app.py

import gradio as gr
import pandas as pd
import numpy as np
from sklearn.decomposition import TruncatedSVD
import time
from model import MatrixFactorization

try:
    # Load data
    print("Loading data...")
    df = pd.read_csv('data.csv')
    
    # Initialize model
    print("Initializing model...")
    mf_recommender = MatrixFactorization(n_factors=100)
    mf_recommender.fit(df)
    
    # Create interface
    print("Creating interface...")
    demo = mf_recommender.create_interface()
    demo.launch()
    
except Exception as e:
    print(f"Error: {str(e)}")