app.py

from transformers import pipeline
import gradio as gr

# Load the sentiment analysis pipeline
classifier = pipeline("sentiment-analysis")

# Function to classify the sentiment
def classify_sentiment(sentence):
    try:
        result = classifier(sentence)[0]
        sentiment = "happy" if result['label'] == 'POSITIVE' else "sad"
        return f"The sentence expresses {sentiment} with a confidence of {result['score']:.2f}."
    except Exception as e:
        return f"An error occurred: {str(e)}"

# Create the Gradio interface
iface = gr.Interface(
    fn=classify_sentiment,
    inputs="text",
    outputs="text",
    title="Sentiment Analysis",
    description="Classify if a sentence is happy or sad."
)

# Launch the interface
iface.launch()