import gradio as gr
from transformers import pipeline

sentiment_analyzer = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")

def analyze_sentiment(text):
    result = sentiment_analyzer(text)
    sentiment = result[0]['label']
    return sentiment

examples = [
    ["I love this product! It's amazing!"],
    ["This was the worst experience I've ever had."],
    ["The movie was okay, not great but not bad either."],
    ["Absolutely fantastic! I would recommend it to everyone."]
]

#Gradio
with gr.Blocks() as demo:
    gr.Markdown("## Sentiment Analysis")

    with gr.Row():
        with gr.Column():
            text_input = gr.Textbox(label="Enter Text", placeholder="Type a sentence or paragraph here ^^...")

        with gr.Column():
            output = gr.Textbox(label="Predicted Sentiment (1-5 stars)", interactive=False)

    analyze_button = gr.Button("Analyze Sentiment", variant="primary")

    gr.Examples(examples=examples, inputs=text_input)

    analyze_button.click(analyze_sentiment, inputs=[text_input], outputs=output)

demo.launch()