Update main.py

main.py

@@ -22,18 +22,45 @@ 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
+
 # Load the pickled XGBoost model
 model_input = joblib.load("model_1.joblib")
 
-@app.post("/sepsis_prediction")
-    async def predicts(input:model_input):
+
+ @app.post("/sepsis_prediction")
+ 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']]
 
     XGB= Pipeline([
     ("col_trans", full_pipeline),
     ("feature_selection", SelectKBest(score_func=f_classif, k='all')),
     ("model", BaggingClassifier(base_estimator=XGBClassifier(random_state=42)))
 ])
-        return prediction
+
+#print(model_input)
+    df = pd.DataFrame([input])
+    final_input = np.array(predict_input.fit_transform(df), dtype = np.str)
+    prediction = model.predict(np.array([[final_input]]).reshape(1, 1))
+
+    return prediction
+
+if __name__ == '__main__':
+    uvicorn.run("Main:app", reload = True)
+