"""
按句子分块策略

按句号/问号/感叹号等句子边界分割文本，
然后将小句子合并到不超过 chunk_size 的分块中。
参考 Dify 的 sentence 分块模式。
"""
import logging
import re
from typing import Dict, Any, List, Optional

from .base import BaseChunker, ChunkResult

logger = logging.getLogger(__name__)

# 句子分隔符正则（中英文句号/问号/感叹号/分号）
SENTENCE_PATTERN = re.compile(
    r'(?<=[。！？；.!?;])\s*'
)


class SentenceChunker(BaseChunker):
    """
    按句子分块器

    先按句子边界分割文本，再将相邻句子合并为不超过 chunk_size 的分块。
    保证每个分块都是完整句子的组合，不会在句子中间截断。
    """

    def chunk(self, text: str, metadata: Dict[str, Any] = None) -> List[ChunkResult]:
        """按句子分块"""
        if not text or not text.strip():
            return []

        text = self._clean_text(text)
        metadata = metadata or {}

        # 按句子边界分割
        sentences = SENTENCE_PATTERN.split(text)
        sentences = [s.strip() for s in sentences if s.strip()]

        if not sentences:
            return [ChunkResult(content=text, position=0, metadata={**metadata})]

        # 合并句子为分块（不超过 chunk_size）
        chunks = []
        current = ""
        position = 0

        for sentence in sentences:
            # 如果单个句子就超过 chunk_size，强制作为独立分块
            if len(sentence) > self.chunk_size:
                if current:
                    chunks.append(current)
                    current = ""
                chunks.append(sentence)
                continue

            test = current + sentence if not current else current + " " + sentence
            if len(test) <= self.chunk_size:
                current = test
            else:
                if current:
                    chunks.append(current)
                current = sentence

        if current:
            chunks.append(current)

        # 合并过小的分块
        chunks = self._merge_small_chunks(chunks)

        # 添加重叠
        if self.chunk_overlap > 0 and len(chunks) > 1:
            chunks = self._add_sentence_overlap(chunks)

        # 构建结果
        results = []
        for i, content in enumerate(chunks):
            if content.strip():
                results.append(ChunkResult(
                    content=content.strip(),
                    position=i,
                    metadata={**metadata},
                ))

        return results

    def _add_sentence_overlap(self, chunks: List[str]) -> List[str]:
        """为相邻分块添加句子级重叠"""
        result = [chunks[0]]
        for i in range(1, len(chunks)):
            prev = chunks[i - 1]
            # 从前一个分块取最后一个句子作为重叠
            prev_sentences = SENTENCE_PATTERN.split(prev)
            prev_sentences = [s.strip() for s in prev_sentences if s.strip()]
            if prev_sentences:
                overlap = prev_sentences[-1]
                if len(overlap) <= self.chunk_overlap:
                    combined = overlap + " " + chunks[i]
                    if len(combined) <= self.chunk_size * 1.2:
                        result.append(combined)
                        continue
            result.append(chunks[i])
        return result