import streamlit as st
from sklearn import neighbors, datasets

with st.form(key='my_form'):
  sLen = st.slider('sepal length (cm) ', 0.0, 10.0)
  sWid = st.slider('sepal Width (cm) ', 0.0, 10.0)
  pLen = st.slider('petal length (cm) ', 0.0, 10.0)
  pWid = st.slider('petal Width (cm) ', 0.0, 10.0)
  st.form_submit_button('predict')
  
  iris = datasets. load_iris()
X, y = iris.data, iris.target
knn = neighbors.KNeighborsClassifier(n_neighbors=3)
knn.fit(X, y)
predict = knn.predict([[sLen,swid,pLen,pWid]])
st.write(iris.target_names[predict])