[BUG]: Unable to deploy a ML model locally to MLFlow about zenml HOT 4 OPEN

@PriyanshBhardwaj

The inconsistent type naming between the model deployer registration and the MLFlowDeploymentService definition could also be contributing to this issue.
One thing you try is to register the MLFLow model deployer as

zenml model-deployer register mlflow --type=model-serving --flavor=mlflow

As it's defined in ServiceType as:

SERVICE_TYPE = ServiceType(
        name="mlflow-deployment",
        type="model-serving",
        flavor="mlflow",
        description="MLflow prediction service",
    )

Or we can change the type in src\zenml\integrations\mlflow\services\mlflow_deployment.py on line 128 to just mlflow rather than mlflow-serving.
So that the service type name matches what is defined in the MLFlowDeploymentService class.
This can contribute to the issue you are facing.

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@Vishal-Padia thanks for your response.

zenml model-deployer register mlflow --type=model-serving --flavor=mlflow
this will not work as --type is an extra field in model deployer registration as you can see in the error below. I tried it because I saw it in some old docs.

ValidationError: 1 validation error for MLFlowModelDeployerConfig
type
  extra fields not permitted (type=value_error.extra)

for your 2nd solution, I tried it but it didn't work.

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@PriyanshBhardwaj
okay, I got it.
I guess Alex will be able to zero-down on the issue!

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Hello @PriyanshBhardwaj , sorry about the delay!

As I learned from the info provided you install mlflow using pip directly, which might not work well with zenml due to version mismatch. Moreover mlflow integration also pulls important components for model deployment, the full list is (for 0.53.1 version you used): 'mlflow>=2.1.1,<=2.9.2', 'mlserver>=1.3.3', 'mlserver-mlflow>=1.3.3'.

Can you do the following and retest?

pip3 uninstall mlflow
zenml integration install mlflow -y

Moreover, forking on MacOS might not be working always smoothly, if OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES is not set, so also ensure that this ENV is properly set before rerunning.

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