app.py

import gradio as gr
from transformers import pipeline

classifier = pipeline('sentiment-analysis', model='distilbert/distilbert-base-uncased-finetuned-sst-2-english')


def analyze_sentiment(text):
    result = classifier(text)
    # The result is a list of dictionaries, e.g., [{'label': 'POSITIVE', 'score': 0.9998}]
    # We extract the label and score for better presentation.
    sentiment_label = result[0]['label']
    sentiment_score = result[0]['score']
    return f"Sentiment: {sentiment_label}, Score: {sentiment_score:.2f}"

# Create and launch the Gradio interface
iface = gr.Interface(
    fn=analyze_sentiment,
    inputs='text',
    outputs='text',
    title='Sentiment Analysis Application',
    description='Enter text to get its sentiment (positive/negative) and score.'
)


# Launch the interface
iface.launch()