from transformers.utils import logging
logging.set_verbosity_error()

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("all-MiniLM-L6-v2")

import gradio as gr
from sentence_transformers import util


def compare_sentences(sentence1, sentence2):
    embeddings1 = model.encode([sentence1], convert_to_tensor=True)
    embeddings2 = model.encode([sentence2], convert_to_tensor=True)
    output = util.cos_sim(embeddings1, embeddings2)
    return float(output[0][0])

sentence1 = input("Enter the first sentence: ")
sentence2 = input("Enter the second sentence: ")

similarity_score = compare_sentences(sentence1, sentence2)

print(similarity_score)


***
for i in range(len(sentences1)):
    print("{} \t\t {} \t\t Score: {:.4f}".format(sentences1[i],
                                                 sentences2[i],
                                                 cosine_scores[i][I]))


#added
demo = gr.Interface(fn=compare, inputs="text", outputs="text")
demo.launch()


def compare(name):
    return model.encode(name, convert_to_tensor=True)

iface.launch()