Update app.py

app.py

@@ -1,18 +1,41 @@
 import gradio as gr
-import ai_text_detector_valid_final as detector
-
-def run_detector(text):
-    try:
-        return detector.detect_text(text)  # change if your function is named differently
-    except Exception as e:
-        return f"Error: {e}"
-
-demo = gr.Interface(
-    fn=run_detector,
-    inputs=gr.Textbox(lines=10, placeholder="Paste your text here..."),
-    outputs="text",
-    title="AI Text Detector",
-    description="Check if text is AI-generated or human."
-)
+from ai_text_detector_valid_final import detect_text
+
+def analyze_text(user_text):
+    return detect_text(user_text)
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 🔍 AI vs Human Text Detector  
+        Paste any text below and our system will analyze it using **3 different models**  
+        and generate a final average probability.  
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            user_input = gr.Textbox(
+                label="✍️ Enter Text",
+                placeholder="Paste text here...",
+                lines=10
+            )
+            analyze_btn = gr.Button("🚀 Run Detection", variant="primary")
+
+        with gr.Column(scale=1):
+            final_output = gr.JSON(label="📊 Final Results")
+
+    with gr.Accordion("🔬 Detailed Model Results", open=False):
+        model_output = gr.JSON(label="All Model Scores")
+
+    def run_analysis(user_text):
+        results = analyze_text(user_text)
+        return results, results  # send to both JSON outputs
+
+    analyze_btn.click(
+        fn=run_analysis,
+        inputs=user_input,
+        outputs=[final_output, model_output]
+    )
 
 demo.launch()