Something like this with numerical integration using torch.trapz?
import torch
from torch.distributions import Beta

conc1, conc0 = 2.0, 3.0
bt = Beta(conc1, conc0)
def beta_cdf(b, npts=100):
    x = torch.linspace(0, b, npts)
    return torch.trapz(bt.log_prob(x).exp(), x)
beta_cdf(0.65)