app.py

import gradio as gr
from transformers import pipeline

# Load FLAN-T5 XL model
generator = pipeline("text2text-generation", model="google/flan-t5-xl")

def generate_questions(prompt):
    input_text = (
        f"You are a survey expert. Generate a numbered list of exactly 10 clear and concise survey questions "
        f"based on the following prompt:\n\n\"{prompt}\""
    )
    result = generator(input_text, max_length=512, num_return_sequences=1)[0]['generated_text']
    lines = [line.strip() for line in result.split('\n') if line.strip()]
    questions = []
    for line in lines:
        if line[0].isdigit() and '.' in line:
            parts = line.split('.', 1)
            if len(parts) == 2:
                questions.append(parts[1].strip())
        elif len(questions) < 10:
            questions.append(line)
        if len(questions) == 10:
            break
    return questions + [""] * (10 - len(questions))

with gr.Blocks() as demo:
    gr.Markdown("## 🧠 Smart Survey Question Generator (FLAN-T5-XL)")

    prompt = gr.Textbox(label="Enter your custom prompt")
    generate = gr.Button("Generate 10 Questions")

    qboxes = [gr.Textbox(label=f"Q{i+1}", interactive=False) for i in range(10)]
    generate.click(fn=generate_questions, inputs=prompt, outputs=qboxes)

demo.launch()