Create app.py

app.py

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+import streamlit as st
+import pickle
+
+# Load the pre-trained phishing detection model from the .pkl file
+with open('phishing (2).pkl', 'rb') as model_file:
+    phishing_model = pickle.load(model_file)
+
+def is_phishing(url):
+    # Replace this with your actual prediction logic
+    # Example: You might need to preprocess the URL before making predictions
+    # prediction = phishing_model.predict(preprocess(url))
+    prediction = phishing_model.predict([url])  # Assuming the model expects a list of URLs
+    return prediction[0]
+
+def main():
+    st.title('Phishing Detection App')
+    
+    url = st.text_input('Enter URL:')
+    
+    if st.button('Check for Phishing'):
+        result = is_phishing(url)
+        st.write(f'The URL is {"phishing" if result else "not phishing"}')
+
+if __name__ == '__main__':
+    main()