##Q&A chatbot
from langchain.llms import OpenAI
from dotenv import load_dotenv
load_dotenv() #take the environment variable from .env 
import streamlit as st
from langchain.chat_models import ChatOpenAI
import os

##function to load OpenAI model and get responses
def got_openai_responses(question):
    llm=OpenAI(openai_api_key=os.getenv("OPEN_API_KEY"),model_name="gpt-3.5-turbo-instruct",temperature=0.5)
    response=llm(question)
    return response
   
#initialize streamit app

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

st.header("Langchain Application")
    
input=st.text_input("input :",key="input")
    
response=got_openai_responses(input)

    
submit=st.button("Ask the question")

##if ask button is clicked


if submit:
       st.subheader("the Responses is")
       st.write(response)
'''import os
import streamlit as st
from dotenv import load_dotenv
from langchain.chat_models import ChatOpenAI

load_dotenv()  # load environment variables from .env

# Function to get response from OpenAI
def got_openai_responses(question):
    llm = ChatOpenAI(openai_api_key=os.getenv("OPEN_API_KEY"), model_name="gpt-3.5-turbo", temperature=0.5)
    response = llm.invoke(question)
    return response.content if hasattr(response, "content") else response

# Streamlit UI
st.set_page_config(page_title="Q&A Demo")
st.header("LangChain Chatbot")

input = st.text_input("Ask your question:", key="input")
submit = st.button("Ask")

if submit and input:
    response = got_openai_responses(input)
    st.subheader("Response:")
    st.write(response)'''