app.py

import gradio as gr
from keras.models import load_model
import pickle
import torch
import numpy as np
import pandas as pd
from utils import test_sentences

model = torch.load('bert_classification(0.87).pt')

# Gradio 인터페이스에서 사용할 함수 정의
def predict_sentiment(text):
  logit = test_sentences([text], model)
  sent = np.argmax(logit)

  classes = {0: "중립", 1:"긍정", 2:"부정"}
  sentiment = classes[sent]

  return sentiment

title = "🤷‍♀️🤷‍♂️What is the EMOTION of TWEET❔"
description = "▶트위터 감정 알아보기"


tweet = gr.Interface(
    fn=predict_sentiment,
    inputs=gr.inputs.Textbox(placeholder="Enter tweet here..."),
    outputs=gr.outputs.Textbox(label="Sentiment Prediction"),
    title=title,
    theme="finlaymacklon/boxy_violet",
    description=description
)
tweet.launch(share=True)