ReMe/reme4/components/tokenizer/regex_tokenizer.py
jinliyl a4efc0f776
refactor(reme4): restructure steps packages (#258)
* fix(bm25_index): 修正BM25索引计算中的文档长度归一化问题

修复了在计算BM25相似度时对文档长度进行不正确归一化的bug,确保所有查询都能得到准确的相关性评分。

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* refactor(steps): Rename and adjust indexing step logic

- Rename `scan_changes.py` and `reindex.py` to `clear_and_scan.py`
- Update implementation details of `ScanChangesStep` and `ClearAndScanStep`
- Modify the scheduling mechanism in `WatchChangesStep`
- Adjust step registration and parameter configuration in config files
- Update related tests to align with the new interface changes

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* feat(daily): replace daily CRUD operations with slug provisioning approach

* refactor(tests): migrate CRUD step tests from HTTP server to direct LocalFileStore

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---------

Co-authored-by: huangsen <huangsen.huang@alibaba-inc.com>
2026-05-28 14:30:30 +08:00

24 lines
880 B
Python

"""Regex tokenizer with Chinese character splitting."""
import re
from .base_tokenizer import BaseTokenizer
from ..component_registry import R
@R.register("regex")
class RegexTokenizer(BaseTokenizer):
"""Regex tokenizer: each CJK char is its own token, non-CJK uses word boundaries.
Treating CJK characters as individual tokens avoids needing a Chinese
segmenter while still giving BM25-style indexes useful unigrams.
"""
WORD_PATTERN = re.compile(r"(?u)\b\w\w+\b") # non-CJK words, 2+ chars
CHINESE_PATTERN = re.compile(r"[一-鿿]")
def _tokenize_one(self, text: str, **kwargs) -> list[str]:
# Pull CJK chars first, then strip them out so the word regex only sees the rest.
tokens = self.CHINESE_PATTERN.findall(text)
tokens.extend(self.WORD_PATTERN.findall(self.CHINESE_PATTERN.sub(" ", text)))
return tokens