Streamlit chatbot connected to MemGPT (OpenAI Back end)

streamChat.py

import streamlit as st
import requests
base_url = "http://localhost:8283/"
headers = {"accept": "application/json"}


st.title("MemGPT Connected Bot")
# check if memgpt server and agents are available

agent_name="agent_1"
user_name=st.text_input("Enter your name", value="Abd")
agent_details_URL=base_url+f"agents?user_id={user_name}"
response = requests.get(agent_details_URL, headers=headers)
response=response.json()
print(response)
if "agent_names" not in response:    
    st.warning('No MemGPT server running', icon="⚠️")
else:

    agent_names=response["agent_names"]
    print(agent_names)
    if len(agent_names)==0:
        st.warning('No agents available. Make sure you set up the agents.', icon="⚠️")
    else:    
        agent_name = st.selectbox("Choose agent", agent_names, index=0)
        
        # 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 up?"):
            # Display user message in chat message container
            st.chat_message("user").markdown(prompt)
            # Add user message to chat history
            print(f"User said {prompt}")
            st.session_state.messages.append({"role": "user", "content": prompt})

            # need to make a megpt call to get the response
            send_message_URL=base_url+"agents/message"
            payload = {
                "user_id": f"{user_name}",
                "agent_id": f"{agent_name}",
                "message": f"{prompt}",
                "stream": False,
                "role": "user"
            }            
            headers = {
                "accept": "application/json",
                "content-type": "application/json"
            }

            response = requests.post(send_message_URL, json=payload, headers=headers)
            response=response.json()
            if "messages" not in response:
                st.warning('Incorrect response from MemGPT', icon="⚠️")
            else:
                list_responses=response["messages"]
                if len(list_responses)<4:
                    st.warning('Incorrect number of responses from MemGPT', icon="⚠️")    
                else:
                    assistant_message=list_responses[2]
                    if "assistant_message" not in assistant_message:
                        st.warning('Missing assistant_message', icon="⚠️")        
                    else:
                        assistant_message=assistant_message["assistant_message"]

                        response = f"{agent_name}: {assistant_message}"
                        # Display assistant response in chat message container
                        with st.chat_message("assistant"):
                            st.markdown(response)
                        # Add assistant response to chat history
                        st.session_state.messages.append({"role": "assistant", "content": response})