Update app.py

app.py

@@ -2,12 +2,6 @@ import gradio as gr
 import pickle
 import json
 import numpy as np
-import pandas as pd
-
-def clear_default_value(val):
-    if val == "0":
-        return ""
-    return val
 
 # Load model and columns
 with open("kigali_model.pickle", "rb") as f:
@@ -64,11 +58,11 @@ def predict(size_sqm, number_of_bedrooms, number_of_bathrooms, number_of_floors,
 
 # Define Gradio interface components
 inputs = [
-    gr.Textbox(label="Size (sqm)", value="0", interactive=True).change(fn=lambda x: clear_default_value(x)),
-    gr.Textbox(label="Number of Bedrooms", value="0", interactive=True).change(fn=lambda x: clear_default_value(x)),
-    gr.Textbox(label="Number of Bathrooms", value="0", interactive=True).change(fn=lambda x: clear_default_value(x)),
-    gr.Textbox(label="Number of Floors", value="0", interactive=True).change(fn=lambda x: clear_default_value(x)),
-    gr.Textbox(label="Parking Space", value="0", interactive=True).change(fn=lambda x: clear_default_value(x)),
+    gr.Textbox(label="Size (sqm)", placeholder="Enter size in sqm"),
+    gr.Textbox(label="Number of Bedrooms", placeholder="Enter number of bedrooms"),
+    gr.Textbox(label="Number of Bathrooms", placeholder="Enter number of bathrooms"),
+    gr.Textbox(label="Number of Floors", placeholder="Enter number of floors"),
+    gr.Textbox(label="Parking Space", placeholder="Enter parking space availability"),
     gr.Dropdown(choices=list(location_mapping.keys()), label="Location"),
     gr.Dropdown(choices=list(property_type_mapping.keys()), label="Property Type")
 ]
@@ -86,4 +80,4 @@ gr.Interface(
     title="Property Price Prediction in Kigali City @2024",
     description="Enter property details to get the price prediction.",
     article=footer
-).launch()
+).launch(share=True)