app.py

import gradio as gr
from transformers import AutoTokenizer, pipeline

# Load tokenizer dan model dari Hugging Face Hub
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
nlp = pipeline("question-answering", model="chandra10/question_tax_indo", tokenizer=tokenizer)

# Definisikan fungsi untuk Gradio
def answer_question(context, question):
    """
    Menjawab pertanyaan berdasarkan konteks yang diberikan.
    """
    result = nlp(question=question, context=context)
    return result['answer']

# Buat interface Gradio
iface = gr.Interface(
    fn=answer_question,
    inputs=[
        gr.Textbox(lines=5, placeholder="Masukkan konteks di sini..."),
        gr.Textbox(lines=2, placeholder="Masukkan pertanyaan di sini...")
    ],
    outputs="text",
    title="Aplikasi Question Answering Pajak",
    description="Masukkan konteks dan pertanyaan pajak untuk mendapatkan jawaban."
)

# Jalankan interface Gradio
iface.launch()