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app.py

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+from langchain.llms import OpenAI
+import streamlit as st
+import os
+
+## Function to load OpenAI model and get responses
+
+def get_openai_response(question):
+    llm = OpenAI(openai_api_key=os.getenv("OPENAI_API_KEY"), model_name="gpt-3.5-turbo-instruct", temperature=0.5)
+    response = llm(question)
+    return response
+
+##initialize our streamlit app
+
+st.set_page_config(page_title="Q&A Demo")
+st.header("Langchain Application")
+
+input_text = st.text_input("Input: ", key="input")
+
+submit = st.button("Ask the question")
+
+## If ask button is clicked
+
+if submit:
+    response = get_openai_response(input_text)
+    st.subheader("The Response is")
+    st.write(response)

requirements.txt

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+langchain
+openai
+huggingface_hub
+python-dotenv
+streamlit