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import streamlit as st
import langchain
from langchain.llms import HuggingFaceHub
#Function to return the response
def load_answer(question):
llm = HuggingFaceHub(repo_id="google/flan-t5-large")
answer=llm(question)
return answer
#App UI starts here
st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
st.header("LangChain Demo")
#Gets the user input
def get_text():
input_text = st.text_input("You: ", key="input")
return input_text
user_input=get_text()
response = load_answer(user_input)
submit = st.button('Generate')
#If generate button is clicked
if submit:
st.subheader("Answer:")
st.write(response)
#App UI starts here
st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
st.header("LangChain Demo")
#Gets the user input
def get_text():
input_text = st.text_input("You: ", key="input")
return input_text
user_input=get_text()
response = load_answer(user_input)
submit = st.button('Generate')
#If generate button is clicked
if submit:
st.subheader("Answer:")
st.write(response)
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