app.py

import gradio as gr
from transformers import pipeline

# Force PyTorch backend to avoid loading TensorFlow (and Keras)
classifier = pipeline("text-classification", model="Varnikasiva/sentiment-classification-bert-mini", framework="pt")

def predict(text):
    result = classifier(text)[0]
    return f"Label: {result['label']} (Score: {round(result['score'], 2)})"

gr.Interface(
    fn=predict,
    inputs=gr.Textbox(lines=3, placeholder="Type your text here..."),
    outputs="text",
    title="Sentiment Classification with BERT Mini",
    description="Predicts nuanced emotions like sadness, sarcasm, guilt, happiness, and more."
).launch()