added app.py

app.py

@@ -0,0 +1,59 @@
+import streamlit as st
+import pickle
+import requests
+
+
+# function to fetch the poster
+def fetch_poster(movie_id):
+    response = requests.get(f"https://api.themoviedb.org/3/movie/{movie_id}?api_key=bb1678d9f4f581a1a07e8161ffe487a0&language=en-US%27")
+    data = response.json()
+    if 'poster_path' in data:
+        return "https://image.tmdb.org/t/p/w500/" + data['poster_path']
+    else:
+        return None
+
+
+
+movielist_of_5000_movies = pickle.load(open('movies.pkl', 'rb'))
+similarityArray = pickle.load(open('similarityArray.pkl', 'rb'))
+
+
+def recommended(movie):
+    movie_index = movielist_of_5000_movies[movielist_of_5000_movies['title'] == movie].index[0]
+    distances = similarityArray[movie_index]
+    movie_list = sorted(enumerate(distances), reverse=True, key=lambda x: x[1])[1:11]
+
+    recommended_movies = []
+    recommended_movies_posters = []
+
+    for i in movie_list:
+        recommended_movies.append(movielist_of_5000_movies.iloc[i[0]].title)
+        recommended_movies_posters.append(fetch_poster(movielist_of_5000_movies.iloc[i[0]].movie_id))
+
+    return recommended_movies, recommended_movies_posters
+
+
+st.title("Movie Recommendation System")
+st.subheader("The is a Movie Recommendation System. I have created this for fun")
+st.caption("I hope you all will like it!!!")
+
+selected_movie = st.selectbox(
+    'Please Select the Movie you like to get Recommendation ',
+    movielist_of_5000_movies['title'].values)
+
+if st.button('Recommend'):
+    st.write('The Recommended Movies for ', selected_movie, " are: ")
+    recommendations, posters = recommended(selected_movie)
+
+
+
+    col1, col2 = st.columns(2)
+    for i in range(5):
+        with col1:
+            st.text(recommendations[i])
+            st.image(posters[i])
+
+    for i in range(5, 10):
+        with col2:
+            st.text(recommendations[i])
+            st.image(posters[i])