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update:text splitter
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pilot/source_embedding/chinese_text_splitter.py
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pilot/source_embedding/chinese_text_splitter.py
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from langchain.text_splitter import CharacterTextSplitter
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import re
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from typing import List
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# from configs.model_config import SENTENCE_SIZE
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class ChineseTextSplitter(CharacterTextSplitter):
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def __init__(self, pdf: bool = False, sentence_size: int = None, **kwargs):
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super().__init__(**kwargs)
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self.pdf = pdf
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self.sentence_size = sentence_size
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def split_text1(self, text: str) -> List[str]:
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if self.pdf:
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text = re.sub(r"\n{3,}", "\n", text)
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text = re.sub('\s', ' ', text)
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text = text.replace("\n\n", "")
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sent_sep_pattern = re.compile('([﹒﹔﹖﹗.。!?]["’”」』]{0,2}|(?=["‘“「『]{1,2}|$))') # del :;
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sent_list = []
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for ele in sent_sep_pattern.split(text):
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if sent_sep_pattern.match(ele) and sent_list:
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sent_list[-1] += ele
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elif ele:
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sent_list.append(ele)
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return sent_list
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def split_text(self, text: str) -> List[str]: ##此处需要进一步优化逻辑
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if self.pdf:
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text = re.sub(r"\n{3,}", r"\n", text)
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text = re.sub('\s', " ", text)
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text = re.sub("\n\n", "", text)
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text = re.sub(r'([;;.!?。!?\?])([^”’])', r"\1\n\2", text) # 单字符断句符
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text = re.sub(r'(\.{6})([^"’”」』])', r"\1\n\2", text) # 英文省略号
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text = re.sub(r'(\…{2})([^"’”」』])', r"\1\n\2", text) # 中文省略号
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text = re.sub(r'([;;!?。!?\?]["’”」』]{0,2})([^;;!?,。!?\?])', r'\1\n\2', text)
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# 如果双引号前有终止符,那么双引号才是句子的终点,把分句符\n放到双引号后,注意前面的几句都小心保留了双引号
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text = text.rstrip() # 段尾如果有多余的\n就去掉它
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# 很多规则中会考虑分号;,但是这里我把它忽略不计,破折号、英文双引号等同样忽略,需要的再做些简单调整即可。
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ls = [i for i in text.split("\n") if i]
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for ele in ls:
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if len(ele) > self.sentence_size:
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ele1 = re.sub(r'([,,.]["’”」』]{0,2})([^,,.])', r'\1\n\2', ele)
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ele1_ls = ele1.split("\n")
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for ele_ele1 in ele1_ls:
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if len(ele_ele1) > self.sentence_size:
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ele_ele2 = re.sub(r'([\n]{1,}| {2,}["’”」』]{0,2})([^\s])', r'\1\n\2', ele_ele1)
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ele2_ls = ele_ele2.split("\n")
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for ele_ele2 in ele2_ls:
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if len(ele_ele2) > self.sentence_size:
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ele_ele3 = re.sub('( ["’”」』]{0,2})([^ ])', r'\1\n\2', ele_ele2)
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ele2_id = ele2_ls.index(ele_ele2)
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ele2_ls = ele2_ls[:ele2_id] + [i for i in ele_ele3.split("\n") if i] + ele2_ls[
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ele2_id + 1:]
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ele_id = ele1_ls.index(ele_ele1)
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ele1_ls = ele1_ls[:ele_id] + [i for i in ele2_ls if i] + ele1_ls[ele_id + 1:]
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id = ls.index(ele)
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ls = ls[:id] + [i for i in ele1_ls if i] + ls[id + 1:]
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return ls
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pilot/source_embedding/pdf_loader.py
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pilot/source_embedding/pdf_loader.py
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"""Loader that loads image files."""
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from typing import List
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from langchain.document_loaders.unstructured import UnstructuredFileLoader
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from paddleocr import PaddleOCR
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import os
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import fitz
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class UnstructuredPaddlePDFLoader(UnstructuredFileLoader):
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"""Loader that uses unstructured to load image files, such as PNGs and JPGs."""
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def _get_elements(self) -> List:
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def pdf_ocr_txt(filepath, dir_path="tmp_files"):
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full_dir_path = os.path.join(os.path.dirname(filepath), dir_path)
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if not os.path.exists(full_dir_path):
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os.makedirs(full_dir_path)
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filename = os.path.split(filepath)[-1]
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ocr = PaddleOCR(lang="ch", use_gpu=False, show_log=False)
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doc = fitz.open(filepath)
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txt_file_path = os.path.join(full_dir_path, "%s.txt" % (filename))
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img_name = os.path.join(full_dir_path, '.tmp.png')
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with open(txt_file_path, 'w', encoding='utf-8') as fout:
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for i in range(doc.page_count):
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page = doc[i]
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text = page.get_text("")
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fout.write(text)
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fout.write("\n")
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img_list = page.get_images()
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for img in img_list:
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pix = fitz.Pixmap(doc, img[0])
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pix.save(img_name)
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result = ocr.ocr(img_name)
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ocr_result = [i[1][0] for line in result for i in line]
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fout.write("\n".join(ocr_result))
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os.remove(img_name)
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return txt_file_path
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txt_file_path = pdf_ocr_txt(self.file_path)
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from unstructured.partition.text import partition_text
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return partition_text(filename=txt_file_path, **self.unstructured_kwargs)
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if __name__ == "__main__":
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filepath = os.path.join(os.path.dirname(os.path.dirname(__file__)), "content", "samples", "test.pdf")
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loader = UnstructuredPaddlePDFLoader(filepath, mode="elements")
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docs = loader.load()
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for doc in docs:
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print(doc)
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