gpt-academic / crazy_functions /Latex输出PDF结果.py
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from toolbox import update_ui, trimmed_format_exc, get_conf, objdump, objload, promote_file_to_downloadzone
from toolbox import CatchException, report_execption, update_ui_lastest_msg, zip_result, gen_time_str
from functools import partial
import glob, os, requests, time
pj = os.path.join
ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
# =================================== 工具函数 ===============================================
专业词汇声明 = 'If the term "agent" is used in this section, it should be translated to "智能体". '
def switch_prompt(pfg, mode, more_requirement):
"""
Generate prompts and system prompts based on the mode for proofreading or translating.
Args:
- pfg: Proofreader or Translator instance.
- mode: A string specifying the mode, either 'proofread' or 'translate_zh'.
Returns:
- inputs_array: A list of strings containing prompts for users to respond to.
- sys_prompt_array: A list of strings containing prompts for system prompts.
"""
n_split = len(pfg.sp_file_contents)
if mode == 'proofread_en':
inputs_array = [r"Below is a section from an academic paper, proofread this section." +
r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " + more_requirement +
r"Answer me only with the revised text:" +
f"\n\n{frag}" for frag in pfg.sp_file_contents]
sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
elif mode == 'translate_zh':
inputs_array = [r"Below is a section from an English academic paper, translate it into Chinese. " + more_requirement +
r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " +
r"Answer me only with the translated text:" +
f"\n\n{frag}" for frag in pfg.sp_file_contents]
sys_prompt_array = ["You are a professional translator." for _ in range(n_split)]
else:
assert False, "未知指令"
return inputs_array, sys_prompt_array
def desend_to_extracted_folder_if_exist(project_folder):
"""
Descend into the extracted folder if it exists, otherwise return the original folder.
Args:
- project_folder: A string specifying the folder path.
Returns:
- A string specifying the path to the extracted folder, or the original folder if there is no extracted folder.
"""
maybe_dir = [f for f in glob.glob(f'{project_folder}/*') if os.path.isdir(f)]
if len(maybe_dir) == 0: return project_folder
if maybe_dir[0].endswith('.extract'): return maybe_dir[0]
return project_folder
def move_project(project_folder, arxiv_id=None):
"""
Create a new work folder and copy the project folder to it.
Args:
- project_folder: A string specifying the folder path of the project.
Returns:
- A string specifying the path to the new work folder.
"""
import shutil, time
time.sleep(2) # avoid time string conflict
if arxiv_id is not None:
new_workfolder = pj(ARXIV_CACHE_DIR, arxiv_id, 'workfolder')
else:
new_workfolder = f'gpt_log/{gen_time_str()}'
try:
shutil.rmtree(new_workfolder)
except:
pass
# align subfolder if there is a folder wrapper
items = glob.glob(pj(project_folder,'*'))
if len(glob.glob(pj(project_folder,'*.tex'))) == 0 and len(items) == 1:
if os.path.isdir(items[0]): project_folder = items[0]
shutil.copytree(src=project_folder, dst=new_workfolder)
return new_workfolder
def arxiv_download(chatbot, history, txt):
def check_cached_translation_pdf(arxiv_id):
translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'translation')
if not os.path.exists(translation_dir):
os.makedirs(translation_dir)
target_file = pj(translation_dir, 'translate_zh.pdf')
if os.path.exists(target_file):
promote_file_to_downloadzone(target_file, rename_file=None, chatbot=chatbot)
return target_file
return False
def is_float(s):
try:
float(s)
return True
except ValueError:
return False
if ('.' in txt) and ('/' not in txt) and is_float(txt): # is arxiv ID
txt = 'https://arxiv.org/abs/' + txt.strip()
if ('.' in txt) and ('/' not in txt) and is_float(txt[:10]): # is arxiv ID
txt = 'https://arxiv.org/abs/' + txt[:10]
if not txt.startswith('https://arxiv.org'):
return txt, None
# <-------------- inspect format ------------->
chatbot.append([f"检测到arxiv文档连接", '尝试下载 ...'])
yield from update_ui(chatbot=chatbot, history=history)
time.sleep(1) # 刷新界面
url_ = txt # https://arxiv.org/abs/1707.06690
if not txt.startswith('https://arxiv.org/abs/'):
msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}"
yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history) # 刷新界面
return msg, None
# <-------------- set format ------------->
arxiv_id = url_.split('/abs/')[-1]
if 'v' in arxiv_id: arxiv_id = arxiv_id[:10]
cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
if cached_translation_pdf: return cached_translation_pdf, arxiv_id
url_tar = url_.replace('/abs/', '/e-print/')
translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
extract_dst = pj(ARXIV_CACHE_DIR, arxiv_id, 'extract')
os.makedirs(translation_dir, exist_ok=True)
# <-------------- download arxiv source file ------------->
dst = pj(translation_dir, arxiv_id+'.tar')
if os.path.exists(dst):
yield from update_ui_lastest_msg("调用缓存", chatbot=chatbot, history=history) # 刷新界面
else:
yield from update_ui_lastest_msg("开始下载", chatbot=chatbot, history=history) # 刷新界面
proxies, = get_conf('proxies')
r = requests.get(url_tar, proxies=proxies)
with open(dst, 'wb+') as f:
f.write(r.content)
# <-------------- extract file ------------->
yield from update_ui_lastest_msg("下载完成", chatbot=chatbot, history=history) # 刷新界面
from toolbox import extract_archive
extract_archive(file_path=dst, dest_dir=extract_dst)
return extract_dst, arxiv_id
# ========================================= 插件主程序1 =====================================================
@CatchException
def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
# <-------------- information about this plugin ------------->
chatbot.append([ "函数插件功能?",
"对整个Latex项目进行纠错, 用latex编译为PDF对修正处做高亮。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4,其他模型转化效果未知。目前对机器学习类文献转化效果最好,其他类型文献转化效果未知。仅在Windows系统进行了测试,其他操作系统表现未知。"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# <-------------- more requirements ------------->
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
more_req = plugin_kwargs.get("advanced_arg", "")
_switch_prompt_ = partial(switch_prompt, more_requirement=more_req)
# <-------------- check deps ------------->
try:
import glob, os, time, subprocess
subprocess.Popen(['pdflatex', '-version'])
from .latex_fns.latex_actions import Latex精细分解与转化, 编译Latex
except Exception as e:
chatbot.append([ f"解析项目: {txt}",
f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。安装方法https://tug.org/texlive/。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# <-------------- clear history and read input ------------->
history = []
if os.path.exists(txt):
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# <-------------- if is a zip/tar file ------------->
project_folder = desend_to_extracted_folder_if_exist(project_folder)
# <-------------- move latex project away from temp folder ------------->
project_folder = move_project(project_folder, arxiv_id=None)
# <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
if not os.path.exists(project_folder + '/merge_proofread_en.tex'):
yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
chatbot, history, system_prompt, mode='proofread_en', switch_prompt=_switch_prompt_)
# <-------------- compile PDF ------------->
success = yield from 编译Latex(chatbot, history, main_file_original='merge', main_file_modified='merge_proofread_en',
work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)
# <-------------- zip PDF ------------->
zip_res = zip_result(project_folder)
if success:
chatbot.append((f"成功啦", '请查收结果(压缩包)...'))
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
else:
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果(压缩包), 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
# <-------------- we are done ------------->
return success
# ========================================= 插件主程序2 =====================================================
@CatchException
def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
# <-------------- information about this plugin ------------->
chatbot.append([
"函数插件功能?",
"对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 此插件Windows支持最佳,Linux下必须使用Docker安装,详见项目主README.md。目前仅支持GPT3.5/GPT4,其他模型转化效果未知。目前对机器学习类文献转化效果最好,其他类型文献转化效果未知。"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# <-------------- more requirements ------------->
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
more_req = plugin_kwargs.get("advanced_arg", "")
_switch_prompt_ = partial(switch_prompt, more_requirement=more_req)
# <-------------- check deps ------------->
try:
import glob, os, time, subprocess
subprocess.Popen(['pdflatex', '-version'])
from .latex_fns.latex_actions import Latex精细分解与转化, 编译Latex
except Exception as e:
chatbot.append([ f"解析项目: {txt}",
f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。安装方法https://tug.org/texlive/。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# <-------------- clear history and read input ------------->
history = []
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt)
if txt.endswith('.pdf'):
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"发现已经存在翻译好的PDF文档")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
if os.path.exists(txt):
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# <-------------- if is a zip/tar file ------------->
project_folder = desend_to_extracted_folder_if_exist(project_folder)
# <-------------- move latex project away from temp folder ------------->
project_folder = move_project(project_folder, arxiv_id)
# <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
if not os.path.exists(project_folder + '/merge_translate_zh.tex'):
yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
chatbot, history, system_prompt, mode='translate_zh', switch_prompt=_switch_prompt_)
# <-------------- compile PDF ------------->
success = yield from 编译Latex(chatbot, history, main_file_original='merge', main_file_modified='merge_translate_zh', mode='translate_zh',
work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)
# <-------------- zip PDF ------------->
zip_res = zip_result(project_folder)
if success:
chatbot.append((f"成功啦", '请查收结果(压缩包)...'))
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
else:
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果(压缩包), 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
# <-------------- we are done ------------->
return success