apps/nli.py

import requests
import streamlit as st
import time 
from transformers import pipeline
import os
from .utils import query

HF_AUTH_TOKEN = os.getenv('HF_AUTH_TOKEN')
headers = {"Authorization": f"Bearer {HF_AUTH_TOKEN}"}

def write():

	st.markdown("# Natural Language Inference")
	st.sidebar.header("Natural Language Inference")
	st.write(
		"""Here, you can perform Natural Language Inference using the fine-tuned TURNA NLI model. """
	)
	
	hypothesis = st.text_area(label='Hypothesis: ', height=50, 
			value="Temple Bar'da çok sanatçı var.")
	premise = st.text_area(label='Premise: ', height=50, 
			value="Temple Bar herhangi bir müzisyen veya sanatçıdan tamamen yoksundur.")
	url = ("/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fboun-tabi-LMG%2Fturna_nli_nli_tr%26quot%3B%3C%2Fspan%3E)%3C!-- HTML_TAG_END -->
	params = {"max_new_tokens": 8 }
	if st.button("Generate"):
		with st.spinner('Generating...'):
			output = query(f"hipotez: {hypothesis} önerme: {premise}", url, params)
			st.success(output)