镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 22:46:48 +00:00
改善chatpdf的功能
这个提交包含在:
@@ -360,3 +360,171 @@ def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
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# 这个中文的句号是故意的,作为一个标识而存在
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res = cut(txt.replace('.', '。\n'), must_break_at_empty_line=False)
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return [r.replace('。\n', '.') for r in res]
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def read_and_clean_pdf_text(fp):
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"""
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这个函数用于分割pdf,用了很多trick,逻辑较乱,效果奇好
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**输入参数说明**
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- `fp`:需要读取和清理文本的pdf文件路径
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**输出参数说明**
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- `meta_txt`:清理后的文本内容字符串
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- `page_one_meta`:第一页清理后的文本内容列表
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**函数功能**
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读取pdf文件并清理其中的文本内容,清理规则包括:
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- 提取所有块元的文本信息,并合并为一个字符串
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- 去除短块(字符数小于100)并替换为回车符
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- 清理多余的空行
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- 合并小写字母开头的段落块并替换为空格
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- 清除重复的换行
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- 将每个换行符替换为两个换行符,使每个段落之间有两个换行符分隔
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"""
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import fitz, copy
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import re
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import numpy as np
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from colorful import print亮黄, print亮绿
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fc = 0
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fs = 1
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fb = 2
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REMOVE_FOOT_NOTE = True
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REMOVE_FOOT_FFSIZE_PERCENT = 0.95
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def primary_ffsize(l):
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fsize_statiscs = {}
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for wtf in l['spans']:
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if wtf['size'] not in fsize_statiscs: fsize_statiscs[wtf['size']] = 0
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fsize_statiscs[wtf['size']] += len(wtf['text'])
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return max(fsize_statiscs, key=fsize_statiscs.get)
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def ffsize_same(a,b):
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return abs((a-b)/max(a,b)) < 0.02
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# file_content = ""
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with fitz.open(fp) as doc:
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meta_txt = []
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meta_font = []
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meta_line = []
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meta_span = []
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for index, page in enumerate(doc):
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# file_content += page.get_text()
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text_areas = page.get_text("dict") # 获取页面上的文本信息
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for t in text_areas['blocks']:
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if 'lines' in t:
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pf = 998
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for l in t['lines']:
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txt_line = "".join([wtf['text'] for wtf in l['spans']])
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pf = primary_ffsize(l)
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meta_line.append([txt_line, pf, l['bbox'], l])
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for wtf in l['spans']: # for l in t['lines']:
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meta_span.append([wtf['text'], wtf['size'], len(wtf['text'])])
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# meta_line.append(["NEW_BLOCK", pf])
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# 块元提取 for each word segment with in line for each line cross-line words for each block
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meta_txt.extend([" ".join(["".join([wtf['text'] for wtf in l['spans']]) for l in t['lines']]).replace(
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'- ', '') for t in text_areas['blocks'] if 'lines' in t])
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meta_font.extend([np.mean([np.mean([wtf['size'] for wtf in l['spans']])
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for l in t['lines']]) for t in text_areas['blocks'] if 'lines' in t])
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if index == 0:
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page_one_meta = [" ".join(["".join([wtf['text'] for wtf in l['spans']]) for l in t['lines']]).replace(
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'- ', '') for t in text_areas['blocks'] if 'lines' in t]
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# 获取正文主字体
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fsize_statiscs = {}
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for span in meta_span:
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if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
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fsize_statiscs[span[1]] += span[2]
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main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
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if REMOVE_FOOT_NOTE:
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give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
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# 切分和重新整合
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mega_sec = []
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sec = []
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for index, line in enumerate(meta_line):
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if index == 0:
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sec.append(line[fc])
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continue
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if REMOVE_FOOT_NOTE:
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if meta_line[index][fs] <= give_up_fize_threshold:
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continue
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if ffsize_same(meta_line[index][fs], meta_line[index-1][fs]):
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# 尝试识别段落
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if meta_line[index][fc].endswith('.') and\
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(meta_line[index-1][fc] != 'NEW_BLOCK') and \
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(meta_line[index][fb][2] - meta_line[index][fb][0]) < (meta_line[index-1][fb][2] - meta_line[index-1][fb][0]) * 0.7:
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sec[-1] += line[fc]
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sec[-1] += "\n\n"
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else:
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sec[-1] += " "
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sec[-1] += line[fc]
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else:
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if (index+1 < len(meta_line)) and \
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meta_line[index][fs] > main_fsize:
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# 单行 + 字体大
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mega_sec.append(copy.deepcopy(sec))
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sec = []
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sec.append("# " + line[fc])
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else:
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# 尝试识别section
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if meta_line[index-1][fs] > meta_line[index][fs]:
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sec.append("\n" + line[fc])
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else:
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sec.append(line[fc])
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mega_sec.append(copy.deepcopy(sec))
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finals = []
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for ms in mega_sec:
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final = " ".join(ms)
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final = final.replace('- ', ' ')
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finals.append(final)
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meta_txt = finals
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def 把字符太少的块清除为回车(meta_txt):
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for index, block_txt in enumerate(meta_txt):
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if len(block_txt) < 100:
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meta_txt[index] = '\n'
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return meta_txt
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meta_txt = 把字符太少的块清除为回车(meta_txt)
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def 清理多余的空行(meta_txt):
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for index in reversed(range(1, len(meta_txt))):
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if meta_txt[index] == '\n' and meta_txt[index-1] == '\n':
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meta_txt.pop(index)
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return meta_txt
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meta_txt = 清理多余的空行(meta_txt)
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def 合并小写开头的段落块(meta_txt):
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def starts_with_lowercase_word(s):
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pattern = r"^[a-z]+"
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match = re.match(pattern, s)
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if match:
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return True
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else:
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return False
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for _ in range(100):
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for index, block_txt in enumerate(meta_txt):
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if starts_with_lowercase_word(block_txt):
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if meta_txt[index-1] != '\n':
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meta_txt[index-1] += ' '
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else:
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meta_txt[index-1] = ''
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meta_txt[index-1] += meta_txt[index]
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meta_txt[index] = '\n'
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return meta_txt
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meta_txt = 合并小写开头的段落块(meta_txt)
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meta_txt = 清理多余的空行(meta_txt)
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meta_txt = '\n'.join(meta_txt)
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# 清除重复的换行
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for _ in range(5):
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meta_txt = meta_txt.replace('\n\n', '\n')
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# 换行 -> 双换行
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meta_txt = meta_txt.replace('\n', '\n\n')
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for f in finals:
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print亮黄(f)
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print亮绿('***************************')
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return meta_txt, page_one_meta
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