镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-08 23:46:48 +00:00
218 行
8.2 KiB
Python
218 行
8.2 KiB
Python
from toolbox import update_ui, trimmed_format_exc
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from toolbox import CatchException, report_execption, write_results_to_file, zip_folder
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import os
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import re
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def 寻找Latex主文件(file_manifest, mode):
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for texf in file_manifest:
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if os.path.basename(texf).startswith('merge'):
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continue
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with open(texf, 'r', encoding='utf8') as f:
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file_content = f.read()
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if r'\documentclass' in file_content:
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return texf
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else:
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continue
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raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')
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def merge_tex_files_(project_foler, main_file, mode):
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for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
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f = s.group(1)
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fp = os.path.join(project_foler, f)
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with open(fp, 'r', encoding='utf-8', errors='replace') as fx:
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c = fx.read()
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c = merge_tex_files_(project_foler, c, mode)
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main_file = main_file[:s.span()[0]] + c + main_file[s.span()[1]:]
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return main_file
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def merge_tex_files(project_foler, main_file, mode):
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main_file = merge_tex_files_(project_foler, main_file, mode)
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if mode == 'translate_zh':
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pattern = re.compile(r'\\documentclass.*\n')
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match = pattern.search(main_file)
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position = match.end()
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main_file = main_file[:position] + '\\usepackage{CTEX}\n' + main_file[position:]
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return main_file
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class LinkTable():
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def __init__(self, string, preserve=True) -> None:
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self.string = string
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self.preserve = preserve
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self.next = None
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def mod_inbraket(match):
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# get the matched string
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cmd = match.group(1)
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str_to_modify = match.group(2)
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# modify the matched string
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str_to_modify = str_to_modify.replace('：', ':')
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str_to_modify = str_to_modify.replace('，', ',')
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# str_to_modify = 'BOOM'
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# return the modified string as the replacement
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return "\\" + cmd + "{" + str_to_modify + "}"
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def fix_content(final_tex):
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"""
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fix common GPT errors to increase success rate
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"""
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final_tex = final_tex.replace('%', r'\%')
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final_tex = final_tex.replace(r'\%', r'\\%')
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final_tex = re.sub(r"\\([a-z]{2,10})\ \{", r"\\\1{", string=final_tex)
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final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)
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return final_tex
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class LatexPaperSplit():
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def __init__(self) -> None:
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self.root = None
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def merge_result(self, arr):
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result_string = ""
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node = self.root
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p = 0
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while True:
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if node.preserve:
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result_string += node.string
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else:
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result_string += fix_content(arr[p])
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p += 1
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node = node.next
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if node is None: break
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return result_string
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def split(self, txt):
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# def replace_with_hash()
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root = LinkTable(txt, False)
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def split_worker(root, pattern, flags=0):
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lt = root
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cnt = 0
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while True:
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if not lt.preserve:
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while True:
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res = re.search(pattern, lt.string, flags)
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if not res: break
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before = res.string[:res.span()[0]]
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this = res.group(0)
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# core = res.group(1)
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after = res.string[res.span()[1]:]
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# ======
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if before.endswith('\n'):
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this = '\n' + this
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before = before[:-1]
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if after.startswith('\n'):
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# move \n
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this = this + '\n'
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after = after[1:]
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# ======
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lt.string = before
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tmp = lt.next
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# ======
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mid = LinkTable(this, True)
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lt.next = mid
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# ======
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aft = LinkTable(after, False)
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mid.next = aft
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aft.next = tmp
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# ======
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lt = aft
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lt = lt.next
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cnt += 1
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print(cnt)
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if lt is None: break
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# root 是链表的头
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print('正在分解Latex源文件')
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split_worker(root, r"(.*?)\\maketitle", re.DOTALL)
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split_worker(root, r"\\section\{(.*?)\}")
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split_worker(root, r"\\subsection\{(.*?)\}")
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split_worker(root, r"\\subsubsection\{(.*?)\}")
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split_worker(root, r"\\begin\{figure\}(.*?)\\end\{figure\}", re.DOTALL)
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split_worker(root, r"\\begin\{figure\*\}(.*?)\\end\{figure\*\}", re.DOTALL)
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split_worker(root, r"\\begin\{table\}(.*?)\\end\{table\}", re.DOTALL)
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split_worker(root, r"\\begin\{table\*\}(.*?)\\end\{table\*\}", re.DOTALL)
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split_worker(root, r"\\begin\{align\*\}(.*?)\\end\{align\*\}", re.DOTALL)
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split_worker(root, r"\\begin\{align\}(.*?)\\end\{align\}", re.DOTALL)
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split_worker(root, r"\\begin\{equation\}(.*?)\\end\{equation\}", re.DOTALL)
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split_worker(root, r"\\begin\{equation\*\}(.*?)\\end\{equation\*\}", re.DOTALL)
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split_worker(root, r"\$\$(.*?)\$\$", re.DOTALL)
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split_worker(root, r"\\item ")
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split_worker(root, r"\\begin\{(.*?)\}")
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split_worker(root, r"\\end\{(.*?)\}")
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res = []
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node = root
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while True:
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res.append((node.string, node.preserve))
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if len(node.string.strip('\n').strip(''))==0: node.preserve = True
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if len(node.string.strip('\n').strip(''))<50: node.preserve = True
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node = node.next
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if node is None: break
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with open('debug_log', 'w', encoding='utf8') as f:
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res_to_t = []
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node = root
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while True:
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if not node.preserve:
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res_to_t.append(node.string)
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f.write(node.string + '\n ========================= \n')
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node = node.next
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if node is None: break
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self.root = root
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self.sp = res_to_t
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return self.sp
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class LatexPaperFileGroup():
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def __init__(self):
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self.file_paths = []
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self.file_contents = []
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self.sp_file_contents = []
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self.sp_file_index = []
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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"""
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将长文本分离开来
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"""
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for index, file_content in enumerate(self.file_contents):
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if self.get_token_num(file_content) < max_token_limit:
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self.sp_file_contents.append(file_content)
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self.sp_file_index.append(index)
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self.sp_file_tag.append(self.file_paths[index])
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else:
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
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for j, segment in enumerate(segments):
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self.sp_file_contents.append(segment)
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self.sp_file_index.append(index)
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self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.tex")
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print('Segmentation: done')
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def merge_result(self):
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self.file_result = ["" for _ in range(len(self.file_paths))]
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for r, k in zip(self.sp_file_result, self.sp_file_index):
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self.file_result[k] += r
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def write_result(self):
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manifest = []
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for path, res in zip(self.file_paths, self.file_result):
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with open(path + '.polish.tex', 'w', encoding='utf8') as f:
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manifest.append(path + '.polish.tex')
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f.write(res)
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return manifest
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def zip_result(self):
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import os, time
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folder = os.path.dirname(self.file_paths[0])
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t = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
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zip_folder(folder, './gpt_log/', f'{t}-polished.zip')
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