src/streamlit_app.py

import pickle
import pandas as pd
import numpy as np
import streamlit as st
import sklearn

model_file = "/model.pkl"
try:
    with open(model_file,'rb') as file:
        model = pickle.load(file)
except FileNotFoundError:
    st.error("The file was not found in the directory")

st.title("FLower Classification using Streamlit on IRIS DATASET")
st.header("Enter your flower features to get the classification prediction")

sepal_length = st.number_input("Enter yuour sepal length") 
sepal_width = st.number_input("Enter yuour sepal width")
petal_length = st.number_input("Enter yuour petal length")
petal_width = st.number_input("Enter yuour petal width")

if st.button("PREDICT"):
    features = np.array([[sepal_length,sepal_width,petal_length,petal_width]])
    prediction = model.predict(features)[0]

    st.subheader("Prediction has been made")
    st.write("Theprediction for your features is",predicton)