Update app.py

app.py

@@ -1,23 +1,25 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the model outside the function
 clf = pipeline("text-classification", model="MayZhou/e5-small-lora-ai-generated-detector")
 
-# Define a Gradio Blocks app
-with gr.Blocks() as demo:
+def detect_ai(text):
+    if not text.strip():
+        return "No text provided."
+    try:
+        result = clf(text)[0]
+        label = result['label']
+        score = round(result['score'] * 100, 2)
+        return f"{label} ({score}%)"
+    except Exception as e:
+        return f"Error: {str(e)}"
 
-    @gr.api()
-    def detect_ai(text: str):
-        try:
-            if not text.strip():
-                return "Error: No text provided"
-            result = clf(text)[0]
-            label = result['label']
-            score = round(result['score'] * 100, 2)
-            return f"{label} ({score}%)"
-        except Exception as e:
-            return f"Error: {str(e)}"
+# Launch the app with a basic Gradio Interface (exposes /predict endpoint)
+demo = gr.Interface(
+    fn=detect_ai,
+    inputs=gr.Textbox(lines=4, label="Enter text"),
+    outputs="text",
+    title="AI Text Detector",
+)
 
-# Important: show_api=True must be passed here
-demo.launch(show_api=True)
+demo.launch()