from fastapi import FastAPI
from pydantic import BaseModel
import joblib 
import numpy as np 


class SepssisInput(BaseModel):
    PRG:float
    PL:float	
    PR:float	
    SK:float	
    TS:float	
    M11:float
    Age:float	
    Insurance:int


model=joblib.load("models/sepssis_model_v1.pkl")

app=FastAPI()


@app.get("/")
def home_page():
    return "Welcome to the API "


@app.post("/predict")
def inference_sepssis(sepssis_features:SepssisInput):
    input_data=np.array([[
        sepssis_features.PRG,
        sepssis_features.PL,
        sepssis_features.PR,
        sepssis_features.SK,
        sepssis_features.TS,
        sepssis_features.M11,
        sepssis_features.Age,
        sepssis_features.Insurance
    ]])

    label_predict=model.predict(input_data)

    sepssis_mapping={
        0:"Negative",
        1:"Positive"
    }
    
    clase_predict=sepssis_mapping[label_predict[0]]
    return {"Predict_for_Sepssis":clase_predict}