import gradio as gr
from transformers.utils import logging
logging.set_verbosity_error()

from sentence_transformers import SentenceTransformer
from sentence_transformers import util

def compare(input):
    lines = input.splitlines()
    embeddings1 = model.encode(lines[0], convert_to_tensor=True)
    embeddings2 = model.encode(lines[1], convert_to_tensor=True)
    cosine_scores = util.cos_sim(embeddings1, embeddings2)
    return "Score: {:.4f} \t\t {} \t\t {}".format(cosine_scores[0][0], lines[0], lines[1])

model = SentenceTransformer("all-MiniLM-L6-v2")
demo = gr.Interface(fn=compare, inputs="textarea", outputs="text")
demo.launch()
gr.close_all()