Update main.py

main.py

@@ -22,14 +22,14 @@ class InputFeatures(BaseModel):
     # bd2: float
     # age: int
 
-    Plasma glucose: float
-    Blood Work Result 1:float
-    Blood Pressure :float
-    Blood Work Result 2:float
-    Blood Work Result 3:float
-    Body mass index :float
-    Blood Work Result 4:float
-    patients age :int
+    Plasma_glucose: float
+    Blood_Work_Result_1:float
+    Blood_Pressure :float
+    Blood_Work_Result_2:float
+    Blood_Work_Result_3:float
+    Body_mass_index :float
+    Blood_Work_Result_4:float
+    patients_age :int
 
 # Load the pickled XGBoost model
 model_input = joblib.load("model_1.joblib")
@@ -39,9 +39,9 @@ model_input = joblib.load("model_1.joblib")
 async def predict(input:model_input):  
      #Numeric Features 
 
-     num_features = [['Plasma glucose','Blood Work Result-1','Blood Pressure',
-       'Blood Work Result-2',' Blood Work Result-3', 'Body mass index',
-       'Blood Work Result-4', 'Age']]
+     num_features = [['Plasma_glucose','Blood_Work_Result_1','Blood_Pressure',
+       'Blood_Work_Result_2',' Blood_Work_Result_3', 'Body_mass_index',
+       'Blood_Work_Result_4', 'Age']]
 
     XGB= Pipeline([
     ("col_trans", full_pipeline),