app.py

from transformers import pipeline
import gradio as gr

# Load the text classification model
classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")

# Define the function that runs when the user submits input
def classify_sentiment(text):
    result = classifier(text)[0]
    label = result['label']
    score = result['score']
    return f"{label} ({score:.2f})"

# Build the Gradio app
demo = gr.Interface(
    fn=classify_sentiment,
    inputs=gr.Textbox(lines=2, placeholder="Enter your sentence here..."),
    outputs="text",
    title="Sentiment Classifier",
    description="This app classifies your text as POSITIVE or NEGATIVE using a Hugging Face model."
)

# Launch it
demo.launch()