mlflow: [BUG] Error when opening the registered-models page on the UI due to a file store backend

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Willingness to contribute

The MLflow Community encourages bug fix contributions. Would you or another member of your organization be willing to contribute a fix for this bug to the MLflow code base?

• Yes. I can contribute a fix for this bug independently.
• Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.
• No. I cannot contribute a bug fix at this time.

System information

• Have I written custom code (as opposed to using a stock example script provided in MLflow):
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
• MLflow installed from (source or binary):
• MLflow version (run mlflow --version):
• Python version:
• npm version, if running the dev UI:
• Exact command to reproduce:

Describe the problem

Describe the problem clearly here. Include descriptions of the expected behavior and the actual behavior.

When I tried to open the registered-models page on the UI, I got an error.

The error is caused by a failed API request to get registered models (/2.0/preview/mlflow/registered-models/list) and the response says:

{
  "error_code": "INVALID_PARAMETER_VALUE",
  "message": "Invalid value for request parameter max_results.It must be at most 1000, but got value 50000"
}

It looks like list_registered_models calls search_registered_models with max_results = 50000 which exceeds SEARCH_REGISTERED_MODEL_MAX_RESULTS_DEFAULT (= 1000). I’m not sure if this is the right approach but specifying max_results in model-registry/actions.js solves the error.

# model-registry/actions.js
export const listRegisteredModelsApi = (id = getUUID()) => ({
  type: LIST_REGISTRED_MODELS,
  payload: wrapDeferred(Services.listRegisteredModels, { max_results: 1000 }),
  meta: { id },
});

Code to reproduce issue

Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs

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What component(s), interfaces, languages, and integrations does this bug 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/projects: MLproject format, project running backends
• area/scoring: Local serving, model deployment tools, spark UDFs
• area/tracking: Tracking Service, tracking client APIs, autologging

Interface

• area/uiux: Front-end, user experience, JavaScript, plotting
• 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

Integrations

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