app.py

from transformers import T5ForConditionalGeneration, T5Tokenizer

# Load the model and tokenizer
model = T5ForConditionalGeneration.from_pretrained("miiiciiii/I-Comprehend_qg")
tokenizer = T5Tokenizer.from_pretrained("miiiciiii/I-Comprehend_qg")

def get_question(context, answer, model, tokenizer):
    """Generate a question for the given answer and context."""
    answer_span = context.replace(answer, f"<hl>{answer}<hl>", 1) + "</s>"
    inputs = tokenizer(answer_span, return_tensors="pt")
    question = model.generate(input_ids=inputs.input_ids, max_length=50)[0]

    return tokenizer.decode(question, skip_special_tokens=True)

# Define the context and answer
context = "The Eiffel Tower is located in Paris and is one of the most famous landmarks in the world."
answer = "Eiffel Tower"

# Generate the question
question = get_question(context, answer, model, tokenizer)
print("Generated Question:", question)