Update app.py

app.py

@@ -15,13 +15,13 @@ patseer_stopwords=['a' , 'abaft' , 'abafter' , 'abaftest' , 'ability' , 'able' ,
 from keybert import KeyBERT
 kw_model=KeyBERT(model='AI-Growth-Lab/PatentSBERTa')
 import yake
-vectorizer = CountVectorizer(ngram_range=(1, 3), stop_words=patseer_stopwords)
+#vectorizer = CountVectorizer(ngram_range=(1, 3), stop_words=patseer_stopwords)
 kw_extractor=yake.KeywordExtractor(top=50, stopwords=patseer_stopwords)
 candidates=kw_extractor.extract_keywords(text)
 candidates=[candidate[0] for candidate in candidates]
 from keyphrase_vectorizers import KeyphraseCountVectorizer
 #vectorizer=KeyphraseCountVectorizer(stop_words=patseer_stopwords)
-keywords=kw_model.extract_keywords(text,candidates, keyphrase_ngram_range=(1, 3),stop_words=patseer_stopwords, top_n=50,vectorizer=vectorizer)
+keywords=kw_model.extract_keywords(text,candidates, keyphrase_ngram_range=(1, 3),stop_words=patseer_stopwords, top_n=50,KeyphraseCountVectorizer(stop_words=patseer_stopwords))
 
 if keywords != []:
       st.info("Extracted keywords")