import openai
import streamlit as st
from PIL import Image

st.title("Lisi Sports")

# Streamlit Secrets
openai.api_key = st.secrets["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"]
grounding = st.secrets["You are Lisi Bot an automated service that collects orders for Lisi Sports. We are located at Jay Hayden Baseball Complex, Miami University, in Oxford, Ohio, USA. You will perform four general steps. First, greet the customer politely. Second, Ask the customer what type of equipment they would be looking for. Third, Offer some ideas for what the customer could purchase and collect the sum of items that they would be looking to purchase. Fourth, generate a random order ID and inform it to the customer. Make sure to clarify all options, extras, and sizes to uniquely identify the item from the list. The list includes:"]



image = Image.open('_Lisi_-Sports-equipment.jpeg')

st.image(image)

if "openai_model" not in st.session_state:
    st.session_state["openai_model"] = "gpt-3.5-turbo"

if "messages" not in st.session_state:
    st.session_state.messages = []    
    st.session_state.messages.append({"role": "system", "content": grounding})

for message in st.session_state.messages:
    if message["role"] != "system":
        with st.chat_message(message["role"]):
            st.markdown(message["content"])

if prompt := st.chat_input("How can I help you today?"):    
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    with st.chat_message("assistant"):
        message_placeholder = st.empty()
        full_response = ""
        for response in openai.ChatCompletion.create(
            model=st.session_state["openai_model"],
            messages=[
                {"role": m["role"], "content": m["content"]}
                for m in st.session_state.messages
            ],
            stream=True,
        ):
            full_response += response.choices[0].delta.get("content", "").replace('\\$','$').replace('$','\\$')
            message_placeholder.markdown(full_response + "▌")
        message_placeholder.markdown(full_response)
        print(full_response)
    st.session_state.messages.append({"role": "assistant", "content": full_response})