Update app.py

app.py

@@ -1,10 +1,7 @@
 import streamlit as st
 import pandas as pd
 import pickle
-from sklearn.naive_bayes import GaussianNB
-import joblib
 
-# Load the trained model
 # Load the trained model using pickle
 with open('naive_bayes_model.pkl', 'rb') as file:
     model = pickle.load(file)
@@ -12,8 +9,9 @@ with open('naive_bayes_model.pkl', 'rb') as file:
 # Define the Streamlit app
 def main():
     st.title("Crop Recommendation Model")
+    st.write("Developed by: Adil")
     st.write("This is a simple web app to make predictions using a Naive Bayes model.")
-
+    
     st.sidebar.header("Enter Features")
 
     # Input fields for each feature
@@ -38,5 +36,9 @@ def main():
         st.header("Prediction")
         st.write("Predicted crop:", prediction[0])
 
+        # Display the labels in a well-formatted box
+        st.info("Labels the model can predict:")
+        st.write(model.classes_)
+
 if __name__ == '__main__':
     main()