first commit for deploying

Procfile

@@ -0,0 +1 @@
+web : sh setup.sh && streamlit run main.py

README.md

@@ -1,13 +1 @@
----
-title: Movies Recommendation
-emoji: 🏃
-colorFrom: blue
-colorTo: gray
-sdk: streamlit
-sdk_version: 1.25.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Movie_Recommendations

app.py

@@ -0,0 +1,60 @@
+import streamlit as st
+import pickle
+import requests
+# from sklearn.feature_extraction.text import CountVectorizer
+
+
+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])
+    recommend_Movies=[]
+    recommended_movie_posters = []
+    for i in distances[1:6]:
+        movie_id = movies.iloc[i[0]].movie_id
+        recommended_movie_posters.append(fetch_poster(movie_id))
+        recommend_Movies.append(movies.iloc[i[0]].title)
+    return recommended_movie_posters,recommend_Movies
+
+
+
+
+movies=pickle.load(open('movie_list.pkl','rb'))
+similarity=pickle.load(open("similarity.pkl",'rb'))
+# cv = CountVectorizer(max_features=10000,stop_words='english')
+# from sklearn.metrics.pairwise import cosine_similarity
+# vector = cv.fit_transform(movies['tags']).toarray()
+# similarity = cosine_similarity(vector)
+
+
+st.title("Movie Recommandor System")
+Movies_Name = st.selectbox('How would you like to recomend movies?',movies['title'].values)
+
+if st.button('recommend'):
+    recommended_movie_posters,recommend_Movies=recommend(Movies_Name)
+    col1, col2, col3, col4, col5 = st.columns(5)
+    with col1:
+        st.text(recommend_Movies[0])
+        st.image(recommended_movie_posters[0])
+    with col2:
+        st.text(recommend_Movies[1])
+        st.image(recommended_movie_posters[1])
+
+    with col3:
+        st.text(recommend_Movies[2])
+        st.image(recommended_movie_posters[2])
+    with col4:
+        st.text(recommend_Movies[3])
+        st.image(recommended_movie_posters[3])
+    with col5:
+        st.text(recommend_Movies[4])
+        st.image(recommended_movie_posters[4])
+
+

gitignore

@@ -0,0 +1 @@
+venv

movie_list.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:89155305bb8377fa5b61f3d83cd728f46e6c6982971b0ee4fdca365a2b43792e
+size 2514290

requirements.txt

@@ -0,0 +1,7 @@
+streamlit_lottie==0.0.2
+pandas==1.3.5
+xlrd<2.0
+streamlit==1.3.0
+requests==2.24.0
+Pillow==8.4.0
+click<8.0

setup.sh

@@ -0,0 +1,9 @@
+mkdir -p ~/.streamlit/
+
+echo "\
+[Server]\n\
+port =$port\n\
+enableCORS = false\n\
+headless =true \n\
+\n\
+" > ~/.streamlit/credentials.toml