Update functions.py

functions.py

@@ -138,7 +138,8 @@ def summary_downloader(raw_text):
 	st.markdown("#### Download Summary as a File ###")
 	href = f'<a href="data:file/txt;base64,{b64}" download="{new_filename}">Click to Download!!</a>'
 	st.markdown(href,unsafe_allow_html=True)
-	
+
+@st.experimental_memo(suppress_st_warning=True) 	
 def get_all_entities_per_sentence(text):
     doc = nlp(''.join(text))
 
@@ -166,11 +167,13 @@ def get_all_entities_per_sentence(text):
         entities_all_sentences.append(entities_this_sentence)
 
     return entities_all_sentences
-    
+ 
+@st.experimental_memo(suppress_st_warning=True)    
 def get_all_entities(text):
     all_entities_per_sentence = get_all_entities_per_sentence(text)
     return list(itertools.chain.from_iterable(all_entities_per_sentence))
-    
+
+@st.experimental_memo(suppress_st_warning=True)    
 def get_and_compare_entities(article_content,summary_output):
     
     all_entities_per_sentence = get_all_entities_per_sentence(article_content)
@@ -218,6 +221,7 @@ def get_and_compare_entities(article_content,summary_output):
 
     return matched_entities, unmatched_entities
 
+@st.experimental_memo(suppress_st_warning=True) 
 def highlight_entities(article_content,summary_output):
    
     markdown_start_red = "<mark class=\"entity\" style=\"background: rgb(238, 135, 135);\">"
@@ -252,7 +256,8 @@ def display_df_as_table(model,top_k,score='score'):
     df['Score'] = round(df['Score'],2)
     
     return df   
-    
+
+      
 def make_spans(text,results):
     results_list = []
     for i in range(len(results)):
@@ -264,4 +269,7 @@ def make_spans(text,results):
 ##Fiscal Sentiment by Sentence
 def fin_ext(text):
     results = remote_clx(sent_tokenizer(text))
-    return make_spans(text,results)
+    return make_spans(text,results)
+    
+nlp = get_spacy()    
+asr_model, sent_pipe, sum_pipe, ner_pipe, sbert, cross_encoder  = load_models()