105 lines
6.2 KiB
Python
105 lines
6.2 KiB
Python
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import re
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from typing import List, Optional, Any
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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import logging
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logger = logging.getLogger(__name__)
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def _split_text_with_regex_from_end(
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text: str, separator: str, keep_separator: bool
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) -> List[str]:
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# Now that we have the separator, split the text
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if separator:
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if keep_separator:
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# The parentheses in the pattern keep the delimiters in the result.
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_splits = re.split(f"({separator})", text)
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splits = ["".join(i) for i in zip(_splits[0::2], _splits[1::2])]
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if len(_splits) % 2 == 1:
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splits += _splits[-1:]
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# splits = [_splits[0]] + splits
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else:
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splits = re.split(separator, text)
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else:
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splits = list(text)
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return [s for s in splits if s != ""]
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class ChineseRecursiveTextSplitter(RecursiveCharacterTextSplitter):
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def __init__(
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self,
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separators: Optional[List[str]] = None,
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keep_separator: bool = True,
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is_separator_regex: bool = True,
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**kwargs: Any,
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) -> None:
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"""Create a new TextSplitter."""
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super().__init__(keep_separator=keep_separator, **kwargs)
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self._separators = separators or [
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"\n\n",
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"\n",
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"。|！|？",
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"\.\s|\!\s|\?\s",
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"；|;\s",
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"，|,\s"
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]
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self._is_separator_regex = is_separator_regex
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def _split_text(self, text: str, separators: List[str]) -> List[str]:
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"""Split incoming text and return chunks."""
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final_chunks = []
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# Get appropriate separator to use
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separator = separators[-1]
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new_separators = []
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for i, _s in enumerate(separators):
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_separator = _s if self._is_separator_regex else re.escape(_s)
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if _s == "":
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separator = _s
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break
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if re.search(_separator, text):
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separator = _s
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new_separators = separators[i + 1:]
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break
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_separator = separator if self._is_separator_regex else re.escape(separator)
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splits = _split_text_with_regex_from_end(text, _separator, self._keep_separator)
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# Now go merging things, recursively splitting longer texts.
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_good_splits = []
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_separator = "" if self._keep_separator else separator
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for s in splits:
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if self._length_function(s) < self._chunk_size:
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_good_splits.append(s)
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else:
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if _good_splits:
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merged_text = self._merge_splits(_good_splits, _separator)
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final_chunks.extend(merged_text)
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_good_splits = []
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if not new_separators:
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final_chunks.append(s)
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else:
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other_info = self._split_text(s, new_separators)
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final_chunks.extend(other_info)
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if _good_splits:
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merged_text = self._merge_splits(_good_splits, _separator)
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final_chunks.extend(merged_text)
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return [re.sub(r"\n{2,}", "\n", chunk.strip()) for chunk in final_chunks if chunk.strip()!=""]
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if __name__ == "__main__":
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text_splitter = ChineseRecursiveTextSplitter(
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keep_separator=True,
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is_separator_regex=True,
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chunk_size=50,
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chunk_overlap=0
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)
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ls = [
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"""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。""",
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]
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# text = """"""
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for inum, text in enumerate(ls):
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print(inum)
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chunks = text_splitter.split_text(text)
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for chunk in chunks:
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print(chunk)
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