import gradio

from src.models.bert import BERTClassifier
from src.utils.utilities import Utility

model = BERTClassifier(model_name='jeevavijay10/nlp-goemotions-bert')

classes = Utility().read_emotion_list()

def predict(inputSentence):
    print(inputSentence)
    predictions = model.evaluate([inputSentence])
    print(f"Predictions: {predictions}")
    return classes[predictions[0]]

gradio.Interface(
    fn=predict,
    inputs="text",
    outputs="text",
    allow_flagging='auto',
    flagging_dir='logs',
    flagging_callback=gradio.SimpleCSVLogger(),
).launch()