"""Paragraph / sentence segmentation with batch streaming."""

from __future__ import annotations

import re
from collections.abc import Iterator

from app.engine.models import DocumentBlock
from app.pipeline.nlp import get_nlp


def split_sentences(text: str) -> list[str]:
    """Split a paragraph into sentences (spaCy preferred)."""
    raw = (text or "").strip()
    if not raw:
        return []
    nlp = get_nlp()
    if nlp is not None:
        try:
            doc = nlp(raw)
            sents = [s.text.strip() for s in doc.sents if s.text.strip()]
            if sents:
                return sents
        except Exception:
            pass
    return [
        part.strip()
        for part in re.split(r"(?<=[.!?])\s+", raw)
        if part.strip()
    ]


def iter_paragraph_batches(
    blocks: list[DocumentBlock],
    *,
    batch_paras: int = 20,
) -> Iterator[list[DocumentBlock]]:
    """Yield batches of rewriteable paragraph blocks interleaved with passthrough.

    Each yielded list preserves document order for that slice of blocks.
    Non-rewriteable blocks are included so stitch can keep structure.
    Batching is driven by count of rewriteable paragraphs.
    """
    batch_paras = max(1, min(int(batch_paras), 100))
    batch: list[DocumentBlock] = []
    rewriteable_count = 0

    for block in blocks:
        batch.append(block)
        if block.rewriteable and block.kind == "paragraph":
            rewriteable_count += 1
        if rewriteable_count >= batch_paras:
            yield batch
            batch = []
            rewriteable_count = 0

    if batch:
        yield batch


def word_count(text: str) -> int:
    return len((text or "").split()) if (text or "").strip() else 0