# -----------------------------------------
# LIBRARY IMPORTS AND INTRODUCTION
# -----------------------------------------

import streamlit as st
from langchain.llms import OpenAI

# -----------------------------------------
# FUNCTION DEFINITIONS
# -----------------------------------------

# This function uses the "text-davinci-003" model to generate a response to a given question.
def load_answer(question):
    llm = OpenAI(model_name="text-davinci-003", temperature=0)
    answer = llm(question)
    return answer

# -----------------------------------------
# STREAMLIT UI CONFIGURATION
# -----------------------------------------

# Set the Streamlit page title and icon.
st.set_page_config(page_title="Langchain Prototype", page_icon=":robot:")

# Display a header for the application.
st.header("LLM App 1")

# Function to get text input from the user.
def get_text():
    input_text = st.text_input("You: ", key="input")
    return input_text

# Get the user input.
user_input = get_text()

# Fetch the response from the LLM.
response = load_answer(user_input)

# Display a button on the Streamlit page.
submit = st.button('Generate')  

# Actions for when the 'Generate' button is clicked.
if submit:
    st.subheader("Answer:")
    st.write(response)

# -----------------------------------------
# END OF STREAMLIT APPLICATION
# -----------------------------------------