Update app.py

app.py

@@ -9,7 +9,34 @@ from langchain.vectorstores import FAISS
 from langchain.memory import ConversationBufferMemory
 from langchain.chains import ConversationalRetrievalChain
 from langchain_groq import ChatGroq
+from langchain_groq import ChatGroq
+from langchain.memory import ConversationBufferMemory
+from langchain.chains import ConversationalRetrievalChain
 
+def get_conversation_chain(vectorstore):
+    try:
+        # Initialize Groq's Chat model
+        llm = ChatGroq(
+            model="llama2-70b-4096",  # You can use other models like "mixtral-8x7b-32768"
+            temperature=0.5,
+            groq_api_key=groq_api_key
+        )
+        
+        # Set up memory for the conversation
+        memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
+        
+        # Create the conversational retrieval chain
+        conversation_chain = ConversationalRetrievalChain.from_llm(
+            llm=llm,
+            retriever=vectorstore.as_retriever(),
+            memory=memory
+        )
+        
+        logging.info("Conversation chain created successfully.")
+        return conversation_chain
+    except Exception as e:
+        logging.error(f"Error creating conversation chain: {e}")
+        st.error("An error occurred while setting up the conversation chain.")
 # Load environment variables
 load_dotenv()