Update app.py

app.py

@@ -1,29 +1,17 @@
 import gradio as gr
+from huggingface_hub import from_pretrained
 
+# Load the model (try with a built-in model first)
+model = from_pretrained("bert-base-uncased")  # Or any other built-in HF model
 
-# Load the model from Hugging Face Hub
-repo_id = "rmaitest/mlmodel2"  # Your model repository ID
-model = repo_id  # Loads the inference function (predict_price)
+def predict_simple(text):
+    return {"result": text.upper()}
 
-
-def predict_with_hf_model(size, bedrooms, age):
-    """Predicts house price using the model from Hugging Face Hub."""
-    # Call the loaded inference function
-    result = model.predict_price(size=size, bedrooms=bedrooms, age=age) 
-    predicted_price = result["predicted_price"]  # Extract the predicted price
-
-    # Format the output
-    return f"Predicted Price: ${predicted_price:,.2f}"
-
-
-# Create the Gradio interface
 iface = gr.Interface(
-    fn=predict_with_hf_model,
-    inputs=["number", "number", "number"],
+    fn=predict_simple,
+    inputs="text",
     outputs="text",
-    title="House Price Prediction",
-    description="Enter house details to predict the price.",
+    title="Simple Text Uppercasing",
 )
 
-# Launch the interface
 iface.launch()