Update main.py

main.py

@@ -44,7 +44,7 @@ def read_root():
 
  
 def data_download(ticker: str):
-    ticker = ticker
+    ticker = ticker.upper()
     # Define the list of tickers
     index_list = [
         ticker, '^VIX', '^VVIX', '^VIX9D', '^VIX3M', '^VIX6M', '^FVX', '^TNX', '^TYX'
@@ -68,7 +68,7 @@ def data_download(ticker: str):
 
     
 def data_manipolation(df,ticker: str):
-    ticker = ticker
+    ticker = ticker.upper()
     # MA calculation for all columns 
     New_Names=[ticker,'VIX','VIX_Index','VIX9D','VIX3M','VIX6M','T5Y','T10Y','T30Y']
     for col in New_Names:
@@ -101,7 +101,7 @@ def data_manipolation(df,ticker: str):
     return df
        
 def data_split_train_test(df,ticker: str):
-    ticker = ticker
+    ticker = ticker.upper()
     X = df.loc[:,df.columns !=  ticker + '_c1']
     y = df[ ticker + '_c1']
     recent_data_size = int(0.3 * len(X))  # Adjust the percentage as needed
@@ -144,6 +144,7 @@ def read_item(ticker: str):
     df=df.round(2)
     Xtrain, ytrain, Xtest, ytest = data_split_train_test(df,ticker)
     forecast_value = xgb_training_forecast(Xtrain, ytrain, Xtest, ytest).round(2)
+    forecast_value = str(forecast_value)
     result = forecast_value.to_json(orient="records")
     return result