import scipy.stats
import numpy as np
import gradio as gr
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')

theta = np.linspace(0, 1, 100)

def plot_beta(alpha, beta):
    plt.gca().cla()
    plt.plot(theta, scipy.stats.beta.pdf(theta, alpha, beta))
    plt.ylim(0, 4)
    plt.xlabel('$\\theta$')
    plt.ylabel('pdf value')
    plt.tight_layout()
    return plt

s1 = gr.inputs.Slider(minimum=0, maximum=5, step=0.1, default=2, label="alpha")
s2 = gr.inputs.Slider(minimum=0, maximum=5, step=0.1, default=2, label="beta")

iface = gr.Interface(fn=plot_beta, inputs=[s1, s2], outputs="image", live=True)
iface.launch()