app.py

import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModel

# load the pre-trained model
model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')

# set the app title
st.title("Brazilian Portuguese Sentence Similarity Checker")

# get the input sentences from the user
sentence1 = st.text_input("Enter the first sentence:")
sentence2 = st.text_input("Enter the second sentence:")

# check if both sentences are not empty
if sentence1 and sentence2:
    embedding_1= model.encode(sentence1, convert_to_tensor=True)
    embedding_2 = model.encode(sentence2, convert_to_tensor=True)

    similarity = util.pytorch_cos_sim(embedding_1, embedding_2)
    
    st.write("Similarity score between the sentences:", similarity)