app.py

import gradio as gr
from transformers import pipeline

# Initialize the sentiment analysis pipeline with your model
sentiment_pipeline = pipeline("sentiment-analysis", model="quocviethere/imdb-roberta")

def analyze_sentiment(text):
    result = sentiment_pipeline(text)[0]
    label = result['label']
    score = result['score']
    sentiment = "Positive 😊" if label == "POSITIVE" else "Negative 😞"
    confidence = f"Confidence: {round(score * 100, 2)}%"
    return sentiment, confidence

# Define the Gradio interface using the updated API
iface = gr.Interface(
    fn=analyze_sentiment,
    inputs=gr.Textbox(
        lines=5,
        placeholder="Enter a movie review here...",
        label="Movie Review"
    ),
    outputs=[
        gr.Textbox(label="Sentiment"),
        gr.Textbox(label="Confidence")
    ],
    title="IMDb Sentiment Analysis with RoBERTa",
    description="Analyze the sentiment of movie reviews using a fine-tuned RoBERTa model.",
    examples=[
        ["I loved the cinematography and the story was captivating."],
        ["The movie was a complete waste of time. Poor acting and boring plot."]
    ],
    theme="default"
)

# Launch the interface
iface.launch()