Update app.py

app.py

@@ -16,10 +16,14 @@ def get_models():
   model = PeftModel.from_pretrained(model, "NursNurs/T5ForReverseDictionary")
 
   tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large")
+
+  st.write("The assistant is loaded and ready to use!")
+  return model, tokenizer
   
-  st.session_state.model['model'] = model
-  st.session_state.model['tokenizer'] = tokenizer
-  
+  # st.session_state.model['model'] = model
+  # st.session_state.model['tokenizer'] = tokenizer
+
+model, tokenizer = get_models()
 
 def return_top_k(sentence, k=10):
   
@@ -73,13 +77,12 @@ if 'counters' not in st.session_state:
 if 'is_helpful' not in st.session_state:
   st.session_state.is_helpful = {'ask':False}
   
-if 'model' not in st.session_state:
-  st.session_state.model = {'model': False, 'tokenizer': False}
+# if 'model' not in st.session_state:
+#   st.session_state.model = {'model': False, 'tokenizer': False}
 
-@st.cache_resource
-if st.session_state.model['model'] == False:
-  get_models()
-  st.write("The assistant is loaded and ready to use!")
+# if st.session_state.model['model'] == False:
+#   get_models()
+#   st.write("The assistant is loaded and ready to use!")
   
 st.title("You name it!")