How to use mlflow to log a composite estimator (multiple pipes) and then deploy it as rest endpoint

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Hello,

I am trying to deploy a composite estimator as single model, by logging the run with mlflow and registering the model.

Can anyone help with how this can be done? This estimator contains different chains-

text: data- tfidf- svm- svm.decision_function- text_dense matrix
cat: data- encoding- scaling- cat_ matrix
Light GBM- gets both concatenated (text_dense matrix, cat_ matrix)

I am using different pipelines for this, as its not possible to create a single transformer/pipe. below is the model blueprint. I need to train and deploy model on a databricks serving enpoint