Update main.py

main.py

@@ -12,6 +12,7 @@ from sklearn.preprocessing import StandardScaler
 from sklearn.compose import ColumnTransformer
 from sklearn.feature_selection import f_classif
 
+
 app = FastAPI()
 templates = Jinja2Templates(directory="templates")
 
@@ -31,11 +32,16 @@ model_input = joblib.load("model_1.joblib")
 @app.post("/sepsis_prediction")
 async def predict(input: InputFeatures):  
     # Numeric Features 
-    num_features = [
+    num_attr = [
         ['Plasma_glucose', 'Blood_Work_Result_1', 'Blood_Pressure',
          'Blood_Work_Result_2', 'Blood_Work_Result_3', 'Body_mass_index',
-         'Blood_Work_Result_4', 'patients_age']
-    ]
+         'Blood_Work_Result_4', 'patients_age']]
+
+    #creating pipelines
+num_pipeline= Pipeline([('imputer', SimpleImputer()),('scaler', StandardScaler())])
+
+
+full_pipeline=ColumnTransformer([('num_pipe',num_pipeline,num_attr)])
 
     XGB = Pipeline([
         ("col_trans", full_pipeline),  # You need to define full_pipeline