# Q&A Chatbot
from langchain_community.llms.openai import OpenAI
from dotenv import load_dotenv
import os
import streamlit as st

# Load environment variables from .env.
load_dotenv()

# Function to load OpenAI models and get responses
def get_openai_response(question):
    # Instantiate the OpenAI class with necessary parameters
    llm = OpenAI(openai_api_key=os.getenv("OPENAI_API_KEY"), model_name="gpt-3.5-turbo-instruct", temperature=0.5)
    # Use the invoke method to get the response
    response = llm.invoke(question)
    return response

# Initialize our Streamlit app
st.set_page_config(page_title='Q&A Demo')
st.header("Langchain Application")

# Streamlit input field
input_question = st.text_input("Input: ", key="input")

# Streamlit button to submit the question
submit = st.button("Ask the question")

# If the "Ask the question" button is clicked
if submit and input_question:
    # Get the response from OpenAI
    response = get_openai_response(input_question)
    # Display the response
    st.subheader("The Response is")
    st.write(response)