Update app.py

app.py

@@ -4,8 +4,9 @@ import plotly.graph_objects as go
 from sklearn.linear_model import LinearRegression
 import numpy as np
 from pandas.tseries.offsets import MonthEnd
+import datetime
 
-def plot_and_predict(zip, start_date, prediction_months):
+def plot_and_predict(zip, start_year, start_month, prediction_months):
     # Read and process the real estate data from Zillow
     df = pd.read_csv('https://files.zillowstatic.com/research/public_csvs/zhvi/Zip_zhvi_uc_sfrcondo_tier_0.33_0.67_sm_sa_month.csv')
     df = df[df['RegionName'] == int(zip)]
@@ -14,7 +15,8 @@ def plot_and_predict(zip, start_date, prediction_months):
     df.columns = ['Date', 'Price']
     df['Date'] = pd.to_datetime(df['Date'])
 
-    # Filter data based on start date
+    # Combine year and month into a start date and filter data based on it
+    start_date = f"{start_year}-{start_month:02d}-01"
     start_date = pd.to_datetime(start_date)
     df = df[df['Date'] >= start_date]
 
@@ -58,16 +60,30 @@ def plot_and_predict(zip, start_date, prediction_months):
 
     return fig
 
-# Gradio interface
+# Custom validation functions
+def validate_zip(zip_code):
+    if not zip_code.isdigit() or len(zip_code) != 5:
+        return "Please enter a valid 5-digit ZIP code."
+
+def validate_year(year):
+    current_year = datetime.datetime.now().year
+    if not year.isdigit() or not (2000 <= int(year) <= current_year):
+        return f"Please enter a valid year between 2000 and {current_year}."
+
+# Gradio interface with updated inputs and validations
 interface = gr.Interface(
     fn=plot_and_predict,
     inputs=[
-        gr.Textbox(label="ZIP Code"),
-        gr.Textbox(label="Start Date (YYYY-MM-DD)", placeholder="YYYY-MM-DD"),
-        gr.Slider(minimum=1, maximum=60, step=1, label="Prediction Months"),
+        gr.Textbox(label="ZIP Code", placeholder="e.g., 90210", validation=validate_zip),
+        gr.Textbox(label="Start Year", placeholder="e.g., 2020", validation=validate_year),
+        gr.Dropdown(label="Start Month", choices=[str(i) for i in range(1, 13)], placeholder="Select Month"),
+        gr.Slider(minimum=1, maximum=60, step=1, label="Prediction Months", default=12),
     ],
-    outputs="plot"
+    outputs="plot",
+    layout="vertical",
+    title="Real Estate Price Predictor",
+    description="Enter a ZIP code, start year, start month, and the number of months for price prediction."
 )
 
 # Launch the app
-interface.launch()
+interface.launch(debug=True)