# src/qa_citation.py — Question Answering with citation

from transformers import pipeline

# Load a QA pipeline with a pre-trained model
qa_pipeline = pipeline("question-answering", model="deepset/roberta-base-squad2")

def answer_question(question, context):
    """Answer the question based on context and provide citation info."""
    result = qa_pipeline(question=question, context=context)
    answer = result['answer']
    score = result['score']
    # For citation, we’ll just return the context snippet here (could be URL in production)
    citation = "Context snippet used as citation"
    return {
        "answer": answer,
        "score": score,
        "citation": citation
    }

if __name__ == "__main__":
    context = (
        "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France. "
        "It was built between 1887 and 1889 as the entrance to the 1889 World's Fair."
    )
    question = "When was the Eiffel Tower built?"
    result = answer_question(question, context)
    print("Answer:", result['answer'])
    print("Score:", result['score'])
    print("Citation:", result['citation'])