import os

import streamlit as st
from dotenv import load_dotenv
from langchain_openai import OpenAI  # Ensure this import is correct for your setup

# Load environment variables
load_dotenv()

# Initialize the OpenAI object with your API key
api_key = os.getenv('OPEN_API_KEY')  # Make sure you have this in your .env file
llm = OpenAI(api_key=api_key)
os.environ["OPENAI_API_KEY"]=os.getenv("OPENAI_API_KEY")
##LAngsmith Tracking 
os.environ['LANGCHAIN_TRACING_V2']="true"
os.environ['LANGCHAIN_API_KEY']=os.getenv("LANGCHAIN_API_KEY")
def get_openai_response(question):
    model_id = "gpt-3.5-turbo"  # Ensure this is a valid model ID
    # response = llm.create_completion(prompt=question, model=model_id)  # Adjust according to actual method signature
    llm=OpenAI(openai_api_key=os.environ["OPEN_API_KEY"],temperature=0.6)
    response=llm(question)
    return response

st.set_page_config(page_title="Q&A Demo")
st.header("Chat Open For All")
user_input = st.text_input("Input:", key="input")  # Changed variable name from 'input' to 'user_input'
submit = st.button("Ask the question")

if submit and user_input:  # Check if 'submit' is pressed and 'user_input' is not empty
    response = get_openai_response(user_input)
    st.subheader("The Response is:")
    st.write(response)  # Adjust based on how the response is structured