app.py

import gradio as gr
from transformers import pipeline

# Load the pretrained sentiment pipeline
sentiment_pipeline = pipeline("sentiment-analysis")

def predict_sentiment(text):
    result = sentiment_pipeline(text)[0]
    label = result["label"]
    
    if label == "POSITIVE":
        return "✅ POSITIVE 😊"
    else:
        return "❌ NEGATIVE 😠"

# Gradio Interface
demo = gr.Interface(
    fn=predict_sentiment,
    inputs=gr.Textbox(lines=3, placeholder="Type your sentence here..."),
    outputs="text",
    title="💬 LM Studios Sentiment Detector",
    description="Now powered by a Hugging Face transformer model for smarter predictions.",
    theme="default",
    flagging_mode="never"
)

demo.launch()