Update app.py

app.py

@@ -71,10 +71,10 @@ def get_databricks_file(file_path):
 def get_month_label(i):
     return f'M{i+1}'
 
-data_predictions_ = get_databricks_file("dbfs:/dbfs/FileStore/forecast_alleviatetax_predictions.csv")
-df = pd.read_csv(StringIO(data_predictions_.decode('utf-8')))
-df['revenue'] = (df['vintage_unique_cases'] / df['predicted_monthly_payment_rate']).round(2)
-df['Month'] = [get_month_label(i) for i in range(len(df))]
+#data_predictions_ = get_databricks_file("dbfs:/dbfs/FileStore/forecast_alleviatetax_predictions.csv")
+#df = pd.read_csv(StringIO(data_predictions_.decode('utf-8')))
+#df['revenue'] = (df['vintage_unique_cases'] / df['predicted_monthly_payment_rate']).round(2)
+#df['Month'] = [get_month_label(i) for i in range(len(df))]
     
 def update_table(start_date, end_date, window, user_text):
     #############################################################################################
@@ -169,7 +169,8 @@ with gr.Blocks(fill_height=True) as demo:
             prediction_input = gr.Text(label="Month Prediction:", placeholder="Enter date (e.g., 2024-10-31)", max_lines=1)
             range_input = gr.Slider(1, 10, 6, label="Window / Moving Average Period")
         
-        table_ = gr.DataFrame(value=df, label="Predictions (consult 'revenue' column):")
+        #table_ = gr.DataFrame(value=df, label="Predictions (consult 'revenue' column):")
+        table_ = gr.DataFrame(value='', label="Predictions (consult 'revenue' column):")
         btn_update = gr.Button("Run Forecast")
     
         #with gr.Row():