Update app.py

app.py

@@ -1,41 +1,14 @@
-# import streamlit as st
-# import torch
-# from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
-
-# language_list = ['eng_Latn', 'zho_Hant']
-
-# st.title("Medical Translation English2Traditional Chinese")
-
-
-# trans_text = st.text_area(label = "Enter your text:", value="")
-# trans_col1, trans_col2 = st.columns(2)
-
-# with trans_col1:
-#     src_lang = st.selectbox('Translate from:', (language_list), format_func = decode_iso)
-# with trans_col2:
-#     target_lang = st.selectbox('Translate to:', (language_list), format_func = decode_iso, index=1)
-
-
-# if st.button("Translate"):
-#     st.divider()
-#     with st.spinner(":rainbow[Translating from " + decode_iso(src_lang) + " into " + decode_iso(target_lang) + ", please wait...]"):
-#         translation = translator(trans_text, src_lang, target_lang)
-#         translation
-            
-
-# app.py
-
-import streamlit as st
-from translation_model import translator
-
-st.title("Medical Translation (en/zh)")
-
-text_input = st.text_area("Enter your text:")
-
-translation_direction = st.selectbox("Translate to", ["English -> Chinese", "Chinese -> English"])
-
-if st.button("Translate"):
-    translated_text = translator.translate(text_input, translation_direction)
-    
-    st.subheader("Output:")
+import streamlit as st
+from translation_model import translator
+
+st.title("Medical Translation (en/zh)")
+
+text_input = st.text_area("Enter your text:")
+
+translation_direction = st.selectbox("Translate to", ["English -> Chinese", "Chinese -> English"])
+
+if st.button("Translate"):
+    translated_text = translator.translate(text_input, translation_direction)
+    
+    st.subheader("Output:")
     st.write(translated_text)