Update app.py

app.py

@@ -2,6 +2,12 @@ import streamlit as st
 from PIL import Image
 from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
 
+
+def clear_text():
+    st.session_state.my_text = st.session_state.widget
+    st.session_state.widget = ""
+
+    
 def get_result_text_es_pt (list_entity, text, lang):
     result_words = []
     tmp_word = ""
@@ -109,6 +115,9 @@ def get_result_text_ca (list_entity, text):
 
 if __name__ == "__main__":
 
+    if "text" not in st.session_state:
+        st.session_state.text = ""
+    
     st.title('Sanivert Punctuation And Capitalization Restoration')
     model_es = AutoModelForTokenClassification.from_pretrained("VOCALINLP/spanish_capitalization_punctuation_restoration_sanivert")
     tokenizer_es = AutoTokenizer.from_pretrained("VOCALINLP/spanish_capitalization_punctuation_restoration_sanivert")
@@ -131,7 +140,9 @@ if __name__ == "__main__":
 	)
 
     st.subheader("Enter the text to be analyzed.")
-    text = st.text_input('Enter text') #text is stored in this variable    
+    st.text_input('Enter text', key='widget', on_change=clear_text) #text is stored in this variable 
+    text = st.session_state.text
+    
     if input_text == "Spanish": 
         result_pipe = pipe_es(text)
         out = get_result_text_es_pt(result_pipe, text, "es")