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| from langchain_community.llms.openai import OpenAI | |
| from dotenv import load_dotenv | |
| import os | |
| load_dotenv() # load environment variables from .env | |
| print(os.getenv("OPENAI_API_KEY")) | |
| import streamlit as st | |
| # Function to load OpenAI model and get response | |
| def get_openai_response(question): | |
| llm = OpenAI(openai_api_key=os.getenv("OPENAI_API_KEY"), | |
| temperature=0.9) | |
| response = llm(question) | |
| return response | |
| # initialize our Streamlit App | |
| st.set_page_config(layout="wide", page_title="Q&A Demo") | |
| st.header("LangChain Application") | |
| input = st.text_input("Input: ", key="input") | |
| response = get_openai_response(input) | |
| submit = st.button("Ask the Question") | |
| # if submit is clicked | |
| if submit: | |
| st.subheader("The Response is") | |
| st.write(response) | |