import streamlit as st
from langchain_groq import ChatGroq
from langchain.schema import HumanMessage, AIMessage

GROQ_API_KEY='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'
# Initialize the ChatGroq model
llm = ChatGroq(temperature=0, model_name='llama-3.1-8b-instant', groq_api_key=GROQ_API_KEY)


st.title("LLM Bot with ChatGroq")

# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = []

# Display chat messages from history on app rerun
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# React to user input
if prompt := st.chat_input("What is your question?"):
    # Display user message in chat message container
    st.chat_message("user").markdown(prompt)
    
    # Add user message to chat history
    st.session_state.messages.append({"role": "user", "content": prompt})

    # Generate AI response
    response = llm([HumanMessage(content=prompt)])
    
    # Display AI response in chat message container
    with st.chat_message("assistant"):
        st.markdown(response.content)
    
    # Add AI response to chat history
    st.session_state.messages.append({"role": "assistant", "content": response.content})