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app.py

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+import streamlit as st
+import pickle
+
+# extract the new_df dataframe from movies.pkl
+movies_list = pickle.load(open("movies.pkl", "rb"))
+# extract the titles of movies
+movies_list_title = movies_list["title"].values
+
+# extract the similarity which contain our cosine similarity values
+similarity = pickle.load(open("similarity.pkl", "rb"))
+
+
+# make a recommend function which will take movie title and return 5 similar movies with their posters
+def recommend(movie):
+    movie_index = movies_list[movies_list["title"] == movie].index[0]
+    distances = similarity[movie_index]
+    sorted_movie_list = sorted(list(enumerate(distances)), reverse=True,
+                               key=lambda x:x[1])[1:6]
+
+    recommended_movies = []
+    recommended_posters = []
+    for i in sorted_movie_list:
+        poster_path = movies_list["poster_path"][i[0]]
+        recommended_movies.append(movies_list.iloc[i[0]].title)
+        recommended_posters.append("https://image.tmdb.org/t/p/original"+poster_path)
+
+    return recommended_movies,  recommended_posters
+
+
+
+# Create title for your stream lit page
+st.title("Movie Recommender System")
+
+# Create a input box for movies name 
+selected_movie_name = st.selectbox(
+    "What is the movie name?",
+    movies_list_title
+)
+
+# create a recommend button with function of displaying recommended movies and movie posters
+if st.button("Recommend"):
+    recommendation, movie_posters = recommend(selected_movie_name)
+
+    col1, col2, col3, col4, col5 = st.columns(5)
+
+    with col1:
+        st.write(recommendation[0])
+        st.image(movie_posters[0])
+    with col2:
+        st.write(recommendation[1])
+        st.image(movie_posters[1])
+    with col3:
+        st.write(recommendation[2])
+        st.image(movie_posters[2])
+    with col4:
+        st.write(recommendation[3])
+        st.image(movie_posters[3])
+    with col5:
+        st.write(recommendation[4])
+        st.image(movie_posters[4])
+

movies.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:59bfacbec6572a27ccdddd3d636b325e4c2288b563e365c356dbbecb253055ef
+size 3834246

similarity.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:92eb0c1f80c11321b9701b61815de547ab3f5cdee87b797451c96a3ea40ac1aa
+size 465979555