Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import joblib
 import numpy as np
+import pandas as pd
 
 # Load the model and unique brand values
 model = joblib.load('model.joblib')
@@ -15,7 +16,12 @@ def predict(brand, screen_size, resolution_width, resolution_height):
     resolution_height = int(resolution_height)
     
     # Prepare the input array for prediction
-    input_data = np.array([[brand, screen_size, resolution_width, resolution_height]])
+    input_data = pd.DataFrame({
+        'Brand': [brand],
+        'Screen Size': [screen_size],
+        'Resolution (Width)': [resolution_width],
+        'Resolution (Height)': [resolution_height]
+    })
     
     # Perform the prediction
     prediction = model.predict(input_data)
@@ -26,7 +32,7 @@ def predict(brand, screen_size, resolution_width, resolution_height):
 interface = gr.Interface(
     fn=predict,
     inputs=[
-        gr.Dropdown(choices=brand_values, label="Brand"),
+        gr.Dropdown(choices=list(brand_values), label="Brand"),
         gr.Textbox(label="Screen Size"),
         gr.Textbox(label="Resolution (Width)"),
         gr.Textbox(label="Resolution (Height)")