Dynamic Regression Prediction with Flask(or sth. similar)
This seems more like an ETL job than an API one. Of course you can have both, but in your specific case I would design it as a series of tasks where each task you extract, transform and load data.
Airflow is an amazing tool for that: https://github.com/apache/airflow
In airflow, each ETL is defined as a DAG (directed acyclic graph) with a series of tasks that are customized by you.
So, for your specific case, you would create a DAG with following tasks:

Retrieve data, prep if necessary.
Make predictions
Save new dataset predictions.csv.

You can schedule it like a cron job to run at each 2 hours. I highly recommend you to look at.