Update app.py

app.py

@@ -19,12 +19,12 @@ pa_stopwords=['a' , 'abaft' , 'abafter' , 'abaftest' , 'ability' , 'able' , 'abo
 #from sklearn.feature_extraction.text import CountVectorizer
 from keybert import KeyBERT
 kw_model = KeyBERT(model='AI-Growth-Lab/PatentSBERTa')
-kw_extractor = yake.KeywordExtractor(top=50)
+kw_extractor = yake.KeywordExtractor(top=50,stopwords=pa_stopwords)
 candidates = kw_extractor.extract_keywords(text)
 keyphrases = [candidate[0] for candidate in candidates]
 from keyphrase_vectorizers import KeyphraseCountVectorizer
 keywords=kw_model.extract_keywords(text,keyphrases, 
-  top_n=50,stop_words=pa_stopwords,keyphrase_ngram_range=(1, 3),vectorizer=KeyphraseCountVectorizer(),use_mmr=True)
+  top_n=50,keyphrase_ngram_range=(1, 3),vectorizer=KeyphraseCountVectorizer(stop_words=pa_stopwords),use_mmr=True)
 
 
 if keywords != []: