases, we've converted the GenAI evaluation metrics to be callable. This allows you to use them directly in packages that support callable GenAI evaluation metrics, as well as making it simpler to debug individual responses when prototyping solutions. (#13144, @​serena-ruan)

  • Audio file support in the MLflow UI - You can now directly 'view' audio files that have been logged and listen to them from within the MLflow UI's artifact viewer pane. (#13017, @​sydneyw-spotify)

  • MLflow AI Gateway is no longer deprecated - We've decided to revert our deprecation for the AI Gateway feature. We had renamed it to the MLflow Deployments Server, but have reconsidered and reverted the naming and namespace back to the original configuration.

Features:

Bug fixes:

  • [Tracking] Fix tracing for LangGraph (#13215, @​B-Step62)
  • [Model Registry] Fix retry and credential refresh issues with artifact downloads from the model registry (#12935, @​rohitarun-db)
  • [Tracking] Fix LangChain autologging so that langchain-community is not required for partner packages (#13172, @​B-Step62)
  • [Artifacts] Fix issues with file removal for the local artifact repository (#13005, @​rzalawad)

Documentation updates:

... (truncated)

Changelog

Sourced from mlflow's changelog.

2.17.0 (2024-09-26)

We are excited to announce the release of MLflow 2.17.0! This release includes several enhancements to extend the functionality of MLflow's ChatModel interface to further extend its versatility for handling custom GenAI application use cases. Additionally, we've improved the interface within the tracing UI to provide a structured output for retrieved documents, enhancing the ability to read the contents of those documents within the UI. We're also starting the work on improving both the utility and the versatility of MLflow's evaluate functionality for GenAI, initially with support for callable GenAI evaluation metrics.

Major Features and notifications:

  • ChatModel enhancements - As the GenAI-focused 'cousin' of PythonModel, ChatModel is getting some sizable functionality extensions. From native support for tool calling (a requirement for creating a custom agent), simpler conversions to the internal dataclass constructs needed to interface with ChatModel via the introduction of from_dict methods to all data structures, the addition of a metadata field to allow for full input payload customization, handling of the new refusal response type, to the inclusion of the interface type to the response structure to allow for greater integration compatibility. (#13191, #13180, #13143, @​daniellok-db, #13102, #13071, @​BenWilson2)

  • Callable GenAI Evaluation Metrics - As the intial step in a much broader expansion of the functionalities of mlflow.evaluate for GenAI use cases, we've converted the GenAI evaluation metrics to be callable. This allows you to use them directly in packages that support callable GenAI evaluation metrics, as well as making it simpler to debug individual responses when prototyping solutions. (#13144, @​serena-ruan)

  • Audio file support in the MLflow UI - You can now directly 'view' audio files that have been logged and listen to them from within the MLflow UI's artifact viewer pane.

  • MLflow AI Gateway is no longer deprecated - We've decided to revert our deprecation for the AI Gateway feature. We had renamed it to the MLflow Deployments Server, but have reconsidered and reverted the naming and namespace back to the original configuration.

Features:

Bug fixes:

  • [Tracking] Fix tracing for LangGraph (#13215, @​B-Step62)
  • [Tracking] Fix an issue with presigned_url_artifact requests being in the wrong format (#13366, @​WeichenXu123)
  • [Models] Update Databricks dependency extraction functionality to work with the langchain-databricks partner package. (#13266, @​B-Step62)
  • [Model Registry] Fix retry and credential refresh issues with artifact downloads from the model registry (#12935, @​rohitarun-db)
  • [Tracking] Fix LangChain autologging so that langchain-community is not required for partner packages (#13172, @​B-Step62)

... (truncated)

Commits


Dependabot compatibility score

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 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)