app.py

import gradio as gr
from transformers import pipeline

question_gen = pipeline("text2text-generation", model="valhalla/t5-small-qg-hl")

def generate_questions(input_text, num_questions, question_type):
    highlighted_text = input_text
    if question_type == "mcq":
        prefix = "generate questions:"
    elif question_type == "subjective":
        prefix = "generate descriptive questions:"
    else:
        prefix = "generate questions:"
    prompt = f"{prefix} {highlighted_text}"
    questions = question_gen(prompt, max_length=64, num_return_sequences=num_questions)
    return [q['generated_text'] for q in questions]

with gr.Blocks() as demo:
    gr.Markdown("# AI Mock Test Generator")
    input_text = gr.Textbox(lines=10, label="Paste text or content here")
    num_questions = gr.Slider(minimum=1, maximum=10, value=5, label="Number of Questions")
    question_type = gr.Radio(choices=["mcq", "subjective", "mixed"], value="mixed", label="Question Type")
    output = gr.Textbox(label="Generated Questions", lines=10)
    btn = gr.Button("Generate")
    btn.click(fn=generate_questions, inputs=[input_text, num_questions, question_type], outputs=output)

demo.launch()