comm1

app.py

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+from langchain.llms import OpenAI
+
+from dotenv import load_dotenv
+from langchain import HuggingFaceHub
+import os
+
+load_dotenv()
+
+import streamlit as st
+
+
+def get_openai_response(question):
+    print(question)
+    llm=OpenAI(openai_api_key=os.getenv("OPEN_API_KEY"),model_name='text-davinci-003', temperature=0.6)
+    # response = llm_huggingface.predict(question[0])
+    response = llm(question)
+    return response
+    
+st.set_page_config(page_title='QA demo')
+
+st.header('LangChain APP')
+
+input = st.text_input("Input: ",key="input")
+response=get_openai_response(input)
+
+submit = st.button("Ask the question")
+
+if submit:
+    st.subheader("The response is: ")
+    st.write(response)

requirements.txt

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+langchain
+openai
+huggingface_hub
+langchain_openai
+google-cloud-aiplatform