import streamlit as st
from agent_util import config_agent, configure_llm

# Streamlit Application Interface
st.sidebar.header("Configure LLM")
st.title("CEC Seller Assistant")
# Model Selection
model_options = ["llama3.2"]
selected_model = st.sidebar.selectbox(
    "Choose the LLM Model", options=model_options, index=0)

# Temperature Setting
temperature = st.sidebar.slider(
    "Set the Temperature", min_value=0.0, max_value=1.0, value=0.5, step=0.1)

llama3, llama3_json = configure_llm(selected_model, temperature)

local_agent = config_agent(llama3, llama3_json)


def run_agent(query):
    config = {"configurable": {"thread_id": "1", "user_id": "1"}}
    output = local_agent.invoke({"question": [query]}, config)
    print(list(local_agent.get_state_history(config)))
    # output = local_agent.invoke({"question": ['hi, my name is cz', query]})
    print("=======")
    return output["generation"]


user_query = st.text_input("Enter your research question:", "")

if st.button("Run Query"):
    if user_query:
        st.write(run_agent(user_query))