app.py

import gradio as gr
from transformers import pipeline
import torch
# Load the sentiment analysis model
sentiment_analyzer = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")

def analyze_sentiment(input_text):
    # Analyze the sentiment of the input text
    result = sentiment_analyzer(input_text)
    sentiment_score = result[0]['label']
    return sentiment_score

# Predefined examples
example_inputs = [
    "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."
]

# Create the Gradio interface
interface = gr.Interface(
    fn=analyze_sentiment,
    inputs=gr.Textbox(label="Enter Text", placeholder="Type or paste your sentence or paragraph here...", lines=5),
    outputs=gr.Textbox(label="Predicted Sentiment (1 to 5 stars)"),
    examples=example_inputs,
    title="Sentiment Analysis App",
    description="Enter a sentence or paragraph and click the button to analyze the sentiment. The output will show a score from 1 to 5 stars."
)

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