Conversational_memory for a pandas_dataframe_agent in a Streamlit app

[SynergyWiz]

I am a coding noob, but I have been beating my head against the wall for 6 hours trying to get my LLM to have any memory of the prior message in my Streamlit chat app. I have tried adding memory via st.session_state and Conversational_memory, but neither have worked. I have been troubleshooting with Bard, ChatGPT, Bing, and Claude with no success. Could someone PLEASE help and tell me what I am doing wrong. Thanks in advance for taking a look!

New Chat Functionality

def chat(temperature, model_name,openai_api_key=st.secrets["OPENAI_API_KEY"]):
st.write("# Talk to your data")

Add functionality for Page 1

reset = st.sidebar.button("Reset Chat")

Create a ConversationBufferMemory instance

conversational_memory = ConversationBufferWindowMemory(
memory_key='chat_history',
k=5,
return_messages=True

)

Create agent

agent = create_pandas_dataframe_agent(
    ChatOpenAI(temperature=0.01, model_name=model_name),
    gsheetpd,
    verbose=True,
    agent_type=AgentType.OPENAI_FUNCTIONS,memory=conversational_memory
)


if 'chat_history' not in st.session_state:
    st.session_state['chat_history'] = []
if 'generatedd' not in st.session_state:
    st.session_state['generatedd'] = ["Hello ! Ask me anything about your data 🤗"]

if 'pastt' not in st.session_state:
    st.session_state['pastt'] = ["Hey ! 👋"]

#tools = [CircumferenceTool()]


llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY, temperature=0)

# agent_chain = initialize_agent(tools, llm, agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION, verbose=True, memory=memory)

# def conversational_chat(query):
#         # Pass the conversational_memory object to the agent
#         result = agent_chain.run(query=query, memory=conversational_memory)
#         return result

def conversational_chat(query):
    #st.session_state["chat_history"].append(query)
    #prompt = "\n".join(st.session_state["chat_history"])
    result = agent.run(query=query, memory=conversational_memory, input=user_input)
    
    #st.session_state["chat_history"].append(result)
    return result

#container for the chat history
response_container = st.container()

#container for the user's text input
container = st.container()

with container:
    with st.form(key='my_form', clear_on_submit=True):
        
        user_input = st.text_input("Query:", placeholder="Talk about your data here (:", key='input')
        submit_button = st.form_submit_button(label='Send')
        
    if submit_button and user_input:
        output = conversational_chat(user_input)
        
        st.session_state['pastt'].append(user_input)
        st.session_state['generatedd'].append(output)

if st.session_state['generatedd']:
    with response_container:
        for i in range(len(st.session_state['generatedd'])):
            message(st.session_state["pastt"][i], is_user=True, key=str(i) + '_user', avatar_style="fun-emoji")
            message(st.session_state["generatedd"][i], key=str(i), avatar_style="bottts")
if reset:
    st.session_state["pastt"] = []
    st.session_state["generatedd"] = []