from transformers import pipeline

# ────────────────────────────────────────────────────────────────
# 3. Question Answering (extractive)
# ────────────────────────────────────────────────────────────────
# Default model: deepset/roberta-base-squad2
#   → Used for: very good balance of speed & accuracy on SQuAD-style questions
#              (finds answer spans in given context)
#              widely used in 2022–2024 documentation & tutorials
#
# Alternative model: deepset/deberta-v3-large-squad2
#   → Used for: significantly higher accuracy (especially hard questions)
#              better at understanding complex context & negation
#              but slower & needs more memory (~435M params)

pipe = pipeline("question-answering")
# pipe = pipeline("question-answering", model="deepset/deberta-v3-large-squad2")

result = pipe(
    question="Which city in Punjab has the biggest textile market?",
    context="Ludhiana is famous for its huge textile and hosiery industry."
)
print(result["answer"])