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##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)'''
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