Update app.py

app.py

@@ -13,7 +13,7 @@ with st.sidebar:
     st.write('This chatbot is created using the open-source Llama model from Meta.')
     
     # Use Hugging Face API Key from secrets or environment
-    api_key = os.getenv("HUGGINGFACE_API_KEY")
+    api_key = os.getenv("llama3")
 
     if not api_key:
         st.error("Hugging Face API key is missing!")
@@ -28,13 +28,16 @@ with st.sidebar:
         st.stop()
 
     st.subheader('Models and parameters')
-    selected_model = st.sidebar.selectbox('Choose a Llama model', ['Llama-3.2-1B', 'Llama-7B'], key='selected_model')
     
-    # Model configurations based on selection
-    if selected_model == 'Llama-3.2-1B':
-        model_id = "meta-llama/Llama-3.2-1B"
-    elif selected_model == 'Llama-7B':
-        model_id = "meta-llama/Llama-7B"
+    # Model selection
+    model_options = [
+        "meta-llama/Llama-3.2-1B", 
+        "meta-llama/Llama-3.2-1B-Instruct", 
+        "meta-llama/Llama-3.2-3B-Instruct", 
+        "meta-llama/Llama-3.2-3B"
+    ]
+    
+    selected_model = st.sidebar.selectbox('Choose a Llama model', model_options, key='selected_model')
 
     temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=1.0, value=0.1, step=0.01)
     top_p = st.sidebar.slider('top_p', min_value=0.01, max_value=1.0, value=0.9, step=0.01)
@@ -56,8 +59,8 @@ st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
 
 # Load the tokenizer and model
 try:
-    tokenizer = AutoTokenizer.from_pretrained(model_id)
-    model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
+    tokenizer = AutoTokenizer.from_pretrained(selected_model)
+    model = AutoModelForCausalLM.from_pretrained(selected_model, torch_dtype=torch.bfloat16, device_map="auto")
 except Exception as e:
     st.error(f"Error loading model: {e}")
     st.stop()