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from transformers import pipeline
import gradio as gr
# Ganti model ke yang multilingual dan compatible!
model_id = "nlptown/bert-base-multilingual-uncased-sentiment"
# Load pipeline
sentiment_model = pipeline("sentiment-analysis", model=model_id)
# Mapping fungsi bintang ke label sentimen
def map_label(star_label):
star = int(star_label.split()[0]) # Ambil angka dari "5 stars", dst
if star <= 2:
return "Negative 😠"
elif star == 3:
return "Neutral 😐"
else:
return "Positive 😊"
# Fungsi prediksi
def predict_sentiment(text):
result = sentiment_model(text)[0]
label = map_label(result['label'])
confidence = round(result['score'] * 100, 2)
return f"Sentiment: {label}\nConfidence: {confidence}%"
# Gradio UI
iface = gr.Interface(
fn=predict_sentiment,
inputs=gr.Textbox(lines=4, placeholder="Tulis pendapatmu di sini..."),
outputs="text",
title="🌐 Multilingual Sentiment Analyzer",
description="Analisis sentimen teks dalam berbagai bahasa menggunakan model multilingual BERT."
)
iface.launch()
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