import gradio as gr
from transformers import pipeline

def load_question_generator():
    question_generator = pipeline('text2text-generation', 
                                model='your-username/your-model-name')
    return question_generator

def generate_questions(context, num_questions=3):
    try:
        generator = load_question_generator()
        questions = []
        
        for _ in range(num_questions):
            result = generator(context, max_length=64, num_return_sequences=1)
            questions.append(result[0]['generated_text'])
            
        return "\n\n".join(questions)
    except Exception as e:
        return f"Error generating questions: {str(e)}"

iface = gr.Interface(
    fn=generate_questions,
    inputs=[
        gr.Textbox(lines=5, label="Enter your text context"),
        gr.Slider(minimum=1, maximum=5, value=3, step=1, label="Number of questions")
    ],
    outputs=gr.Textbox(label="Generated Questions"),
    title="Question Generator",
    description="Generate questions from your text using AI",
    examples=[
        ["The Sun is the star at the center of the Solar System. It is a nearly perfect sphere of hot plasma, heated to incandescence by nuclear fusion reactions in its core.", 2],
    ]
)

iface.launch()