Update app.py

app.py

@@ -246,6 +246,10 @@ def getSentence(listOfSentences,value):
             return sent
     return value
 def get_annotated_text(text,value,entity):
+    doc = nlp(text)
+    doc.ents = [doc.char_span(txt.index(value), txt.index(value)+len(value), label=entity)]
+    ent_html = displacy.render(doc, style='ent', jupyter=False)# Display the entity visualization in the browser:
+    st.markdown(ent_html, unsafe_allow_html=True)
     return [text.split(value)[0],(value,entity),text.split(value)[1]]
     
 st.header("Transcript Analysis", divider='rainbow')
@@ -299,18 +303,18 @@ if st.button("Analyze"):
     expences=[x["expense"] for x in ner_result if "expense" in x]
     for idx in range(len(revenues)): 
          st.text_input(f'Revenue:{idx+1}', revenues[idx])
-         st.text_input(f'Revenue-Sentence:{idx+1}', getSentence(sentences,revenues[idx]))
-         annotated_text(get_annotated_text(getSentence(sentences,revenues[idx]),str(revenues[idx]),"Revenue"))
+         # st.text_input(f'Revenue-Sentence:{idx+1}', getSentence(sentences,revenues[idx]))
+         get_annotated_text(getSentence(sentences,revenues[idx]),str(revenues[idx]),"Revenue")
         
     for idx in range(len(profits)):
          st.text_input(f'Profit:{idx+1}', profits[idx])
-         st.text_input(f'Profit-Sentence:{idx+1}', getSentence(sentences,profits[idx]))
-         annotated_text(get_annotated_text(getSentence(sentences,profits[idx]),str(profits[idx]),"Profit"))
+         # st.text_input(f'Profit-Sentence:{idx+1}', getSentence(sentences,profits[idx]))
+         get_annotated_text(getSentence(sentences,profits[idx]),str(profits[idx]),"Profit")
          
     for idx in range(len(expences)):
          st.text_input(f'Expences:{idx+1}', expences[idx])
-         st.text_input(f'Expences-Sentences:{idx+1}', getSentence(sentences,expences[idx]))
-         annotated_text(get_annotated_text(getSentence(sentences,expences[idx]),str(expences[idx]),"Expences"))
+         # st.text_input(f'Expences-Sentences:{idx+1}', getSentence(sentences,expences[idx]))
+         get_annotated_text(getSentence(sentences,expences[idx]),str(expences[idx]),"Expences")
          
 
     st.subheader("Investment Recommendation", divider='rainbow')