import gradio as gr
from transformers import pipeline

# Load model from Hub
classifier = pipeline(
    "sentiment-analysis",
    model="Nav772/distilbert-rotten-tomatoes-sentiment"
)

def predict_sentiment(text):
    """
    Takes user input text and returns sentiment prediction.
    """
    if not text.strip():
        return "Please enter some text."
    
    result = classifier(text)[0]
    label = result["label"]
    confidence = result["score"]
    
    return f"{label} (confidence: {confidence:.2%})"

# Create interface
demo = gr.Interface(
    fn=predict_sentiment,
    inputs=gr.Textbox(
        label="Enter a movie review",
        placeholder="Type your review here...",
        lines=3
    ),
    outputs=gr.Textbox(label="Prediction"),
    title="🎬 Movie Review Sentiment Analyzer",
    description="This model predicts whether a movie review is positive or negative. Fine-tuned on the Rotten Tomatoes dataset using DistilBERT.",
    examples=[
        ["This film was a masterpiece of storytelling and visual effects."],
        ["Boring plot, terrible acting, waste of money."],
        ["It was okay, not great but not terrible either."]
    ],
    theme="soft"
)

demo.launch()