[BUG]mlflow gc command raise exception when serve-artifacts as local file

Willingness to contribute

Yes. I can contribute a fix for this bug independently.

System information

• Have I written custom code (as opposed to using a stock example script provided in MLflow): no
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 20.04
• MLflow installed from (source or binary): binary
• MLflow version (run mlflow --version): 1.25.1
• Python version: 3.9
• npm version, if running the dev UI: None

Describe the problem

mlflow gc command raise exception when serve-artifacts as local file

my solution is add code to mlflow/mlflow/store/artifact/mlflow_artifacts_repo.py line 61

        # if uri is file, return the artifacts under "./mlartifacts", same fold with mlruns
        if track_parse.scheme == "file":

            return os.path.join(os.path.dirname(track_parse.path),"mlartifacts",uri_parse.path[1:])

Tracking information

No response

Code to reproduce issue

cd ./mlflow-root
mlflow server -h 0.0.0.0 -p 18888 --serve-artifacts

after delete mlflow-runs and under mlflow-root then use

mlflow gc

Other info / logs

Traceback (most recent call last):
  File "/opt/anaconda3/envs/mlflow/bin/mlflow", line 8, in <module>
    sys.exit(cli())
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/click/core.py", line 1128, in __call__
    return self.main(*args, **kwargs)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/click/core.py", line 1053, in main
    rv = self.invoke(ctx)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/click/core.py", line 1659, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/click/core.py", line 1395, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/click/core.py", line 754, in invoke
    return __callback(*args, **kwargs)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/mlflow/cli.py", line 489, in gc
    artifact_repo = get_artifact_repository(run.info.artifact_uri)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/mlflow/store/artifact/artifact_repository_registry.py", line 107, in get_artifact_repository
    return _artifact_repository_registry.get_artifact_repository(artifact_uri)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/mlflow/store/artifact/artifact_repository_registry.py", line 73, in get_artifact_repository
    return repository(artifact_uri)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/mlflow/store/artifact/mlflow_artifacts_repo.py", line 46, in __init__
    super().__init__(self.resolve_uri(artifact_uri, get_tracking_uri()))
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/mlflow/store/artifact/mlflow_artifacts_repo.py", line 61, in resolve_uri
    _validate_uri_scheme(track_parse.scheme)
  File "/opt/anaconda3/envs/mlflow/lib/python3.9/site-packages/mlflow/store/artifact/mlflow_artifacts_repo.py", line 35, in _validate_uri_scheme
    raise MlflowException(
mlflow.exceptions.MlflowException: The configured tracking uri scheme: 'file' is invalid for use with the proxy mlflow-artifact scheme. The allowed tracking schemes are: {'https', 'http'}

What component(s) does this bug affect?

• 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/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

What interface(s) does this bug affect?

• 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

What language(s) does this bug affect?

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

What integration(s) does this bug affect?

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

[vanIvan]

Had the same error. Was able to fix this by calling mlflow.set_tracking_uri(tracking_uri) before any call to mlflow API on client side (error caused by mlflow call to get_tracking_uri() and getting default tracking_uri, which has file schema):

tracking_uri = os.environ["MLFLOW_TRACKING_URL"]
mlflow.set_tracking_uri(tracking_uri)
logger = MLFlowLogger(
    run_name=run_name,
    experiment_name=experiment_name, 
    tracking_uri=tracking_uri
)  

[DraXus]

Thanks @okoben, setting MLFLOW_TRACKING_URI also fixed my issue.