app.py

import gradio as gr
from transformers import pipeline

sentiment_pipeline = pipeline("sentiment-analysis")

def predict_sentiment(text):
    result = sentiment_pipeline(text)[0]
    return f"{result['label']}"

with gr.Blocks(theme=gr.themes.Soft()) as interface:
    gr.Markdown(
        """

        <h1 style='text-align: center;'>Sentiment Analysis App</h1>

        <p style='text-align: center;'>Analyze the sentiment of any review or short text. The model will classify it as <strong>Positive</strong> or <strong>Negative</strong>.</p>

        """,
    )

    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(
                label="Enter your text",
                placeholder="Type your review here...",
                lines=4
            )
            submit_btn = gr.Button("Analyze")

        with gr.Column():
            output_label = gr.Textbox(
                label="Prediction",
                interactive=False
            )

    submit_btn.click(predict_sentiment, inputs=input_text, outputs=output_label)

interface.launch()