app.py

import gradio as gr  
from gradio.components import File
import pandas as pd
from sklearn.linear_model import LogisticRegression

def classify(data):
    df = pd.read_csv(data)  
    X = df.drop('y', axis=1)
    y = df['y']   
    
    model = LogisticRegression()
    model.fit(X, y)  
    
    return model.predict(X)

demo = gr.Interface(fn=classify,    
                    inputs=File(),
                    outputs="label")

if __name__ == "__main__":
    demo.launch()