app.py

from langchain import HuggingFaceHub

from dotenv import load_dotenv

import streamlit as st

# variable d'environement
load_dotenv()

#  HuggingFace model 
llm_huggingface = HuggingFaceHub(repo_id="google/flan-t5-large", model_kwargs={"temperature": 0.0, "max_length": 64})

# Streamlit app 
st.set_page_config(page_title="Chatbot")
st.header('Langchain Application')

# Function to get responsr
def get_huggingface_response(question):
    response = llm_huggingface(question) 
    return response

# Streamlit input
user_input = st.text_input("Input: ", key="input")

# Streamlit button
submit = st.button('Generate')


if submit: 
   
    response = get_huggingface_response(user_input)
    st.subheader("The response is ")
    st.write(response)