"""RAG 管道：标题感知的连续窗口分块。"""
import re

TARGET = 500
MIN_CHUNK = 120
OVERLAP_RATIO = 0.15

def chunk_texts(units: list[dict], target: int = TARGET) -> list[dict]:
    """连续合并相同元数据的相邻单元，避免字幕类文件被切成大量细碎向量。"""
    target = max(MIN_CHUNK, int(target or TARGET))
    chunks = []
    buf: list[str] = []
    buf_len = 0
    active_meta: dict | None = None

    def flush() -> None:
        nonlocal buf, buf_len
        if buf:
            text = "".join(buf)
            if len(text) >= 30:
                chunks.append({"text": text, "meta": dict(active_meta or {})})
        buf, buf_len = [], 0

    for u in units:
        text = str(u.get("text") or "")
        meta = dict(u.get("meta") or {})
        if not text:
            continue
        if active_meta is not None and meta != active_meta:
            flush()
        if active_meta is None or meta != active_meta:
            active_meta = meta
        # 按句子/标点切候选段
        parts = _split_sentences(text)
        for p in parts:
            if buf_len + len(p) > target * 1.15 and buf:
                chunks.append({"text": "".join(buf), "meta": dict(active_meta)})
                # 重叠：保留最后 15% 字符
                overlap = "".join(buf)
                cut = int(len(overlap) * OVERLAP_RATIO)
                keep = overlap[-cut:] if cut > 30 else ""
                buf = [keep] if keep else []
                buf_len = len(keep)
            buf.append(p)
            buf_len += len(p)
    flush()
    return chunks

def _split_sentences(text: str) -> list[str]:
    # 在句号/问号/感叹号/换行后切分，保持小段不小于 30 字
    parts = re.split(r"(?<=[。！？!?；;])\s*|\n+", text)
    merged, cur = [], ""
    for p in parts:
        if not p:
            continue
        cur += p
        if len(cur) >= 30:
            merged.append(cur)
            cur = ""
    if cur:
        merged.append(cur)
    return merged or [text]