Update app.py

app.py

@@ -54,19 +54,17 @@ with col1:
             language = st.selectbox(f"Select language for input {i+1}:", language_options, key=f'language_{i}')
             sentence = st.text_input(f"Enter sentence for input {i+1} (with <mask>):", key=f'sentence_{i}')
             
+            # Only process filled language and sentence pairs
             if language != 'Choose language' and sentence:
                 input_sentences[language.lower()] = sentence
-            else:
-                st.session_state['warnings'].append(f"Warning: Please select a language and enter a sentence for input {i+1}")
 
         if st.button("Submit"):
-            if st.session_state['warnings']:
-                for warning in st.session_state['warnings']:
-                    st.warning(warning)
-            else:
+            if input_sentences:
                 results, warnings = fill_mask(input_sentences)
                 st.session_state['results'] = results
                 st.session_state['warnings'] = warnings
+            else:
+                st.warning("Please fill at least one language and sentence.")
 
     elif option_selected == 'Upload a file(csv/txt)':
         uploaded_file = st.file_uploader("Choose a file (one sentence per line)")
@@ -95,13 +93,17 @@ with col2:
     st.markdown("### Output :bar_chart:")
     
     if st.session_state['results']:
-        for language, predictions in st.session_state['results'].items():
-            if predictions:
-                top_prediction = predictions[0]
-                predicted_word = top_prediction['token_str']
-                score = top_prediction['score'] * 100
-
-                st.markdown(f"**{language.capitalize()} Prediction:** {predicted_word} ({score:.2f}%)")
+        # Use st.fragment for dynamic content
+        with st.container():
+            for language, predictions in st.session_state['results'].items():
+                if predictions:
+                    top_prediction = predictions[0]
+                    predicted_word = top_prediction['token_str']
+                    score = top_prediction['score'] * 100
+
+                    # Displaying the prediction with fragment
+                    st.markdown(f"**{language.capitalize()} Prediction:** {predicted_word} ({score:.2f}%)")
+                    st.markdown(f"<div class='bar'><div class='bar-fill' style='width:{score}%;'></div></div>", unsafe_allow_html=True)
 
     if st.session_state['warnings']:
         for warning in st.session_state['warnings']:
@@ -116,4 +118,4 @@ footer {display:none !important;}
 .container {display: flex; justify-content: space-between; align-items: center; margin-bottom: 5px;}
 </style>
 """
-st.markdown(css, unsafe_allow_html=True)
+st.markdown(css, unsafe_allow_html=True)