Update pages/botsify.py

pages/botsify.py

@@ -2,6 +2,10 @@ import streamlit as st
 from streamlit_chat import message
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
+# Define the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(st.session_state['model_name'])
+model = AutoModelForCausalLM.from_pretrained(st.session_state['model_name'])
+
 if 'conversation' not in st.session_state:
     st.session_state['conversation'] = None
 if 'messages' not in st.session_state:
@@ -15,7 +19,7 @@ st.markdown("<h1 style='text-align: center;'>💻 ChatterBot</h1>", unsafe_allow
 st.subheader("How Can I Help You Today? 🤖")
 
 st.sidebar.title("😎🗝️")
-st.session_state['model_name'] = st.sidebar.text_input("Hugging Face Model Name", value="microsoft/DialoGPT-medium")
+st.session_state['model_name'] = st.sidebar.text_input("Current Model", value="microsoft/DialoGPT-medium")
 summarise_button = st.sidebar.button("Summarise the conversation", key="summarise")
 st.sidebar.image('./chatbot.jpg', width=300, use_column_width=True)
 if summarise_button:
@@ -24,8 +28,6 @@ if summarise_button:
 def get_response(userInput):
 
     if st.session_state['conversation'] is None:
-        tokenizer = AutoTokenizer.from_pretrained(st.session_state['model_name'])
-        model = AutoModelForCausalLM.from_pretrained(st.session_state['model_name'])
         st.session_state['conversation'] = ""
 
     input_ids = tokenizer.encode(userInput + tokenizer.eos_token, return_tensors="pt")