Update app.py

app.py

@@ -1,21 +1,7 @@
 import gradio as gr
 
-def classify_image(image):
-    # Preprocess the image
-    inputs = processor(images=image, return_tensors="pt")
-
-    # Predict
-    outputs = model(**inputs)
-    predictions = outputs.logits.softmax(dim=-1)
-
-    # Assuming your model returns two probabilities: [real, AI-generated]
-    probs = predictions.detach().numpy()[0]
-    labels = ['Real', 'AI-generated']
-    result = {labels[i]: probs[i] for i in range(len(labels))}
-
-    return result
-
-# Create the Gradio interface
-iface = gr.Interface(fn=classify_image, inputs=gr.inputs.Image(shape=(224, 224)), outputs=gr.outputs.Label(num_top_classes=2))
+def greet(name):
+    return "Hello, " + name + ". Thank you for yout visit! \n This Project will be available after the Gulf Coast Conference & Expo on AI. \n You are welcome to join us at this event. \n Find out more at https://hcc.idloom.events/artificial-intelligence-conference-dit"
 
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()