Update ✨Entity Linking Application✨.py

✨Entity Linking Application✨.py

@@ -288,9 +288,6 @@ def main_cli():
 
     if "disabled" not in st.session_state:
         st.session_state.disabled = False
-
-    def disable_inputs():
-        st.session_state.disabled = True
         
     input_sentence_user = st.text_input("Enter a sentence:", "", disabled=st.session_state.disabled)
     input_mention_user = st.text_input("Enter a textural reference (mention) that is inside the sentence:", "", disabled=st.session_state.disabled)
@@ -298,11 +295,10 @@ def main_cli():
     combi = st.selectbox("Make combinations of each word? (Useful for difficult mentions)", ['Yes', 'No'], index=1, disabled=st.session_state.disabled)
     disambi = st.selectbox("Run acronym disambiguation? (Enable it if the mention include an acronym or if it is nested)", ['Yes', 'No'], index=0, disabled=st.session_state.disabled)
     
-    if st.button("Run Entity Linking"):
+    if st.button("Run Entity Linking", key="disabled"):
         if input_sentence_user and input_mention_user:
             # check if the mention is in the sentence
             if input_mention_user in input_sentence_user:
-                disable_inputs()
                 with st.spinner("Applying Data Normalization module... (1/5)"):
                 # Data Normalization               
                     start_time = time.time()
@@ -437,7 +433,7 @@ def main_cli():
                             lista = []
                             lista_1 = []
                             my_bar = st.progress(0)
-                            for i, element in enumerate(json_file):
+                            for index, element in enumerate(json_file):
                                 qid = element.get("qid")
                                 link = f"https://www.wikidata.org/wiki/{qid}"
                                 label = element.get("label")
@@ -447,7 +443,7 @@ def main_cli():
                                 desc_emb = model.encode([description])
                                 
                                 lista.append({link: [label_emb, desc_emb]})
-                                my_bar.progress((i + 1) / len(json_file))
+                                my_bar.progress((index + 1) / len(json_file))
                                 print(qid)
     
                             label_dataset_emb = model.encode([i])