LangChainQA / app.py
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from langchain_openai import ChatOpenAI # Import the correct class
from dotenv import load_dotenv
import os
import streamlit as st
load_dotenv() # Load environment variables
# Function to load OpenAI model and get responses
def get_openai_response(question):
# Use ChatOpenAI for chat models like gpt-3.5-turbo
llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.5, openai_api_key=os.getenv("OPENAI_API_KEY"))
response = llm.invoke(question) # Use invoke() instead of __call__()
return response.content
# Initialize Streamlit app
st.set_page_config(page_title="Q&A Demo")
st.header("LangChain Application")
input = st.text_input("Input: ", key="input")
response = get_openai_response(input)
print(type)
submit = st.button("Ask the question")
# If ask button is clicked
if submit:
st.subheader("The response is")
st.write(response)