Update app.py

app.py

@@ -1,12 +1,17 @@
 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:
+
     @gr.api()
-    def detect_ai(text: str) -> str:
+    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)
@@ -14,4 +19,5 @@ with gr.Blocks() as demo:
         except Exception as e:
             return f"Error: {str(e)}"
 
+# Important: show_api=True must be passed here
 demo.launch(show_api=True)