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import streamlit as st
import os
from groq import Groq
import random
from langchain.chains import ConversationChain
from langchain.chains.conversation.memory import ConversationBufferWindowMemory
from langchain_groq import ChatGroq
from langchain.prompts import PromptTemplate
from dotenv import load_dotenv
import os
load_dotenv()
groq_api_key = os.environ['GROQ_API_KEY']
def main():
st.title("Groq Chat App")
# Add customization options to the sidebar
st.sidebar.title('Select an LLM')
model = st.sidebar.selectbox(
'Choose a model',
['mixtral-8x7b-32768', 'llama2-70b-4096']
)
conversational_memory_length = st.sidebar.slider('Conversational memory length:', 1, 10, value = 5)
memory=ConversationBufferWindowMemory(k=conversational_memory_length)
user_question = st.text_area("Ask a question:")
# session state variable
if 'chat_history' not in st.session_state:
st.session_state.chat_history=[]
else:
for message in st.session_state.chat_history:
memory.save_context({'input':message['human']},{'output':message['AI']})
# Initialize Groq Langchain chat object and conversation
groq_chat = ChatGroq(
groq_api_key=groq_api_key,
model_name=model
)
conversation = ConversationChain(
llm=groq_chat,
memory=memory
)
if user_question:
response = conversation(user_question)
message = {'human':user_question,'AI':response['response']}
st.session_state.chat_history.append(message)
st.write("Chatbot:", response['response'])
if __name__ == "__main__":
main() |