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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}) |