app.py

# import streamlit as st
import streamlit as st

# import openai from langchain_openai
from langchain_openai import OpenAI

# Function to return the response
def load_answer(question):
    llm = OpenAI(model_name="gpt-3.5-turbo-instruct",temperature=0)

    answer=llm.invoke(question)
    return answer

# App UI starts here
st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
st.header("LangChain Demo")

# Gets the user input
def get_text():
    # Add key to text_input to avoid re-rendering
    input_text = st.text_input("User: ", key="input")
    return input_text

# Get user input
user_input=get_text()

# Get response
response = load_answer(user_input)

# Add button to generate response
submit = st.button('Generate')

# If generate button is clicked
if submit:

    st.subheader("Answer:")

    st.write(response)