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Add an SDK for search sessions to get complete sessions#20288

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B-Step62 merged 8 commits intomlflow:masterfrom
smoorjani:gwt-search-sessions
Feb 2, 2026
Merged

Add an SDK for search sessions to get complete sessions#20288
B-Step62 merged 8 commits intomlflow:masterfrom
smoorjani:gwt-search-sessions

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@smoorjani smoorjani commented Jan 23, 2026

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

This PR introduces a search_sessions API proposed to ensure we can get full conversations which is a gap in the current search_traces API which does not guarantee completeness.

How is this PR tested?

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

mlflow.set_tracking_uri("databricks")
experiment_id = "3011836326718646"

print(f"Searching sessions in experiment {experiment_id}...")

sessions = mlflow.search_sessions(
    locations=[experiment_id],
    max_results=5,
)

print(f"Found {len(sessions)} sessions")

for i, session in enumerate(sessions):
    print(f"Session {i + 1}: {len(session)} traces")
    for trace in session:
        session_id = trace.info.request_metadata.get("mlflow.trace.session", "N/A")
        print(f"  - Trace ID: {trace.info.trace_id}, Session ID: {session_id}")
    print()

Result:
image

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.

Add an SDK for search sessions to get complete sessions from an experiment.

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.

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)

Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
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🛠 DevTools 🛠

Install mlflow from this PR

# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/20288/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/20288/merge#subdirectory=libs/skinny

For Databricks, use the following command:

%sh curl -LsSf https://raw.githubusercontent.com/mlflow/mlflow/HEAD/dev/install-skinny.sh | sh -s pull/20288/merge

@github-actions github-actions bot added area/tracing MLflow Tracing and its integrations rn/feature Mention under Features in Changelogs. labels Jan 23, 2026
@smoorjani smoorjani requested a review from B-Step62 January 23, 2026 21:46
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@B-Step62 I'm going to do docs as a follow-up, but curious if you think we should document this standalone (similar to the search traces page) or if we should just reference it in multi-turn docs and rely on API reference? It is not the most efficient API + is experimental.

.
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
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github-actions bot commented Jan 23, 2026

Documentation preview for 5f358ee is available at:

More info
  • Ignore this comment if this PR does not change the documentation.
  • The preview is updated when a new commit is pushed to this PR.
  • This comment was created by this workflow run.
  • The documentation was built by this workflow run.

Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
.
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>

# Flatten sessions for evaluation if needed
all_traces = [trace for session in sessions for trace in session]
mlflow.genai.evaluate(data=all_traces)
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@smoorjani smoorjani Jan 24, 2026

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@B-Step62 one thought here - should we make evaluate take a list[list[trace]]? Not sure if I'll keep this example in the current state as it requires flattening.

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@B-Step62 B-Step62 Jan 30, 2026

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I think that's a good idea, maybe not too urgent tho given list[trace] doesn't have a lot of usage today.

Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
.
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
@smoorjani smoorjani requested a review from B-Step62 January 30, 2026 06:32
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
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LGTM! Can you address #20288 (comment) in a follow-up?

@B-Step62 B-Step62 added this pull request to the merge queue Feb 2, 2026
Merged via the queue into mlflow:master with commit 41e4a5f Feb 2, 2026
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