Update app.py

app.py

@@ -3,9 +3,17 @@ from streamlit_chat import message
 from streamlit_extras.colored_header import colored_header
 from streamlit_extras.add_vertical_space import add_vertical_space
 from hugchat import hugchat
+from transformers import AutoModelForCausalLM
 
 st.set_page_config(page_title="HugChat - An LLM-powered Streamlit app")
 
+def check_model(model_name):
+    try:
+        model = AutoModelForCausalLM.from_pretrained(model_name)
+        st.write(f"Model {model_name} loaded successfully.")
+    except Exception as e:
+        st.write(f"Failed to load model {model_name}. Error: {str(e)}")
+
 # Sidebar contents
 with st.sidebar:
     st.title('🤗💬 HugChat App')
@@ -13,7 +21,7 @@ with st.sidebar:
     ## About
     This app is an LLM-powered chatbot built using:
     - [Streamlit](https://streamlit.io/)
-    - [OpenAssistant/oasst-sft-6-llama-30b-xor](https://huggingface.co/OpenAssistant/oasst-sft-6-llama-30b-xor) LLM model
+    - [OpenAssistant/oasst-sft-6-llama-30b-xor] LLM model
     
     💡 Note: No API key required!
     ''')
@@ -45,7 +53,8 @@ with input_container:
 # Response output
 ## Function for taking user prompt as input followed by producing AI generated responses
 def generate_response(prompt):
-    chatbot = hugchat.ChatBot()
+    chatbot = hugchat.ChatBot(model_name="gpt3") # For GPT-3
+    # chatbot = hugchat.ChatBot(model_name="gpt4") # For GPT-4
     response = chatbot.chat(prompt)
     return response
 
@@ -59,4 +68,8 @@ with response_container:
     if st.session_state['generated']:
         for i in range(len(st.session_state['generated'])):
             message(st.session_state['past'][i], is_user=True, key=str(i) + '_user')
-            message(st.session_state["generated"][i], key=str(i))
+            message(st.session_state["generated"][i], key=str(i))
+
+# Check the model
+check_model("gpt3") # For GPT-3
+# check_model("gpt4") # For GPT-4