"""Base pipeline with shared SAT preprocessing and reconstruction."""

from abc import ABC, abstractmethod

LABEL_SYMBOLS = {
    "SAME_PARAGRAPH": " ",
    "NEW_PARAGRAPH": "\n\n",
    "NEWLINE": "\n",
}


class BasePipeline(ABC):
    """Base class for newline-fixing inference pipelines."""

    def _split_sentences(self, text: str) -> list[str]:
        sentences = self._sat.split(text, split_on_input_newlines=False, strip_whitespace=False)
        return [s.replace('\n', '').strip() for s in sentences if s.strip()]

    @staticmethod
    def _reconstruct(sentences: list[str], predictions: list[dict]) -> str:
        if not sentences:
            return ""
        parts = [sentences[0]]
        for i, pred in enumerate(predictions):
            sep = LABEL_SYMBOLS.get(pred["label"], " ")
            parts.append(sep + sentences[i + 1])
        return "".join(parts)

    @abstractmethod
    def predict(self, text: str):
        ...