Primeiro teste do recommender

app.py

@@ -1,4 +1,8 @@
 import gradio as gr
+import nltk
+nltk.download('punkt')
+from nltk import sent_tokenize, word_tokenize
+from nltk.stem.snowball import SnowballStemmer
 import imdb_recommender
 
 #def greet(name):

imdb_recommender.py

@@ -1,10 +1,7 @@
 import numpy as np
 import pandas as pd
 import re
-import nltk
-nltk.download('punkt')
-from nltk import sent_tokenize, word_tokenize
-from nltk.stem.snowball import SnowballStemmer
+
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 import requests