Update app.py

app.py

@@ -23,13 +23,9 @@ kw_model = {
 
 ## KeyphraseVectorizers
 # source: https://github.com/TimSchopf/KeyphraseVectorizers#keyphrasevectorizers
-
-download spacy pipeline (https://spacy.io/models/pt)
-source: https://melaniewalsh.github.io/Intro-Cultural-Analytics/05-Text-Analysis/Multilingual/Portuguese/03-POS-Keywords-Portuguese.html
-os.system("python -m spacy download pt_core_news_lg")
-
-# Part-of-Speech Tagging for Portuguese (https://melaniewalsh.github.io/Intro-Cultural-Analytics/05-Text-Analysis/Multilingual/Portuguese/03-POS-Keywords-Portuguese.html)
-pos_pattern='<CONJ.*>*<ADP.*>*<ADV.*>*<NUM.*>*<ADJ.*>*<N.*>+'
+# download spacy pipeline (https://spacy.io/models/pt)
+# source: https://melaniewalsh.github.io/Intro-Cultural-Analytics/05-Text-Analysis/Multilingual/Portuguese/03-POS-Keywords-Portuguese.html
+# os.system("python -m spacy download pt_core_news_lg")
 
 # download stop words in Portuguese
 #import nltk
@@ -37,8 +33,11 @@ pos_pattern='<CONJ.*>*<ADP.*>*<ADV.*>*<NUM.*>*<ADJ.*>*<N.*>+'
 #from nltk.corpus import stopwords
 #stop_words = set(stopwords.words('portuguese'))
 
+# Part-of-Speech Tagging for Portuguese (https://melaniewalsh.github.io/Intro-Cultural-Analytics/05-Text-Analysis/Multilingual/Portuguese/03-POS-Keywords-Portuguese.html)
+pos_pattern='<CONJ.*>*<ADP.*>*<ADV.*>*<NUM.*>*<ADJ.*>*<N.*>+'
+
 # define o vectorizer
-vectorizer = KeyphraseCountVectorizer(spacy_pipeline='pt_core_news_lg', pos_pattern=pos_pattern, stop_words=None, lowercase=False)
+vectorizer = KeyphraseCountVectorizer(spacy_pipeline='pt_core_news_lg', stop_words=None, pos_pattern=pos_pattern, lowercase=False)
 
 # function principal (keywords)
 def get_kw_html(model_id, doc, top_n, diversity):