Update app.py

app.py

@@ -1,42 +1,4 @@
-pip install langchain_groq
-GROQ_API_KEY=your_groq_api_key_here
-from dotenv import load_dotenv
 import os
-
-# Load environment variables
-load_dotenv()
-
-# Access the Groq API key
-groq_api_key = os.getenv("GROQ_API_KEY")
-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.")
-        import os
 import logging
 from dotenv import load_dotenv
 import streamlit as st