Update app.py

app.py

@@ -1,44 +1,45 @@
 import streamlit as st
-import os
-from dotenv import load_dotenv
 from groq import Groq
 
-# Load environment variables from .env file
-load_dotenv()
-
-# Get the GROQ API key from the .env file
-API_KEY = os.getenv("GROQ_API_KEY")
-if not API_KEY:
-    st.error("GROQ_API_KEY is not set. Please check your .env file.")
-
-# Initialize the Groq client
-client = Groq(api_key=API_KEY)
-
 # Streamlit App
 st.title("Q&A Application with Groq API")
 st.write("Ask a question and get a response using Groq's AI model!")
 
-# Input prompt from the user
-user_input = st.text_input("Enter your question:", "")
+# Input for API key
+api_key = st.text_input("Enter your GROQ API Key:", type="password")
+
+# Check if API key is provided
+if not api_key:
+    st.warning("Please enter your GROQ API Key to proceed.")
+else:
+    # Initialize the Groq client
+    try:
+        client = Groq(api_key=api_key)
+        st.success("GROQ API Key successfully set!")
+    except Exception as e:
+        st.error(f"Error initializing Groq client: {str(e)}")
+
+    # Input prompt from the user
+    user_input = st.text_input("Enter your question:", "")
 
-# Button to trigger the API call
-if st.button("Get Answer"):
-    if user_input.strip():
-        try:
-            # API call to Groq
-            chat_completion = client.chat.completions.create(
-                messages=[{"role": "user", "content": user_input}],
-                model="llama3-8b-8192"
-            )
-            # Extracting the response
-            response = chat_completion.choices[0].message.content
-            # Display the response
-            st.subheader("Response:")
-            st.write(response)
-        except Exception as e:
-            st.error(f"Error: {str(e)}")
-    else:
-        st.warning("Please enter a valid question.")
+    # Button to trigger the API call
+    if st.button("Get Answer"):
+        if user_input.strip():
+            try:
+                # API call to Groq
+                chat_completion = client.chat.completions.create(
+                    messages=[{"role": "user", "content": user_input}],
+                    model="llama3-8b-8192"
+                )
+                # Extracting the response
+                response = chat_completion.choices[0].message.content
+                # Display the response
+                st.subheader("Response:")
+                st.write(response)
+            except Exception as e:
+                st.error(f"Error: {str(e)}")
+        else:
+            st.warning("Please enter a valid question.")
 
 # Footer
 st.markdown("---")