2024-01-13 18:04:09 +08:00

695 lines
23 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

import os, shutil
import re
import numpy as np
PRESERVE = 0
TRANSFORM = 1
pj = os.path.join
class LinkedListNode:
"""
Linked List Node
"""
def __init__(self, string, preserve=True) -> None:
self.string = string
self.preserve = preserve
self.next = None
self.range = None
# self.begin_line = 0
# self.begin_char = 0
def convert_to_linklist(text, mask):
root = LinkedListNode("", preserve=True)
current_node = root
for c, m, i in zip(text, mask, range(len(text))):
if (m == PRESERVE and current_node.preserve) or (
m == TRANSFORM and not current_node.preserve
):
# add
current_node.string += c
else:
current_node.next = LinkedListNode(c, preserve=(m == PRESERVE))
current_node = current_node.next
return root
def post_process(root):
# 修复括号
node = root
while True:
string = node.string
if node.preserve:
node = node.next
if node is None:
break
continue
def break_check(string):
str_stack = [""] # (lv, index)
for i, c in enumerate(string):
if c == "{":
str_stack.append("{")
elif c == "}":
if len(str_stack) == 1:
print("stack fix")
return i
str_stack.pop(-1)
else:
str_stack[-1] += c
return -1
bp = break_check(string)
if bp == -1:
pass
elif bp == 0:
node.string = string[:1]
q = LinkedListNode(string[1:], False)
q.next = node.next
node.next = q
else:
node.string = string[:bp]
q = LinkedListNode(string[bp:], False)
q.next = node.next
node.next = q
node = node.next
if node is None:
break
# 屏蔽空行和太短的句子
node = root
while True:
if len(node.string.strip("\n").strip("")) == 0:
node.preserve = True
if len(node.string.strip("\n").strip("")) < 42:
node.preserve = True
node = node.next
if node is None:
break
node = root
while True:
if node.next and node.preserve and node.next.preserve:
node.string += node.next.string
node.next = node.next.next
node = node.next
if node is None:
break
# 将前后断行符脱离
node = root
prev_node = None
while True:
if not node.preserve:
lstriped_ = node.string.lstrip().lstrip("\n")
if (
(prev_node is not None)
and (prev_node.preserve)
and (len(lstriped_) != len(node.string))
):
prev_node.string += node.string[: -len(lstriped_)]
node.string = lstriped_
rstriped_ = node.string.rstrip().rstrip("\n")
if (
(node.next is not None)
and (node.next.preserve)
and (len(rstriped_) != len(node.string))
):
node.next.string = node.string[len(rstriped_) :] + node.next.string
node.string = rstriped_
# =-=-=
prev_node = node
node = node.next
if node is None:
break
# 标注节点的行数范围
node = root
n_line = 0
expansion = 2
while True:
n_l = node.string.count("\n")
node.range = [n_line - expansion, n_line + n_l + expansion] # 失败时,扭转的范围
n_line = n_line + n_l
node = node.next
if node is None:
break
return root
"""
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Latex segmentation with a binary mask (PRESERVE=0, TRANSFORM=1)
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
"""
def set_forbidden_text(text, mask, pattern, flags=0):
"""
Add a preserve text area in this paper
e.g. with pattern = r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}"
you can mask out (mask = PRESERVE so that text become untouchable for GPT)
everything between "\begin{equation}" and "\end{equation}"
"""
if isinstance(pattern, list):
pattern = "|".join(pattern)
pattern_compile = re.compile(pattern, flags)
for res in pattern_compile.finditer(text):
mask[res.span()[0] : res.span()[1]] = PRESERVE
return text, mask
def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
"""
Move area out of preserve area (make text editable for GPT)
count the number of the braces so as to catch compelete text area.
e.g.
\begin{abstract} blablablablablabla. \end{abstract}
"""
if isinstance(pattern, list):
pattern = "|".join(pattern)
pattern_compile = re.compile(pattern, flags)
for res in pattern_compile.finditer(text):
if not forbid_wrapper:
mask[res.span()[0] : res.span()[1]] = TRANSFORM
else:
mask[res.regs[0][0] : res.regs[1][0]] = PRESERVE # '\\begin{abstract}'
mask[res.regs[1][0] : res.regs[1][1]] = TRANSFORM # abstract
mask[res.regs[1][1] : res.regs[0][1]] = PRESERVE # abstract
return text, mask
def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
"""
Add a preserve text area in this paper (text become untouchable for GPT).
count the number of the braces so as to catch compelete text area.
e.g.
\caption{blablablablabla\texbf{blablabla}blablabla.}
"""
pattern_compile = re.compile(pattern, flags)
for res in pattern_compile.finditer(text):
brace_level = -1
p = begin = end = res.regs[0][0]
for _ in range(1024 * 16):
if text[p] == "}" and brace_level == 0:
break
elif text[p] == "}":
brace_level -= 1
elif text[p] == "{":
brace_level += 1
p += 1
end = p + 1
mask[begin:end] = PRESERVE
return text, mask
def reverse_forbidden_text_careful_brace(
text, mask, pattern, flags=0, forbid_wrapper=True
):
"""
Move area out of preserve area (make text editable for GPT)
count the number of the braces so as to catch compelete text area.
e.g.
\caption{blablablablabla\texbf{blablabla}blablabla.}
"""
pattern_compile = re.compile(pattern, flags)
for res in pattern_compile.finditer(text):
brace_level = 0
p = begin = end = res.regs[1][0]
for _ in range(1024 * 16):
if text[p] == "}" and brace_level == 0:
break
elif text[p] == "}":
brace_level -= 1
elif text[p] == "{":
brace_level += 1
p += 1
end = p
mask[begin:end] = TRANSFORM
if forbid_wrapper:
mask[res.regs[0][0] : begin] = PRESERVE
mask[end : res.regs[0][1]] = PRESERVE
return text, mask
def set_forbidden_text_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
"""
Find all \begin{} ... \end{} text block that with less than limit_n_lines lines.
Add it to preserve area
"""
pattern_compile = re.compile(pattern, flags)
def search_with_line_limit(text, mask):
for res in pattern_compile.finditer(text):
cmd = res.group(1) # begin{what}
this = res.group(2) # content between begin and end
this_mask = mask[res.regs[2][0] : res.regs[2][1]]
white_list = [
"document",
"abstract",
"lemma",
"definition",
"sproof",
"em",
"emph",
"textit",
"textbf",
"itemize",
"enumerate",
]
if (cmd in white_list) or this.count(
"\n"
) >= limit_n_lines: # use a magical number 42
this, this_mask = search_with_line_limit(this, this_mask)
mask[res.regs[2][0] : res.regs[2][1]] = this_mask
else:
mask[res.regs[0][0] : res.regs[0][1]] = PRESERVE
return text, mask
return search_with_line_limit(text, mask)
"""
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Latex Merge File
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
"""
def find_main_tex_file(file_manifest, mode):
"""
在多Tex文档中寻找主文件必须包含documentclass返回找到的第一个。
P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
"""
canidates = []
for texf in file_manifest:
if os.path.basename(texf).startswith("merge"):
continue
with open(texf, "r", encoding="utf8", errors="ignore") as f:
file_content = f.read()
if r"\documentclass" in file_content:
canidates.append(texf)
else:
continue
if len(canidates) == 0:
raise RuntimeError("无法找到一个主Tex文件包含documentclass关键字")
elif len(canidates) == 1:
return canidates[0]
else: # if len(canidates) >= 2 通过一些Latex模板中常见但通常不会出现在正文的单词对不同latex源文件扣分取评分最高者返回
canidates_score = []
# 给出一些判定模板文档的词作为扣分项
unexpected_words = [
"\\LaTeX",
"manuscript",
"Guidelines",
"font",
"citations",
"rejected",
"blind review",
"reviewers",
]
expected_words = ["\\input", "\\ref", "\\cite"]
for texf in canidates:
canidates_score.append(0)
with open(texf, "r", encoding="utf8", errors="ignore") as f:
file_content = f.read()
file_content = rm_comments(file_content)
for uw in unexpected_words:
if uw in file_content:
canidates_score[-1] -= 1
for uw in expected_words:
if uw in file_content:
canidates_score[-1] += 1
select = np.argmax(canidates_score) # 取评分最高者返回
return canidates[select]
def rm_comments(main_file):
new_file_remove_comment_lines = []
for l in main_file.splitlines():
# 删除整行的空注释
if l.lstrip().startswith("%"):
pass
else:
new_file_remove_comment_lines.append(l)
main_file = "\n".join(new_file_remove_comment_lines)
# main_file = re.sub(r"\\include{(.*?)}", r"\\input{\1}", main_file) # 将 \include 命令转换为 \input 命令
main_file = re.sub(r"(?<!\\)%.*", "", main_file) # 使用正则表达式查找半行注释, 并替换为空字符串
return main_file
def find_tex_file_ignore_case(fp):
dir_name = os.path.dirname(fp)
base_name = os.path.basename(fp)
# 如果输入的文件路径是正确的
if os.path.isfile(pj(dir_name, base_name)):
return pj(dir_name, base_name)
# 如果不正确,试着加上.tex后缀试试
if not base_name.endswith(".tex"):
base_name += ".tex"
if os.path.isfile(pj(dir_name, base_name)):
return pj(dir_name, base_name)
# 如果还找不到,解除大小写限制,再试一次
import glob
for f in glob.glob(dir_name + "/*.tex"):
base_name_s = os.path.basename(fp)
base_name_f = os.path.basename(f)
if base_name_s.lower() == base_name_f.lower():
return f
# 试着加上.tex后缀试试
if not base_name_s.endswith(".tex"):
base_name_s += ".tex"
if base_name_s.lower() == base_name_f.lower():
return f
return None
def merge_tex_files_(project_foler, main_file, mode):
"""
Merge Tex project recrusively
"""
main_file = rm_comments(main_file)
for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
f = s.group(1)
fp = os.path.join(project_foler, f)
fp_ = find_tex_file_ignore_case(fp)
if fp_:
try:
with open(fp_, "r", encoding="utf-8", errors="replace") as fx:
c = fx.read()
except:
c = f"\n\nWarning from GPT-Academic: LaTex source file is missing!\n\n"
else:
raise RuntimeError(f"找不到{fp}Tex源文件缺失")
c = merge_tex_files_(project_foler, c, mode)
main_file = main_file[: s.span()[0]] + c + main_file[s.span()[1] :]
return main_file
def find_title_and_abs(main_file):
def extract_abstract_1(text):
pattern = r"\\abstract\{(.*?)\}"
match = re.search(pattern, text, re.DOTALL)
if match:
return match.group(1)
else:
return None
def extract_abstract_2(text):
pattern = r"\\begin\{abstract\}(.*?)\\end\{abstract\}"
match = re.search(pattern, text, re.DOTALL)
if match:
return match.group(1)
else:
return None
def extract_title(string):
pattern = r"\\title\{(.*?)\}"
match = re.search(pattern, string, re.DOTALL)
if match:
return match.group(1)
else:
return None
abstract = extract_abstract_1(main_file)
if abstract is None:
abstract = extract_abstract_2(main_file)
title = extract_title(main_file)
return title, abstract
def merge_tex_files(project_foler, main_file, mode):
"""
Merge Tex project recrusively
P.S. 顺便把CTEX塞进去以支持中文
P.S. 顺便把Latex的注释去除
"""
main_file = merge_tex_files_(project_foler, main_file, mode)
main_file = rm_comments(main_file)
if mode == "translate_zh":
# find paper documentclass
pattern = re.compile(r"\\documentclass.*\n")
match = pattern.search(main_file)
assert match is not None, "Cannot find documentclass statement!"
position = match.end()
add_ctex = "\\usepackage{ctex}\n"
add_url = "\\usepackage{url}\n" if "{url}" not in main_file else ""
main_file = main_file[:position] + add_ctex + add_url + main_file[position:]
# fontset=windows
import platform
main_file = re.sub(
r"\\documentclass\[(.*?)\]{(.*?)}",
r"\\documentclass[\1,fontset=windows,UTF8]{\2}",
main_file,
)
main_file = re.sub(
r"\\documentclass{(.*?)}",
r"\\documentclass[fontset=windows,UTF8]{\1}",
main_file,
)
# find paper abstract
pattern_opt1 = re.compile(r"\\begin\{abstract\}.*\n")
pattern_opt2 = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
match_opt1 = pattern_opt1.search(main_file)
match_opt2 = pattern_opt2.search(main_file)
if (match_opt1 is None) and (match_opt2 is None):
# "Cannot find paper abstract section!"
main_file = insert_abstract(main_file)
match_opt1 = pattern_opt1.search(main_file)
match_opt2 = pattern_opt2.search(main_file)
assert (match_opt1 is not None) or (
match_opt2 is not None
), "Cannot find paper abstract section!"
return main_file
insert_missing_abs_str = r"""
\begin{abstract}
The GPT-Academic program cannot find abstract section in this paper.
\end{abstract}
"""
def insert_abstract(tex_content):
if "\\maketitle" in tex_content:
# find the position of "\maketitle"
find_index = tex_content.index("\\maketitle")
# find the nearest ending line
end_line_index = tex_content.find("\n", find_index)
# insert "abs_str" on the next line
modified_tex = (
tex_content[: end_line_index + 1]
+ "\n\n"
+ insert_missing_abs_str
+ "\n\n"
+ tex_content[end_line_index + 1 :]
)
return modified_tex
elif r"\begin{document}" in tex_content:
# find the position of "\maketitle"
find_index = tex_content.index(r"\begin{document}")
# find the nearest ending line
end_line_index = tex_content.find("\n", find_index)
# insert "abs_str" on the next line
modified_tex = (
tex_content[: end_line_index + 1]
+ "\n\n"
+ insert_missing_abs_str
+ "\n\n"
+ tex_content[end_line_index + 1 :]
)
return modified_tex
else:
return tex_content
"""
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Post process
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
"""
def mod_inbraket(match):
"""
为啥chatgpt会把cite里面的逗号换成中文逗号呀
"""
# get the matched string
cmd = match.group(1)
str_to_modify = match.group(2)
# modify the matched string
str_to_modify = str_to_modify.replace("", ":") # 前面是中文冒号,后面是英文冒号
str_to_modify = str_to_modify.replace("", ",") # 前面是中文逗号,后面是英文逗号
# str_to_modify = 'BOOM'
return "\\" + cmd + "{" + str_to_modify + "}"
def fix_content(final_tex, node_string):
"""
Fix common GPT errors to increase success rate
"""
final_tex = re.sub(r"(?<!\\)%", "\\%", final_tex)
final_tex = re.sub(r"\\([a-z]{2,10})\ \{", r"\\\1{", string=final_tex)
final_tex = re.sub(r"\\\ ([a-z]{2,10})\{", r"\\\1{", string=final_tex)
final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)
if "Traceback" in final_tex and "[Local Message]" in final_tex:
final_tex = node_string # 出问题了,还原原文
if node_string.count("\\begin") != final_tex.count("\\begin"):
final_tex = node_string # 出问题了,还原原文
if node_string.count("\_") > 0 and node_string.count("\_") > final_tex.count("\_"):
# walk and replace any _ without \
final_tex = re.sub(r"(?<!\\)_", "\\_", final_tex)
def compute_brace_level(string):
# this function count the number of { and }
brace_level = 0
for c in string:
if c == "{":
brace_level += 1
elif c == "}":
brace_level -= 1
return brace_level
def join_most(tex_t, tex_o):
# this function join translated string and original string when something goes wrong
p_t = 0
p_o = 0
def find_next(string, chars, begin):
p = begin
while p < len(string):
if string[p] in chars:
return p, string[p]
p += 1
return None, None
while True:
res1, char = find_next(tex_o, ["{", "}"], p_o)
if res1 is None:
break
res2, char = find_next(tex_t, [char], p_t)
if res2 is None:
break
p_o = res1 + 1
p_t = res2 + 1
return tex_t[:p_t] + tex_o[p_o:]
if compute_brace_level(final_tex) != compute_brace_level(node_string):
# 出问题了,还原部分原文,保证括号正确
final_tex = join_most(final_tex, node_string)
return final_tex
def compile_latex_with_timeout(command, cwd, timeout=60):
import subprocess
process = subprocess.Popen(
command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd
)
try:
stdout, stderr = process.communicate(timeout=timeout)
except subprocess.TimeoutExpired:
process.kill()
stdout, stderr = process.communicate()
print("Process timed out!")
return False
return True
def run_in_subprocess_wrapper_func(func, args, kwargs, return_dict, exception_dict):
import sys
try:
result = func(*args, **kwargs)
return_dict["result"] = result
except Exception as e:
exc_info = sys.exc_info()
exception_dict["exception"] = exc_info
def run_in_subprocess(func):
import multiprocessing
def wrapper(*args, **kwargs):
return_dict = multiprocessing.Manager().dict()
exception_dict = multiprocessing.Manager().dict()
process = multiprocessing.Process(
target=run_in_subprocess_wrapper_func,
args=(func, args, kwargs, return_dict, exception_dict),
)
process.start()
process.join()
process.close()
if "exception" in exception_dict:
# ooops, the subprocess ran into an exception
exc_info = exception_dict["exception"]
raise exc_info[1].with_traceback(exc_info[2])
if "result" in return_dict.keys():
# If the subprocess ran successfully, return the result
return return_dict["result"]
return wrapper
def _merge_pdfs(pdf1_path, pdf2_path, output_path):
import PyPDF2 # PyPDF2这个库有严重的内存泄露问题把它放到子进程中运行从而方便内存的释放
Percent = 0.95
# raise RuntimeError('PyPDF2 has a serious memory leak problem, please use other tools to merge PDF files.')
# Open the first PDF file
with open(pdf1_path, "rb") as pdf1_file:
pdf1_reader = PyPDF2.PdfFileReader(pdf1_file)
# Open the second PDF file
with open(pdf2_path, "rb") as pdf2_file:
pdf2_reader = PyPDF2.PdfFileReader(pdf2_file)
# Create a new PDF file to store the merged pages
output_writer = PyPDF2.PdfFileWriter()
# Determine the number of pages in each PDF file
num_pages = max(pdf1_reader.numPages, pdf2_reader.numPages)
# Merge the pages from the two PDF files
for page_num in range(num_pages):
# Add the page from the first PDF file
if page_num < pdf1_reader.numPages:
page1 = pdf1_reader.getPage(page_num)
else:
page1 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
# Add the page from the second PDF file
if page_num < pdf2_reader.numPages:
page2 = pdf2_reader.getPage(page_num)
else:
page2 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
# Create a new empty page with double width
new_page = PyPDF2.PageObject.createBlankPage(
width=int(
int(page1.mediaBox.getWidth())
+ int(page2.mediaBox.getWidth()) * Percent
),
height=max(page1.mediaBox.getHeight(), page2.mediaBox.getHeight()),
)
new_page.mergeTranslatedPage(page1, 0, 0)
new_page.mergeTranslatedPage(
page2,
int(
int(page1.mediaBox.getWidth())
- int(page2.mediaBox.getWidth()) * (1 - Percent)
),
0,
)
output_writer.addPage(new_page)
# Save the merged PDF file
with open(output_path, "wb") as output_file:
output_writer.write(output_file)
merge_pdfs = run_in_subprocess(_merge_pdfs) # PyPDF2这个库有严重的内存泄露问题把它放到子进程中运行从而方便内存的释放