main.py

from fastapi import FastAPI, File, UploadFile
from fastapi.responses import StreamingResponse
from fastapi.responses import FileResponse, HTMLResponse
import os
import io
import json

from fastapi import FastAPI
from pydantic import BaseModel
import joblib
import json


app = FastAPI()

class model_input(BaseModel):
    
    pregnancies : int
    Glucose : int
    BloodPressure : int
    SkinThickness : int
    Insulin : int
    BMI : float
    DiabetesPedigreeFunction : float
    Age : int       
        
# loading the saved model
diabetes_model = joblib.load(open('diabetes_model.sav', 'rb'))

@app.post('/diabetes_prediction')
def diabetes_predd(input_parameters : model_input):
    
    input_data = input_parameters.json()
    input_dictionary = json.loads(input_data)
    
    preg = input_dictionary['pregnancies']
    glu = input_dictionary['Glucose']
    bp = input_dictionary['BloodPressure']
    skin = input_dictionary['SkinThickness']
    insulin = input_dictionary['Insulin']
    bmi = input_dictionary['BMI']
    dpf = input_dictionary['DiabetesPedigreeFunction']
    age = input_dictionary['Age']
    
    
    input_list = [preg, glu, bp, skin, insulin, bmi, dpf, age]
    
    prediction = diabetes_model.predict([input_list])
    
    if (prediction[0] == 0):
        return 'The person is not diabetic'
    else:
        return 'The person is diabetic'