app.py

import pandas as pd
import streamlit as st
import pickle

def recommend(movie):
    movie_index =movies[movies['title'] == movie].index[0]
    distances = similarity[movie_index]
    movies_list = sorted(list(enumerate(distances)), reverse=True, key=lambda x: x[1])[1:6]
    recommended_movies=[]
    for i in movies_list:
        movie_id=i[0]
        
        recommended_movies.append(movies.iloc[i[0]].title)
    return recommended_movies

movie_dict = pickle.load(open('movies.pkl','rb'))
movies=pd.DataFrame(movie_dict)

similarity=pickle.load(open('similarity.pkl','rb'))

st.title('movie recommender system')

option=st.selectbox(
'Choose a movie to find similar ones', movies['title'].values
)

if st.button('Recommend'):
    recommendations=recommend(option)
    for i in recommendations:
        st.write(i)