Update app.py

app.py

@@ -15,10 +15,10 @@ from sklearn.metrics.pairwise import cosine_similarity
 from fuzzywuzzy import fuzz
 import gradio as gr
 
-meta_df = pd.read_csv("/content/Metacritic_Scores_File.csv",  error_bad_lines=False, encoding='utf-8') 
+meta_df = pd.read_csv("Metacritic_Scores_File.csv",  error_bad_lines=False, encoding='utf-8') 
 meta_df = meta_df[['game', 'reviewer_ID', 'score']]
 
-df_game_names = pd.read_csv("/content/Game_Titles_IDs.csv",  error_bad_lines=False, encoding='utf-8')
+df_game_names = pd.read_csv("Game_Titles_IDs.csv",  error_bad_lines=False, encoding='utf-8')
 
 #We will create a pivot table of users as rows and games as columns. 
 #The pivot table will help us make the calcuations of similarity between the reviewers.