Fix model config logging for Langchain autologging

[B-Step62]

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Install mlflow from this PR

pip install git+https://github.com/mlflow/mlflow.git@refs/pull/11890/merge

Checkout with GitHub CLI

gh pr checkout 11890

Related Issues/PRs

#11880 introduced logging for model_config as params. However, the log_params call does not adhere the run_id argument passed to the parent function and always tries to log to active run (create if not exists). This breaks special cases like LangChain autologging where the logging function is called for non active run.

What changes are proposed in this pull request?

This PR fixes the issue by propagating run_id argument to log_params function.

How is this PR tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests

Does this PR require documentation update?

• No. You can skip the rest of this section.
• Yes. I've updated:
  • Examples
  • API references
  • Instructions

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

What component(s), interfaces, languages, and integrations does this PR affect?

Components

• area/artifacts: Artifact stores and artifact logging
• area/build: Build and test infrastructure for MLflow
• area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

Interface

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

Language

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

Integrations

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

• rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
• rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
• rn/documentation - A user-facing documentation change worth mentioning in the release notes

Should this PR be included in the next patch release?

Yes should be selected for bug fixes, documentation updates, and other small changes. No should be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.

What is a minor/patch release?

• Minor release: a release that increments the second part of the version number (e.g., 1.2.0 -> 1.3.0).
  Bug fixes, doc updates and new features usually go into minor releases.
• Patch release: a release that increments the third part of the version number (e.g., 1.2.0 -> 1.2.1).
  Bug fixes and doc updates usually go into patch releases.

• Yes (this PR will be cherry-picked and included in the next patch release)
• No (this PR will be included in the next minor release)

[B-Step62]

/cross-version-test langchain

[github-actions]

Cross-version test run started: https://github.com/mlflow/mlflow/actions/runs/8932551060

[B-Step62]

Cross-version test run started: https://github.com/mlflow/mlflow/actions/runs/8932551060

It seems this job checks out from the master branch not this PR🤔 (and thus we can see the failure)

Triggered jobs by a dummy commit like we had been doing back then: https://github.com/mlflow/mlflow/actions/runs/8932672191/job/24536883476?pr=11890

[daniellok-db]

mistake?

[B-Step62]

Ah this one is only for triggering cross version test, and was intended to be reverted after cross-version test🙃

[daniellok-db]

ahh right! i guess we can use the new /cross-version-test command for this too

[daniellok-db]

oh wait sorry i just saw the above, ignore me

[daniellok-db]

lgtm pending the _FOO!

[BenWilson2]

Great fix! TY!!!