app.py

from langchain import HuggingFaceHub
from langchain.llms import OpenAI
from dotenv import load_dotenv
import streamlit as st
import os

load_dotenv()

def get_openai_response(question):
    # try:
    #     llm = OpenAI(model="text-davinci-003",openai_api_key=os.getenv("OPEN_API_KEY"),temperature=0.6)
    #     response=llm(question)
    # except:
    llm_hugg = HuggingFaceHub(repo_id="google/flan-t5-large",model_kwargs={'temperature':0, "max_length":64})
    response=llm_hugg(question)
    return response

st.set_page_config(page_title="Q&A Demo")
st.header("Langchain Aplication")

input = st.text_input("Input: ",key="input")
response = get_openai_response(input)
submit = st.button("Ask Question")
if submit:
    st.subheader("The Response is:")
    st.write(response)