import gradio as gr
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

# Load model & tokenizer dari Hugging Face Hub
model = AutoModelForSequenceClassification.from_pretrained("galennolan/indobert-b-p1-indoemotion-5class")
tokenizer = AutoTokenizer.from_pretrained("galennolan/indobert-b-p1-indoemotion-5class")

# Inisialisasi pipeline
emotion_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

# Fungsi prediksi
def predict_emotion(text):
    result = emotion_classifier(text)[0]
    label = result['label']
    score = round(result['score'], 4)
    return f"{label} ({score})"

# Gradio Interface
demo = gr.Interface(fn=predict_emotion,
                    inputs=gr.Textbox(lines=3, placeholder="Masukkan teks..."),
                    outputs="text",
                    title="Klasifikasi Emosi Bahasa Indonesia",
                    description="Model IndoBERT untuk mendeteksi 5 emosi dari teks Bahasa Indonesia.")

# Jalankan saat local testing
if __name__ == "__main__":
    demo.launch()