from mlflow.models.signature import infer_signature
signature = infer_signature(X_train, y_train)

import mlflow.sklearn
nom_model = 'mlfow_model'
mlflow.sklearn.save_model(pipeline, nom_model, signature=signature)
print(f"mlflow models serve -m {nom_model}/") # avec conda
print(f"mlflow models serve -m {nom_model}/ --env-manager=local") # Sans conda

# avec conda
print(f"mlflow models serve -m {nom_model}/") 
# Sans conda
print(f"mlflow models serve -m {nom_model}/ --env-manager=local") 

print('streamlit run myfile.py')

TODO