from __future__ import annotations

from typing import Any, TYPE_CHECKING

from wisent.core.contrastive_pairs.core.pair import ContrastivePair
from wisent.core.contrastive_pairs.huggingface_pairs.atoms import HuggingFaceBenchmarkExtractor
from wisent.core.cli_logger import setup_logger, bind

if TYPE_CHECKING:
    from lm_eval.api.task import ConfigurableTask


__all__ = ["XsumExtractor"]
_LOG = setup_logger(__name__)

task_names = ("xsum",)

class XsumExtractor(HuggingFaceBenchmarkExtractor):
    """Extractor for Xsum benchmark."""


    evaluator_name = "exact_match"
    def extract_contrastive_pairs(
        self,
        lm_eval_task_data: ConfigurableTask,
        limit: int | None = None,
        preferred_doc: str | None = None,
    ) -> list[ContrastivePair]:
        log = bind(_LOG, task=getattr(lm_eval_task_data, "NAME", "unknown"))
        max_items = self._normalize_limit(limit)
        docs = self.load_docs(lm_eval_task_data, max_items, preferred_doc=preferred_doc)
        pairs: list[ContrastivePair] = []
        log.info("Extracting contrastive pairs", extra={"doc_count": len(docs)})

        for doc in docs:
            pair = self._extract_pair_from_doc(doc)
            if pair is not None:
                pairs.append(pair)
                if max_items is not None and len(pairs) >= max_items:
                    break

        if not pairs:
            task_name = getattr(lm_eval_task_data, "NAME", type(lm_eval_task_data).__name__)
            log.warning("No valid pairs extracted", extra={"task": task_name})

        return pairs

    def _extract_pair_from_doc(self, doc: dict[str, Any]) -> ContrastivePair | None:
        log = bind(_LOG, doc_id=doc.get("id", "unknown"))

        try:
            # XSum format: source (document to summarize) and target (gold summary)
            source = doc.get("source", "").strip()
            target = doc.get("target", "").strip()

            if not source or not target:
                log.debug("Skipping doc due to missing source or target", extra={"doc": doc})
                return None

            # Use the source as prompt and target as correct response
            # For incorrect response, use first half of target as a truncated/incomplete summary
            words = target.split()
            if len(words) > 3:
                incorrect = " ".join(words[:len(words)//2])
            else:
                # If target is very short, use empty or single word
                incorrect = words[0] if words else "No summary"

            metadata = {"label": "xsum"}

            return self._build_pair(
                question=source,
                correct=target,
                incorrect=incorrect,
                metadata=metadata,
            )

        except Exception as exc:
            log.error("Error extracting pair from doc", exc_info=exc, extra={"doc": doc})
            return None

