Update app.py

app.py

@@ -1,63 +1,61 @@
 import os
-import json
-
 import streamlit as st
 from groq import Groq
 
-
-# streamlit page configuration
+# Streamlit page configuration
 st.set_page_config(
-    page_title="LLAMA 3.1. Chat",
+    page_title="LLAMA 3.1 Chat",
     page_icon="🦙",
     layout="centered"
 )
 
-working_dir = os.path.dirname(os.path.abspath(__file__))
-config_data = json.load(open(f"{working_dir}/config.json"))
+# Retrieve API key from Hugging Face Secrets
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 
-GROQ_API_KEY = config_data["GROQ_API_KEY"]
+if not GROQ_API_KEY:
+    st.error("⚠️ Error: GROQ_API_KEY is missing! Please add it to Hugging Face Secrets.")
+    st.stop()
 
-# save the api key to environment variable
-os.environ["GROQ_API_KEY"] = GROQ_API_KEY
+# Initialize Groq client with API key
+client = Groq(api_key=GROQ_API_KEY)
 
-client = Groq()
-
-# initialize the chat history as streamlit session state of not present already
+# Initialize the chat history in Streamlit session state if not present already
 if "chat_history" not in st.session_state:
     st.session_state.chat_history = []
 
+# Streamlit page title
+st.title("🦙 LLAMA 3.1 ChatBot")
 
-# streamlit page title
-st.title("🦙 LLAMA 3.1. ChatBot")
-
-# display chat history
+# Display chat history
 for message in st.session_state.chat_history:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
-
-# input field for user's message:
+# Input field for user's message
 user_prompt = st.chat_input("Ask LLAMA...")
 
 if user_prompt:
-
     st.chat_message("user").markdown(user_prompt)
     st.session_state.chat_history.append({"role": "user", "content": user_prompt})
 
-    # sens user's message to the LLM and get a response
+    # Send user's message to the LLM and get a response
     messages = [
         {"role": "system", "content": "You are a helpful assistant"},
         *st.session_state.chat_history
     ]
 
-    response = client.chat.completions.create(
-        model="llama-3.1-8b-instant",
-        messages=messages
-    )
+    try:
+        response = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=messages
+        )
+
+        assistant_response = response.choices[0].message.content
+        st.session_state.chat_history.append({"role": "assistant", "content": assistant_response})
 
-    assistant_response = response.choices[0].message.content
-    st.session_state.chat_history.append({"role": "assistant", "content": assistant_response})
+        # Display the LLM's response
+        with st.chat_message("assistant"):
+            st.markdown(assistant_response)
 
-    # display the LLM's response
-    with st.chat_message("assistant"):
-        st.markdown(assistant_response)
+    except Exception as e:
+        st.error(f"⚠️ Error: {str(e)}")