Usage of MLFlow models inside Streamlit app in Databricks
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12-24-2025 09:50 AM
I have an issue with loading registered MLflow model into streamlit app inside the Databricks
This is the sample code used for model load:
import mlflow
from mlflow.tracking import MlflowClient
mlflow.set_tracking_uri("databricks")
mlflow.set_registry_uri("databricks-uc")
client = MlflowClient()
model_uri = "models:/workspace.default.xgboost_units/2"
model = mlflow.pyfunc.load_model(model_uri=model_uri)
The streamlit app served with the databricks app is failing silently loading this model, why the same code inside the databricks python notebook is working without any issues.
Any thoughts what can be the reason? Or maybe there is sample app which uses MLflow models successfully?
mlflow==2.22.0 in both envs
The streamlit app served with the databricks app is failing silently loading this model, why the same code inside the databricks python notebook is working without any issues.
Any thoughts what can be the reason? Or maybe there is sample app which uses MLflow models successfully?
mlflow==2.22.0 in both envs
