[BUG] Pydantic warning: Field "model_server_url" has conflict with protected namespace "model_"

[aldanor]

Issues Policy acknowledgement

• I have read and agree to submit bug reports in accordance with the issues policy

Where did you encounter this bug?

Local machine

Willingness to contribute

No. I cannot contribute a bug fix at this time.

MLflow version

• Client: 2.8.0
• Tracking server: 2.8.0

System information

• OS Platform and Distribution: macOS
• Python version: 3.11.5

Describe the problem

Both the client and the UI always emit the following two warnings:

pydantic/_internal/_fields.py:127: UserWarning:
Field "model_server_url" has conflict with protected namespace "model_".
You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.

pydantic/_internal/_config.py:269: UserWarning:
Valid config keys have changed in V2:
* 'schema_extra' has been renamed to 'json_schema_extra'

Given that model_* attributes have special meaning in pydantic, I guess it's complaining about model_server_url not being explicitly whitelisted somewhere. And in the second warning, a deprecated schema_extra is being accessed instead of the new json_schema_extra.

Tracking information

REPLACE_ME

Code to reproduce issue

REPLACE_ME

Stack trace

REPLACE_ME

Other info / logs

REPLACE_ME

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/gateway: AI Gateway service, Gateway client APIs, third-party Gateway integrations
• 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

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

[nomomon]

I have the same warning

[github-actions]

@mlflow/mlflow-team Please assign a maintainer and start triaging this issue.

[MountassirEl]

same issue

[laineil]

I encountered the same issue, which seems related to pydantic. Rolling back pydantic from version v2.5.1 to v1.10.13 resolved the warning for me.

[sinberlin2]

I have the same problem with pydantic 2.0

[sinberlin2]

The issue disappears when instaling pydantic with conda (conda install pydantic -c conda-forge)

[asanglard]

same issue here

[tkaraouzene]

Hi same issue for me too

[4pygmalion]

same issue

[juliusaka]

same issue here

[amoosebitmymom]

same issue here

[B-Step62]

For those who still encountered this issue, could you try updating MLflow to the latest version? We have released a patch in v2.9.0: #10483