Update app.py

app.py

@@ -5,13 +5,11 @@ import yake
 from keyphrase_vectorizers import KeyphraseCountVectorizer
 
 @st.cache(allow_output_mutation=True, suppress_st_warning=True, show_spinner=True)
-def load_model():
-  model = KeyBERT("google/bigbird-pegasus-large-bigpatent")
-  return model
+#def load_model():
+  #model = KeyBERT("google/bigbird-pegasus-large-bigpatent")
+  #return model
   
-model = load_model()
-
-
+#model = load_model()
 st.title("Patent Text Extractor")
 placeholder = st.empty()
 text_input = placeholder.text_area("Paste or write text", height=300)
@@ -39,11 +37,11 @@ button = st.button("Extract Keywords")
 kw_extractor = yake.KeywordExtractor(top=50)
 candidates = kw_extractor.extract_keywords(text_input)
 keyphrases = [candidate[0] for candidate in candidates]
-#kw_model = KeyBERT(model=model)
+kw_model = KeyBERT(model="google/bigbird-pegasus-large-bigpatent")
 
 #if keywords != []:
-keywords = model.extract_keywords(text_input,keyphrases, keyphrase_ngram_range=(1, 3), 
-                       top_n=50,stop_words='english')
+keywords = kw_model.extract_keywords(text_input,keyphrases, keyphrase_ngram_range=(1, 3), 
+                       top_n=50,stop_words='english',vectorizer=KeyphraseCountVectorizer())
 if keywords != []:
     st.info("Extracted keywords")
     keywords = pd.DataFrame(keywords, columns=["Keyword", "Score"])