test_ai/text_splitter/chinese_recursive_text_spli...

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import re
from typing import List, Optional, Any
from langchain.text_splitter import RecursiveCharacterTextSplitter
import logging
logger = logging.getLogger(__name__)
def _split_text_with_regex_from_end(
text: str, separator: str, keep_separator: bool
) -> List[str]:
# Now that we have the separator, split the text
if separator:
if keep_separator:
# The parentheses in the pattern keep the delimiters in the result.
_splits = re.split(f"({separator})", text)
splits = ["".join(i) for i in zip(_splits[0::2], _splits[1::2])]
if len(_splits) % 2 == 1:
splits += _splits[-1:]
# splits = [_splits[0]] + splits
else:
splits = re.split(separator, text)
else:
splits = list(text)
return [s for s in splits if s != ""]
class ChineseRecursiveTextSplitter(RecursiveCharacterTextSplitter):
def __init__(
self,
separators: Optional[List[str]] = None,
keep_separator: bool = True,
is_separator_regex: bool = True,
**kwargs: Any,
) -> None:
"""Create a new TextSplitter."""
super().__init__(keep_separator=keep_separator, **kwargs)
self._separators = separators or [
"\n\n",
"\n",
"。||",
"\.\s|\!\s|\?\s",
"|;\s",
"|,\s"
]
self._is_separator_regex = is_separator_regex
def _split_text(self, text: str, separators: List[str]) -> List[str]:
"""Split incoming text and return chunks."""
final_chunks = []
# Get appropriate separator to use
separator = separators[-1]
new_separators = []
for i, _s in enumerate(separators):
_separator = _s if self._is_separator_regex else re.escape(_s)
if _s == "":
separator = _s
break
if re.search(_separator, text):
separator = _s
new_separators = separators[i + 1:]
break
_separator = separator if self._is_separator_regex else re.escape(separator)
splits = _split_text_with_regex_from_end(text, _separator, self._keep_separator)
# Now go merging things, recursively splitting longer texts.
_good_splits = []
_separator = "" if self._keep_separator else separator
for s in splits:
if self._length_function(s) < self._chunk_size:
_good_splits.append(s)
else:
if _good_splits:
merged_text = self._merge_splits(_good_splits, _separator)
final_chunks.extend(merged_text)
_good_splits = []
if not new_separators:
final_chunks.append(s)
else:
other_info = self._split_text(s, new_separators)
final_chunks.extend(other_info)
if _good_splits:
merged_text = self._merge_splits(_good_splits, _separator)
final_chunks.extend(merged_text)
return [re.sub(r"\n{2,}", "\n", chunk.strip()) for chunk in final_chunks if chunk.strip()!=""]
if __name__ == "__main__":
text_splitter = ChineseRecursiveTextSplitter(
keep_separator=True,
is_separator_regex=True,
chunk_size=50,
chunk_overlap=0
)
ls = [
"""中国对外贸易形势报告75页。前 10 个月,一般贸易进出口 19.5 万亿元,增长 25.1% 比整体进出口增速高出 2.9 个百分点,占进出口总额的 61.7%,较去年同期提升 1.6 个百分点。其中,一般贸易出口 10.6 万亿元,增长 25.3%,占出口总额的 60.9%,提升 1.5 个百分点进口8.9万亿元增长24.9%占进口总额的62.7% 提升 1.8 个百分点。加工贸易进出口 6.8 万亿元,增长 11.8% 占进出口总额的 21.5%,减少 2.0 个百分点。其中,出口增 长 10.4%,占出口总额的 24.3%,减少 2.6 个百分点;进口增 长 14.2%,占进口总额的 18.0%,减少 1.2 个百分点。此外, 以保税物流方式进出口 3.96 万亿元,增长 27.9%。其中,出 口 1.47 万亿元,增长 38.9%;进口 2.49 万亿元,增长 22.2%。前三季度,中国服务贸易继续保持快速增长态势。服务 进出口总额 37834.3 亿元,增长 11.6%;其中服务出口 17820.9 亿元,增长 27.3%;进口 20013.4 亿元,增长 0.5%,进口增 速实现了疫情以来的首次转正。服务出口增幅大于进口 26.8 个百分点,带动服务贸易逆差下降 62.9%至 2192.5 亿元。服 务贸易结构持续优化,知识密集型服务进出口 16917.7 亿元, 增长 13.3%,占服务进出口总额的比重达到 44.7%,提升 0.7 个百分点。 二、中国对外贸易发展环境分析和展望 全球疫情起伏反复,经济复苏分化加剧,大宗商品价格 上涨、能源紧缺、运力紧张及发达经济体政策调整外溢等风 险交织叠加。同时也要看到,我国经济长期向好的趋势没有 改变,外贸企业韧性和活力不断增强,新业态新模式加快发 展,创新转型步伐提速。产业链供应链面临挑战。美欧等加快出台制造业回迁计 划,加速产业链供应链本土布局,跨国公司调整产业链供应 链,全球双链面临新一轮重构,区域化、近岸化、本土化、 短链化趋势凸显。疫苗供应不足,制造业“缺芯”、物流受限、 运价高企,全球产业链供应链面临压力。 全球通胀持续高位运行。能源价格上涨加大主要经济体 的通胀压力,增加全球经济复苏的不确定性。世界银行今年 10 月发布《大宗商品市场展望》指出,能源价格在 2021 年 大涨逾 80%,并且仍将在 2022 年小幅上涨。IMF 指出,全 球通胀上行风险加剧,通胀前景存在巨大不确定性。""",
]
# text = """"""
for inum, text in enumerate(ls):
print(inum)
chunks = text_splitter.split_text(text)
for chunk in chunks:
print(chunk)