# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/19067/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/19067/merge#subdirectory=libs/skinny

%sh curl -LsSf https://raw.githubusercontent.com/mlflow/mlflow/HEAD/dev/install-skinny.sh | sh -s pull/19067/merge

🥞 Stacked PR

Use this link to review incremental changes.

What changes are proposed in this pull request?

Update required_column to "trace" for session level scorers to prevent the following warning when running with genai.evaluate:

INFO mlflow.genai.scorers.validation: The input data is missing following columns that are required by the specified scorers. The results will be null for those scorers.
 - `session` column is required by [conversation_completeness].

How is this PR tested?

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

Manual Test:

Tested with

  traces = mlflow.search_traces(
      experiment_ids=[experiment_id],
      filter_string=f"metadata.`mlflow.trace.session` = '{session_id}'",
      return_type="list",
  )

  result_df = mlflow.genai.evaluate(
      data = traces,
      scorers = [conversation_completeness_scorer],
  ).result_df

  print(result_df[['trace_id', 'conversation_completeness/value']])

Before:

INFO mlflow.genai.scorers.validation: The input data is missing following columns that are required by the specified scorers. The results will be null for those scorers.
 - `session` column is required by [conversation_completeness].
trace_id conversation_completeness/value
0  tr-2cd106b40e5cdfddffede040e34789a5                             NaN
1  tr-0a9f70b110b6f7045858228d6a2c74b1                             yes
2  tr-4c63218e359c30170fb7324f2177a035                             NaN
3  tr-e234aea83059823beadb90f0a7f0909f                             NaN
4  tr-2e2d728503c6f3de878c34c9d1b0f4dc                             NaN
5  tr-26d0ea33568b18301be944295fcc971a                             NaN
6  tr-f79ea6c663980841141961b6fac02f16                             NaN
7  tr-af8fb72cc9cd5d2f6637b416f7553289                             NaN
8  tr-713501bcb3c5b94211bec6d25a43b663                             NaN
9  tr-f319a35c635c3f308aee8257280b43ec                             NaN

After:

trace_id conversation_completeness/value
0  tr-843c1b545b861979e728a87d893878b3                             NaN
1  tr-d243d1f989fcea071b540173fbe655a7                             NaN
2  tr-f5e77a3d65d4174a96ca2374f9490b17                             NaN
3  tr-fd9e209b519417499b6397f9b2a1eab2                             NaN
4  tr-c125efb43121c5e40b247ddcfe806556                             NaN
5  tr-a70d40defd74b98a570dd50a2c8b8b55                             NaN
6  tr-2dcfdd2dde5863633b89c5de8ed87f86                             yes
7  tr-5ff410c5001376d5644a512890e59943                             NaN
8  tr-61365b536fc86e28c7d22c4fd38d7a9d                             NaN
9  tr-50dd9f34c727d17a3e79d94c9964e01b                             NaN

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/tracking: Tracking Service, tracking client APIs, autologging
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
• area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
• area/prompts: MLflow prompt engineering features, prompt templates, and prompt management
• area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
• area/projects: MLproject format, project running backends
• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages

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.

• 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)