upadted

app.py

@@ -420,7 +420,8 @@ def humanize_text(
         
         # Calculate similarity
         similarity = calculate_similarity(input_text, result)
-        ai_content_label, ai_content_score = predict_ai_content(result)
+        ai_content_label_generated, ai_content_score_generated = predict_ai_content(result)
+        ai_content_label_input, ai_content_score_input = predict_ai_content(input_text)
         
         # Generate status message
         if not stages_applied:
@@ -428,7 +429,7 @@ def humanize_text(
         else:
             status = f"✅ Successfully applied: {', '.join(stages_applied)}"
         
-        return result, similarity, status,ai_content_label, ai_content_score
+        return result, similarity, status,ai_content_label_generated, ai_content_score_generated,ai_content_label_input, ai_content_score_input
     
     except Exception as e:
         logger.error(f"Error in humanization: {e}")
@@ -471,8 +472,14 @@ def create_gradio_interface():
                 with gr.Row():
                     similarity_output = gr.Number(label="Similarity Score", precision=4)
                     status_output = gr.Textbox(label="Status",interactive=False,lines=2, max_lines=10)
-                    ai_content_label = gr.Textbox(label="AI Content Detection",interactive=False)
-                    ai_content_score = gr.Number(label="AI Content Score", precision=4,interactive=False)
+                
+                with gr.Row():
+                    ai_content_label_input = gr.Textbox(label="AI Content Detection", interactive=False)
+                    ai_content_score_input = gr.Number(label="AI Content Score", precision=4, interactive=False)
+                
+                with gr.Row():
+                    ai_content_label_generated = gr.Textbox(label="AI Content Detection", interactive=False)
+                    ai_content_score_generated = gr.Number(label="AI Content Score", precision=4, interactive=False)
             
             with gr.Column(scale=1):
                 gr.Markdown("## 🎛️ Pipeline Configuration")
@@ -520,13 +527,13 @@ def create_gradio_interface():
                 hedge_prob, booster_prob, connector_prob, starter_prob,
                 split_prob, merge_prob, min_split_length, max_merge_length
             ],
-            outputs=[output_text, similarity_output, status_output,ai_content_label, ai_content_score]
+            outputs=[output_text, similarity_output, status_output,]
         )
         
         clear_btn.click(
             fn=lambda: ("", "", 0.0, ""),
             inputs=[],
-            outputs=[input_text, output_text, similarity_output, status_output]
+            outputs=[input_text, output_text, similarity_output, status_output,ai_content_label_generated, ai_content_score_generated,ai_content_label_input, ai_content_score_input]
         )
         
     return demo