Update app.py

app.py

@@ -224,7 +224,7 @@ def dedupe(items):
             yield item
             seen.add(item)
 
-lem_clinical_note= lemmatize(text, nlp0)
+lem_clinical_note= lemmatize(runtext, nlp0)
 #creating a doc object using BC5CDR model
 doc = nlp1(lem_clinical_note)
 options = get_entity_options()
@@ -238,7 +238,7 @@ matcher = match(nlp1, results0,"NEG_ENTITY")
 doc0 = overwrite_ent_lbl(matcher,doc)
 
 #visualizing identified Named Entities in clinical input text 
-displacy.render(doc0, style='ent', options=options)
+ent_html = displacy.render(doc0, style='ent', options=options)
 
 ##======================== End of NER Tagging ========================
 
@@ -278,11 +278,12 @@ def run_model(input_text):
 
     
     st.success(output)
-
-doc = nlp(str(original_text2))
-colors = { "DISEASE": "pink","CHEMICAL": "orange"}
-options = {"ents": [ "DISEASE", "CHEMICAL"],"colors": colors}
-ent_html = displacy.render(doc, style="ent", options=options)
+# ====== Old NER ======
+#doc = nlp(str(original_text2))
+#colors = { "DISEASE": "pink","CHEMICAL": "orange"}
+#options = {"ents": [ "DISEASE", "CHEMICAL"],"colors": colors}
+#ent_html = displacy.render(doc, style="ent", options=options)
+# ====== End of Old NER ======
 
 col1, col2 = st.columns([1,1])