app.py

import gradio as gr
from transformers import pipeline
classifier=pipeline("sentiment-analysis")

# Load sentiment analysis pipeline
sentiment_pipeline = pipeline("sentiment-analysis")

text = "I absolutely love this app! It's amazing."

# Define function to use in Gradio
def analyze_sentiment(text):
    result = sentiment_pipeline(text)[0]
    label = result['label']
    score = result['score']
    return f"Sentiment: {label} (confidence: {score})"
    return result

# Create Gradio interface
demo = gr.Interface(fn=analyze_sentiment,
inputs=gr.Textbox(lines=4, placeholder="Enter text here..."),
outputs="text",
title="Sentiment Analysis App",
description="Enter text and get the sentiment prediction using a Hugging Face transformer model.")

# Launch app
if __name__ == "__main__":
    demo.launch()