import streamlit as st
import os

import openai
from openai import OpenAI

# App title
st.set_page_config(page_title="💬 Open AI Chatbot")

# Replicate Credentials
with st.sidebar:
    st.title('💬 Open AI Chatbot')
    st.write('This chatbot is created using the GPT model from Open AI.')
    if 'OPENAI_API_KEY' in st.secrets:
        st.success('API key already provided!', icon='✅')
        openai_api = st.secrets['OPENAI_API_KEY']
    else:
        openai_api = st.text_input('Enter OpenAI API token:', type='password')
        if not (openai_api.startswith('sk-') and len(openai_api)==51):
            st.warning('Please enter your credentials!', icon='⚠️')
        else:
            st.success('Proceed to entering your prompt message!', icon='👉')
    os.environ['OPENAI_API_KEY'] = openai_api

    st.subheader('Models and parameters')
    selected_model = st.sidebar.selectbox('Choose an OpenAI model', ['gpt-3.5-turbo-1106', 'gpt-4-1106-preview'], key='selected_model')
    temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.1, step=0.01)
    st.markdown('📖 Reach out to Sakimilo to learn how to create this app!')

# Store LLM generated responses
if "messages" not in st.session_state.keys():
    st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]

# Display or clear chat messages
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.write(message["content"])

def clear_chat_history():
    st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
st.sidebar.button('Clear Chat History', on_click=clear_chat_history)

def generate_llm_response(prompt_input):
    system_content = ("You are a helpful assistant. "
                       "You do not respond as 'User' or pretend to be 'User'. "
                       "You only respond once as 'Assistant'."
    )

    completion = client.chat.completions.create(
                    model=selected_model,
                    messages=[
                            {"role": "system", "content": system_content},
                    ] + st.session_state.messages,
                    temperature=temperature
    )
    return completion.choices[0].message.content

# User-provided prompt
if prompt := st.chat_input(disabled=not openai_api):
    client = OpenAI()
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.write(prompt)

# Generate a new response if last message is not from assistant
if st.session_state.messages[-1]["role"] != "assistant":
    with st.chat_message("assistant"):
        with st.spinner("Thinking..."):
            response = generate_llm_response(prompt)
            placeholder = st.empty()
            full_response = ''
            for item in response:
                full_response += item
                placeholder.markdown(full_response)
            placeholder.markdown(full_response)
    message = {"role": "assistant", "content": full_response}
    st.session_state.messages.append(message)