Remove unnecessary STATIC_DIR variable

[eliaskoromilas]

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

This pull request removes the redundant intermediate variable STATIC_DIR that stores the full path to the js/build directory. Functions now use directly the app.static_folder variable, which stores the same value (both in Flask 1.x and 2.x), but also allows it to be easily/dynamically configurable by downstream UI apps. In other words, it enables custom UI providers to change the path to the front-end build directory without changing the back-end configuration (i.e. Flask routes), like this:

from mlflow.server import app

app.root_path = '/path/to/custom/root/path/with/custom/js/build'

How is this patch tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests (describe details, including test results, below)

Does this PR change the documentation?

• No. You can skip the rest of this section.
• Yes. Make sure the changed pages / sections render correctly in the documentation preview.

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.

(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)

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/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/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• 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/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

[harupy]

LGTM!

[harupy]

Manually confirmed the UI launches fine.

[mlflow-automation]

Documentation preview for f7e8a5b will be available here when this CircleCI job completes successfully.

More info

• Ignore this comment if this PR does not change the documentation.
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• The preview is updated when a new commit is pushed to this PR.
• This comment was created by https://github.com/mlflow/mlflow/actions/runs/5056393461.