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--bug=1052039 --user=王孝刚 【知识库】-压缩文件中包含csv、docx文件时，导入到知识库后，文档名称包含文件夹名称 https://www.tapd.cn/57709429/s/1651752
73 lines
2.5 KiB
Python
73 lines
2.5 KiB
Python
# coding=utf-8
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"""
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@project: maxkb
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@Author：虎
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@file： csv_parse_qa_handle.py
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@date：2024/5/21 14:59
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@desc:
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"""
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import csv
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import io
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import os
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from typing import List
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from charset_normalizer import detect
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from common.handle.base_split_handle import BaseSplitHandle
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def post_cell(cell_value):
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return cell_value.replace('\n', '<br>').replace('|', '|')
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def row_to_md(row):
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return '| ' + ' | '.join(
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[post_cell(cell) if cell is not None else '' for cell in row]) + ' |\n'
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class CsvSplitHandle(BaseSplitHandle):
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def handle(self, file, pattern_list: List, with_filter: bool, limit: int, get_buffer, save_image):
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buffer = get_buffer(file)
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paragraphs = []
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file_name = os.path.basename(file.name)
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result = {'name': file_name, 'content': paragraphs}
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try:
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reader = csv.reader(io.TextIOWrapper(io.BytesIO(buffer), encoding=detect(buffer)['encoding']))
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try:
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title_row_list = reader.__next__()
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title_md_content = row_to_md(title_row_list)
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title_md_content += '| ' + ' | '.join(
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['---' if cell is not None else '' for cell in title_row_list]) + ' |\n'
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except Exception as e:
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return result
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if len(title_row_list) == 0:
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return result
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result_item_content = ''
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for row in reader:
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next_md_content = row_to_md(row)
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next_md_content_len = len(next_md_content)
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result_item_content_len = len(result_item_content)
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if len(result_item_content) == 0:
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result_item_content += title_md_content
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result_item_content += next_md_content
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else:
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if result_item_content_len + next_md_content_len < limit:
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result_item_content += next_md_content
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else:
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paragraphs.append({'content': result_item_content, 'title': ''})
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result_item_content = next_md_content
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if len(result_item_content) > 0:
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paragraphs.append({'content': result_item_content, 'title': ''})
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return result
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except Exception as e:
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return result
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def get_content(self, file, save_image):
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pass
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def support(self, file, get_buffer):
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file_name: str = file.name.lower()
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if file_name.endswith(".csv"):
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return True
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return False
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