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Add optimization backend APIs to auth control#20392

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chenmoneygithub merged 4 commits intomlflow:masterfrom
chenmoneygithub:prompt-optimization-auth
Feb 2, 2026
Merged

Add optimization backend APIs to auth control#20392
chenmoneygithub merged 4 commits intomlflow:masterfrom
chenmoneygithub:prompt-optimization-auth

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@chenmoneygithub chenmoneygithub commented Jan 28, 2026 •
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Related Issues/PRs

#xxx

What changes are proposed in this pull request?

Add optimization backend APIs to auth control. We are using the experiment permission for the optimization APIs.

Tested manually that all 5 APIs can function properly.

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/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)

Copilot AI review requested due to automatic review settings January 28, 2026 03:32
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github-actions bot commented Jan 28, 2026

🛠 DevTools 🛠

Install mlflow from this PR

# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/20392/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/20392/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/20392/merge

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github-actions bot commented Jan 28, 2026

@chenmoneygithub Thank you for the contribution! Could you fix the following issue(s)?

⚠ DCO check

The DCO check failed. Please sign off your commit(s) by following the instructions here. See https://github.com/mlflow/mlflow/blob/master/CONTRIBUTING.md#sign-your-work for more details.

Copilot AI reviewed Jan 28, 2026
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Pull request overview

This pull request adds authorization controls for prompt optimization backend APIs by integrating them with MLflow's existing authentication and permission system.

Changes:

  • Added imports for five new protobuf message types related to prompt optimization jobs
  • Implemented three validation functions that check permissions based on experiment permissions (since optimization jobs inherit from parent experiment)
  • Added route mappings for five prompt optimization job API endpoints to their corresponding permission validators

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@github-actions github-actions bot added area/prompts MLflow Prompt Registry and Optimization rn/feature Mention under Features in Changelogs. labels Jan 28, 2026
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github-actions bot commented Jan 28, 2026 •
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Documentation preview for 3cf8f3c is available at:

Changed Pages (1)

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.

WeichenXu123
WeichenXu123 reviewed Jan 28, 2026
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could you add some unit tests in tests/server/auth/test_auth.py ?

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TomeHirata commented Jan 28, 2026

Can we update documentation too?

chenmoneygithub
chenmoneygithub commented Jan 28, 2026
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tests/server/auth/test_auth.py
).raise_for_status()


def test_prompt_optimization_job_search_permissions(client, monkeypatch):
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@chenmoneygithub chenmoneygithub Jan 28, 2026

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Testing the Get/Cancel/Delete requires creating actual prompt optimization jobs, which is a bit too heavy. Relying on manual testing for those APIs.

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Can't we test them by mocking submit_job and get_job?

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Yes I did look into the mock approach and it won't work because the server is running in a separate process (test_auth.py is an integration test, not a unit test)

WeichenXu123
WeichenXu123 approved these changes Feb 2, 2026
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LGTM!

@chenmoneygithub chenmoneygithub added this pull request to the merge queue Feb 2, 2026
Merged via the queue into mlflow:master with commit 60835ad Feb 2, 2026
47 of 50 checks passed
@chenmoneygithub chenmoneygithub deleted the prompt-optimization-auth branch February 2, 2026 07:18
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@WeichenXu123 WeichenXu123 WeichenXu123 approved these changes

@harupy harupy Awaiting requested review from harupy

@TomeHirata TomeHirata Awaiting requested review from TomeHirata

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@WeichenXu123 WeichenXu123

@TomeHirata TomeHirata

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