app.py

import gradio as gr
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline


class EmotionClassifier:
    def __init__(self):
        self.model = AutoModelForSequenceClassification.from_pretrained("barbieheimer/MND_TweetEvalBert_model")
        self.tokenizer = AutoTokenizer.from_pretrained("barbieheimer/MND_TweetEvalBert_model")
        self.pipeline = pipeline(
            "text-classification",
            model=self.model,
            tokenizer=self.tokenizer,
            return_all_scores=True,
        )

    def predict(self, input_text: str):
        pred = self.pipeline(input_text)[0]
        result = {
            "Anger 😠": pred[0]["score"],
           "Joy 😂": pred[1]["score"],
           "Surprise 😲": pred[2]["score"],
           "Sadness 😭": pred[3]["score"],
        }
        return result


def main():
    model = EmotionClassifier()
    iface = gr.Interface(
        fn=model.predict,
        inputs=gr.inputs.Textbox(
            lines=3,
            placeholder="Type a phrase that has some emotion",
            label="Input Text",
        ),
        outputs="label",
        title="Emotion Classification",
        examples=[
    ["The movie was a bummer."],
    ["I cannot wait to watch all these movies!"],
    ["The ending of the movie really irks me, gives me the ick fr."],
    ["The protagonist seems to have a lot of hope...."]
],
    )

    iface.launch()


if __name__ == "__main__":
    main()