import pickle import streamlit as st import requests def fetch_poster(movie_id): url = "https://api.themoviedb.org/3/movie/{}?api_key=8265bd1679663a7ea12ac168da84d2e8&language=en-US".format(movie_id) data = requests.get(url) data = data.json() poster_path = data['poster_path'] full_path = "https://image.tmdb.org/t/p/w500/" + poster_path return full_path def recommend(movie): index = movies[movies['title'] == movie].index[0] distances = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda x: x[1]) recommended_movie_names = [] recommended_movie_posters = [] for i in distances[1:6]: # fetch the movie poster movie_id = movies.iloc[i[0]].movie_id recommended_movie_posters.append(fetch_poster(movie_id)) recommended_movie_names.append(movies.iloc[i[0]].title) return recommended_movie_names,recommended_movie_posters st.markdown("

Movie Recommender System

", unsafe_allow_html=True) st.markdown("

Find a similar movie from a dataset of 5,000 movies!

", unsafe_allow_html=True) st.markdown("

Web App created by Sagar Bapodara

", unsafe_allow_html=True) movies = pickle.load(open('movies.pkl','rb')) similarity = pickle.load(open('similarity.pkl','rb')) movie_list = movies['title'].values selected_movie = st.selectbox( "Type or select a movie you like :", movie_list ) if st.button('Show Recommendation'): st.write("Recommended Movies based on your interests are :") recommended_movie_names,recommended_movie_posters = recommend(selected_movie) col1, col2, col3, col4, col5 = st.columns(5) with col1: st.text(recommended_movie_names[0]) st.image(recommended_movie_posters[0]) with col2: st.text(recommended_movie_names[1]) st.image(recommended_movie_posters[1]) with col3: st.text(recommended_movie_names[2]) st.image(recommended_movie_posters[2]) with col4: st.text(recommended_movie_names[3]) st.image(recommended_movie_posters[3]) with col5: st.text(recommended_movie_names[4]) st.image(recommended_movie_posters[4]) st.title(" ") # st.write("The code for this recommender system is available [here](https://share.streamlit.io/mesmith027/streamlit_webapps/main/MC_pi/streamlit_app.py)")