app.py

import gradio as gr
from transformers import pipeline

classifier = pipeline("text-classification", model='isom5240ust/bert-base-uncased-emotion', return_all_scores=True)

def classify_text(text):

    results = classifier(text)[0]

    max_score = float('-inf')
    max_label = ''

    for result in results:
        if result['score'] > max_score:
            max_score = result['score']
            max_label = result['label']

    return max_label, max_score

# Gradio interface
iface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(placeholder="Enter text here..."),
    outputs=[
        gr.Textbox(label="Label"),
        gr.Textbox(label="Score")
    ],
    title="Text Classification",
    description="Classification for 6 emotions: sadness, joy, love, anger, fear, surprise"
)

iface.launch()