Update app.py

app.py

@@ -0,0 +1,27 @@
+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)