Update app.py

app.py

@@ -86,27 +86,29 @@ with gr.Blocks(css=".gradio-container { max-width: 900px; margin: auto; padding:
         "Predict the sentiment of your text review using RNN-based models."
     )
     
+    # Text input box
     with gr.Row():
-        with gr.Column():
-            text_input = gr.Textbox(
-                label="Enter your text here:", 
-                lines=3, 
-                placeholder="Type your review here..."
-            )
-        
-    with gr.Row():
-        gru_output = gr.Textbox(label="Predicted Sentiment (GRU Model)", interactive=False)
-        lstm_output = gr.Textbox(label="Predicted Sentiment (LSTM Model)", interactive=False)
-        bilstm_output = gr.Textbox(label="Predicted Sentiment (BiLSTM Model)", interactive=False)
+        text_input = gr.Textbox(
+            label="Enter your text here:", 
+            lines=3, 
+            placeholder="Type your review here..."
+        )
     
-    with gr.Row():
-        statistics_output = gr.Textbox(label="Statistics (Lowest, Highest, Average)", interactive=False)
-
-    # Buttons placed together in a row
+    # Buttons placed together in a row (second line)
     with gr.Row():
         analyze_button = gr.Button("Analyze Sentiment", variant="primary")  # Blue button
         clear_button = gr.ClearButton([text_input, gru_output, lstm_output, bilstm_output, statistics_output])  # Clear button
 
+    # Prediction and statistics boxes
+    with gr.Row():
+        with gr.Column():
+            gru_output = gr.Textbox(label="Predicted Sentiment (GRU Model)", interactive=False)
+            lstm_output = gr.Textbox(label="Predicted Sentiment (LSTM Model)", interactive=False)
+            bilstm_output = gr.Textbox(label="Predicted Sentiment (BiLSTM Model)", interactive=False)
+        
+        with gr.Column():
+            statistics_output = gr.Textbox(label="Statistics (Lowest, Highest, Average)", interactive=False)
+
     # Button to analyze sentiment and show statistics
     def process_input_and_analyze(text_input):
         results, statistics = analyze_sentiment_and_statistics(text_input)