upadted

app.py

@@ -49,8 +49,22 @@ print("Models loaded successfully!")
 # AI Detection
 # ============================================================================
 def predict_ai_content(text):
-    res = ai_detector_pipe(text)[0]
-    return res['label'], res['score']
+    if not text or not text.strip():
+        return "No input provided", 0.0
+
+    try:
+        result = ai_detector_pipe(text)
+        if isinstance(result, list) and len(result) > 0:
+            res = result[0]
+            ai_content_label = res.get('label', 'Unknown')
+            ai_content_score = round(float(res.get('score', 0)) * 100, 2)
+            return ai_content_label, ai_content_score
+        else:
+            return "Invalid response", 0.0
+    except Exception as e:
+        print(f"Error in prediction: {e}")
+        return "Error", 0.0
+
 
 # ============================================================================
 # STAGE 1: PARAPHRASING WITH T5 MODEL
@@ -478,13 +492,13 @@ def create_gradio_interface():
 
                 with gr.Row():
                         ai_content_label_input = gr.Textbox(
-                            label="AI Content Detection",
+                            label="Detected Content Type",
                             interactive=False,
                             lines=1,
                             max_lines=10
                         )
                         ai_content_score_input = gr.Number(
-                            label="Confidence Score",
+                            label="Model Confidence (%)",
                             precision=2,
                             interactive=False
                         )
@@ -494,14 +508,14 @@ def create_gradio_interface():
 
                 with gr.Row():
                     ai_content_label_generated = gr.Textbox(
-                        label="AI Content Detection",
+                        label="Detected Content Type",
                         interactive=False,
                         lines=1,
                         max_lines=10
                     )
                 
                     ai_content_score_generated = gr.Number(
-                        label="Confidence Score",
+                        label="Model Confidence (%)",
                         precision=2,
                         interactive=False
                     )