import streamlit as st
from transformers import AutoModelForSequenceClassification
from transformers import AutoTokenizer
from transformers import TextClassificationPipeline
from transformers import pipeline

from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import pipeline, AutoTokenizer
from transformers import pipeline
from pathlib import Path


onnx_path = Path("onnx")
model = ORTModelForSequenceClassification.from_pretrained(onnx_path, file_name="model_quantized.onnx")
tokenizer = AutoTokenizer.from_pretrained(onnx_path)

st.write("Airi.uz jamoasi amaliyotchilari tomonidan tayyorlangan text classification uchun mo'ljallangan model")
st.write("Ishlatish uchun pastdagi maydonga matn kiriting va model sizga kiritilgan matnni qaysi sohaga aloqador ekanligini ko'rsatadi")
input = st.text_area(label='input_areaf',placeholder='matnni shu yerga kiriting',height=350,max_chars = 5000)
try:
      if st.button(label='bashorat qilish'):
            cls_pipeline = pipeline("text-classification", model=model, tokenizer=tokenizer)
            data = input
            st.info(cls_pipeline(data))
except RuntimeError:
      st.info("Iltimos kamroq malumot kiriting")