config file for theme

.streamlit/config.toml

@@ -0,0 +1,6 @@
+[theme]
+primaryColor="#FF4B4B"
+backgroundColor="#0E1117"
+secondaryBackgroundColor="#E50914"
+textColor="#FAFAFA"
+font="sans serif"

.streamlit/credentials.toml

@@ -0,0 +1,2 @@
+[general]
+email = ""

app.py

@@ -13,7 +13,6 @@ from sklearn.metrics.pairwise import cosine_similarity
 import numpy as np
 import pandas as pd
 import streamlit as st
-from random import choice
 import subprocess
 import sys
 
@@ -31,7 +30,6 @@ links_df = pd.read_csv(
     'https://raw.githubusercontent.com/sherwan-m/WBSFLIX_Recommender_System/main/ml-latest-small/links.csv')
 tags_df = pd.read_csv(
     'https://raw.githubusercontent.com/sherwan-m/WBSFLIX_Recommender_System/main/ml-latest-small/tags.csv')
-
 # %% format dataframes
 # MOVIE DF:
 movie_df = (
@@ -170,39 +168,39 @@ x = popular_n_movies(5, 'Any')
 st.set_page_config(page_title="WBSFLIX",
                    page_icon="🎬",
                    initial_sidebar_state="expanded",
-                   # layout="wide"
+                   layout="wide"
                    )
 
 # set colors: These has to be set on the setting menu online
 # primary color: #FF4B4B, background color:#0E1117
-# text color: #FAFAFA, secindary background color: #E50914
+# text color: #FAFAFA, secondary background color: #E50914
 
 # Set the logo of app
 st.sidebar.image("wbs_logo.png",
                  width=300, clamp=True)
-welcome_img = Image.open("welcome_page_img01.png")
+welcome_img = Image.open('welcome_page_img01.png')
 st.image(welcome_img)
-st.markdown("""
+st.sidebar.markdown("""
 # 🎬 Welcome to the next generation movie recommendation app
 """)
 
 # %% APP WORKFLOW
-st.markdown("""
+st.sidebar.markdown("""
 ### How may we help you?
 """
-            )
+                    )
 # Popularity based recommender system
-genre_default, n_default = None, None
-pop_based_rec = st.checkbox("Show me the all time favourites",
-                            False,
-                            help="Movies that are liked by many people")
+genre_default = None
+pop_based_rec = st.sidebar.checkbox("Show me the all time favourites",
+                                    False,
+                                    help="Movies that are liked by many people")
 
 
 if pop_based_rec:
-    st.markdown("### Select Genre and Nr of movie recommendations")
+    st.markdown("### Select the Genre and the Number of recommendations")
     genre_default, n_default = None, 5
     with st.form(key="pop_form"):
-        # genre_default, year_default = ['Any'], ['Any']
+        genre_default = ['Any']
         genre = st.multiselect(
             "Genre",
             options=genre_list,
@@ -229,11 +227,10 @@ st.write("")
 st.write("")
 st.write("")
 
-item_based_rec = st.checkbox("Show me a movie like this",
-                             False,
-                             help="Input some movies and we will show you similar ones")
-short_movie_list = ['Prestige, The (2006)', 'Toy Story (1995)',
-                    'No Country for Old Men (2007)']
+item_based_rec = st.sidebar.checkbox("Show me a movie like this",
+                                     False,
+                                     help="Input some movies and we will show you similar ones")
+
 if item_based_rec:
     st.markdown("### Tell us a movie you like:")
     with st.form(key="movie_form"):
@@ -242,6 +239,7 @@ if item_based_rec:
                                     options=pd.Series(movie_list),
                                     help="Select a movie you like",
                                     key='item_select',
+                                    # default=choice(short_movie_list)
                                     )
 
         nr_rec = st.slider("Number of recommendations",
@@ -266,9 +264,9 @@ st.write("")
 st.write("")
 st.write("")
 
-user_based_rec = st.checkbox("I want to get personalized recommendations",
-                             False,
-                             help="Login to get personalized recommendations")
+user_based_rec = st.sidebar.checkbox("I want to get personalized recommendations",
+                                     False,
+                                     help="Login to get personalized recommendations")
 
 if user_based_rec:
     st.markdown("### Please login to get customized recommendations just for you")