import os import streamlit as st from langchain import OpenAI from langchain.chains import ConversationChain from langchain.chains.conversation.memory import ConversationSummaryMemory from streamlit_chat import message from dotenv import load_dotenv load_dotenv() if "conversation" not in st.session_state: st.session_state["conversation"] = None if "messages" not in st.session_state: st.session_state["messages"] = [] # Setting page title and header st.set_page_config(page_title="Chat GPT Clone", page_icon=":robot_face:") st.markdown( "

How can I assist you?

", unsafe_allow_html=True, ) st.sidebar.title("😎") summarise_button = st.sidebar.button("Summarise the conversation", key="summarise") if summarise_button: summarise_placeholder = st.sidebar.write( "Nice chatting with you my friend ❤️:\n\n" + st.session_state["conversation"].memory.buffer ) def getresponse(userInput: str): if st.session_state["conversation"] is None: llm = OpenAI( temperature=0, openai_api_key=os.getenv("OPENAI_API_KEY"), model_name="text-davinci-003", # we can also use 'gpt-3.5-turbo' ) st.session_state["conversation"] = ConversationChain( llm=llm, verbose=True, memory=ConversationSummaryMemory(llm=llm) ) response = st.session_state["conversation"].predict(input=userInput) print(st.session_state["conversation"].memory.buffer) return response response_container = st.container() container = st.container() with container: with st.form(key="my_form", clear_on_submit=True): user_input = st.text_area("Your question goes here:", key="input", height=100) submit_button = st.form_submit_button(label="Send") if submit_button: st.session_state["messages"].append(user_input) model_response = getresponse(user_input) st.session_state["messages"].append(model_response) with response_container: for i in range(len(st.session_state["messages"])): if (i % 2) == 0: message( st.session_state["messages"][i], is_user=True, key=str(i) + "_user", ) else: message(st.session_state["messages"][i], key=str(i) + "_AI")