#function to pridiction by user input output tells if person is diabetic or not
import joblib
from sklearn.svm import SVC
import streamlit as st
import numpy as np 
import pandas as pd

# Replace 'model_filename.pkl' with the path to your saved model file
model = joblib.load('svm_model_dibetees.pkl')


def predict_diabetes(Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age):
    # Create a DataFrame of the user input
    input_data = pd.DataFrame({
        'Pregnancies': [Pregnancies],
        'Glucose': [Glucose],
        'BloodPressure': [BloodPressure],
        'SkinThickness': [SkinThickness],
        'Insulin': [Insulin],
        'BMI': [BMI],
        'DiabetesPedigreeFunction': [DiabetesPedigreeFunction],
        'Age': [Age]
    })

    # Use the model to make a prediction
    prediction = model.predict(input_data)

    # Return the prediction
    return prediction[0]


st.title("Dibetees Pridiction using Machine Learning: ")

Pregnancies = st.text_input("Enter number of pregnencies")
Glucose = st.text_input("Enter the Glucose Count")
BP = st.text_input("Enter Blood Pressure")
SkinThickness = st.text_input("Enter Skin Thickness Level")
Insulin = st.text_input("Insulin level")
BMI = st.text_input("BMI level")
DiabetesPedigreeFunction = st.text_input("Enter DiabetesPedigreeFunction")
Age = st.text_input("Enter the age")


input_data = np.array([[Pregnancies, Glucose, BP, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age]])


if st.button("Predict"):
    pridiction = model.predict(input_data)
    st.success("Person is Diabetic" if pridiction == 1 else "Person is not Diabetic")