import streamlit as st
from langchain.llms import HuggingFaceHub

# Function to return the response
def load_answer(question):
    if not question:
        return "Please ask a question."
    
    # Initialize the Hugging Face model
    llm = HuggingFaceHub(repo_id="google/flan-t5-large", 
                         model_kwargs={"temperature": 0.7})
    
    # Get response from the model
    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()
submit = st.button('Generate')

# If the generate button is clicked
if submit:
    if user_input:
        response = load_answer(user_input)
        st.subheader("Answer:")
        st.write(response)
    else:
        st.error("Please enter a question!")