[Python] How to implement cloudiness impact in clear_sky function?

Using latitude and longitude, I can calculate solar irradiance for a clear sky using the pvlib clear_sky. If I'm not mistaken, this function doesn't account for cloud cover. How can I implement a reduction in solar irradiance based on this parameter? This value is easily obtained from meteorology websites and ranges from 100 (completely cloudy) to 0 (clear sky).

Below is part of the code that generates GHI, DNI, and DHI data for clear sky conditions.

import pvlib
import pandas as pd

location = pvlib.location.Location(latitude=54, longitude=16)
times = pd.date_range('2024-01-01', periods=24*365, freq='H', tz='Europe/Warsaw')
solpos = location.get_solarposition(times)
clearsky = location.get_clearsky(times, model='ineichen')
clearsky.plot(subplots=True)




I saw that in previous versions there was a function that took this parameter into account, but it seems that it is no longer supported.

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