app.py

import streamlit as st
from surprise import SVD
import pandas as pd
import pickle

# Load data back from the file
with open('svd_model.pkl', 'rb') as file:
    svd_model, merged_data, movies = pickle.load(file)

# Title for the app
st.title("Movie Recommendations")

# User input for user ID
user_id = st.number_input("Enter User ID", min_value=1, step=1)

# Get rated and unrated movies for the given user
rated_user_movies = merged_data[merged_data['userId'] == user_id]['title'].values
unrated_movies = movies[~movies['title'].isin(rated_user_movies)]['title']

# Make predictions on unrated movies
pred_ratings = [svd_model.predict(user_id, movie_id) for movie_id in unrated_movies]

# Sort predictions by estimated rating in descending order
sorted_predictions = sorted(pred_ratings, key=lambda x: x.est, reverse=True)

# Get top 10 movie recommendations
top_recommendations = sorted_predictions[:10]

# Display recommendations
st.write(f"\nTop 10 movie recommendations for User {user_id}:")
for recommendation in top_recommendations:
    movie_title = movies[movies['title'] == recommendation.iid]['title'].values[0]
    st.write(f"{movie_title} (Estimated Rating: {recommendation.est})")