added session state check

app.py

@@ -8,15 +8,16 @@ from emodeepface import check_image_rotation, process_photo
 def load_cached_model():
     return load_model()
 
-# display loading message when app is accessed/refreshed
-loading_message = st.empty()
-loading_message.text("Loading model... Please wait.")
+# If the model and tokenizer aren't already in session state, load them
+if 'model' not in st.session_state:
+    loading_message = st.empty()
+    loading_message.text("Loading model... Please wait.")
+    
+    # begin loading beluga model and tokenizer
+    st.session_state.model, st.session_state.tokenizer = load_cached_model()
 
-# begin loading beluga model and tokenizer
-model, tokenizer = load_cached_model()
-
-# clear loading message
-loading_message.empty()
+    # clear loading message
+    loading_message.empty()
 
 # title webpage
 st.title("Affective Journaling Assistant")
@@ -42,12 +43,20 @@ file_name = st.file_uploader("Please upload your photo.")
 if file_name is not None:
     # capture image with intended rotation
     image = check_image_rotation(file_name)
-    # display the image directly
-    st.image(image, use_column_width=True)
+    
+    # display the image directly with adjusted width
+    st.image(image, width=300)  # Adjust width as needed
+    
+    processing_message = st.empty()
+    processing_message.text("Analyzing your image... Please wait.")
+    
     # process uploaded image
     emotion_predictions = process_photo(file_name) 
     # process emotion predictions
-    result = process_emotions(model, tokenizer, emotion_predictions)
+    result = process_emotions(st.session_state.model, st.session_state.tokenizer, emotion_predictions)
+    
+    processing_message.empty()
+    
     # generate affective journaling prompt based on emotion predictions
     prompt = generate_prompt(result)
     # display journal prompt