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prediction.py

@@ -17,13 +17,17 @@ def get_feeling(number):
   feeling = number_to_feeling.get(str(number), "Unknown feeling")
   return feeling
 
-with st.spinner("Loading the model, please wait..."):
-  the_model = tf.keras.models.load_model('model.keras', custom_objects={'KerasLayer': tf_hub.KerasLayer})
+# Load the model function
+def load_model():
+    return tf.keras.models.load_model('model.keras', custom_objects={'KerasLayer': tf_hub.KerasLayer})
 
 def app():
   st.header('Prediction', divider='rainbow')
 
   user_input = st.text_input("Enter your text here:")
+  if 'the_model' not in st.session_state:
+    with st.spinner("Loading the model, please wait..."):
+        st.session_state.the_model = load_model()
   if st.button('Predict', type="secondary"):
     data = {
       "text_processed": [
@@ -33,7 +37,7 @@ def app():
     df = pd.DataFrame(data)
     with st.spinner("Making prediction..."):
       # Replace with your preprocessing and prediction code
-      predictions = the_model.predict(df)
+      predictions = st.session_state.the_model.predict(df)
       predicted_class = np.argmax(predictions, axis=1)
       the_sentiment = predicted_class[0]