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from toolbox import update_ui, trimmed_format_exc
from toolbox import CatchException, report_execption, write_results_to_file, zip_folder
class PaperFileGroup():
def __init__(self):
self.file_paths = []
self.file_contents = []
self.sp_file_contents = []
self.sp_file_index = []
self.sp_file_tag = []
# count_token
from request_llm.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
self.get_token_num = get_token_num
def run_file_split(self, max_token_limit=1900):
"""
将长文本分离开来
"""
for index, file_content in enumerate(self.file_contents):
if self.get_token_num(file_content) < max_token_limit:
self.sp_file_contents.append(file_content)
self.sp_file_index.append(index)
self.sp_file_tag.append(self.file_paths[index])
else:
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
for j, segment in enumerate(segments):
self.sp_file_contents.append(segment)
self.sp_file_index.append(index)
self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.tex")
print('Segmentation: done')
def merge_result(self):
self.file_result = ["" for _ in range(len(self.file_paths))]
for r, k in zip(self.sp_file_result, self.sp_file_index):
self.file_result[k] += r
def write_result(self):
manifest = []
for path, res in zip(self.file_paths, self.file_result):
with open(path + '.polish.tex', 'w', encoding='utf8') as f:
manifest.append(path + '.polish.tex')
f.write(res)
return manifest
def zip_result(self):
import os, time
folder = os.path.dirname(self.file_paths[0])
t = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
zip_folder(folder, './gpt_log/', f'{t}-polished.zip')
def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en', mode='polish'):
import time, os, re
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
# <-------- 读取Latex文件,删除其中的所有注释 ---------->
pfg = PaperFileGroup()
for index, fp in enumerate(file_manifest):
with open(fp, 'r', encoding='utf-8', errors='replace') as f:
file_content = f.read()
# 定义注释的正则表达式
comment_pattern = r'%.*'
# 使用正则表达式查找注释,并替换为空字符串
clean_tex_content = re.sub(comment_pattern, '', file_content)
# 记录删除注释后的文本
pfg.file_paths.append(fp)
pfg.file_contents.append(clean_tex_content)
# <-------- 拆分过长的latex文件 ---------->
pfg.run_file_split(max_token_limit=1024)
n_split = len(pfg.sp_file_contents)
# <-------- 多线程润色开始 ---------->
if language == 'en':
if mode == 'polish':
inputs_array = ["Below is a section from an academic paper, polish this section to meet the academic standard, " +
"improve the grammar, clarity and overall readability, do not modify any latex command such as \section, \cite and equations:" +
f"\n\n{frag}" for frag in pfg.sp_file_contents]
else:
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. " +
r"Answer me only with the revised text:" +
f"\n\n{frag}" for frag in pfg.sp_file_contents]
inputs_show_user_array = [f"Polish {f}" for f in pfg.sp_file_tag]
sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
elif language == 'zh':
if mode == 'polish':
inputs_array = [f"以下是一篇学术论文中的一段内容,请将此部分润色以满足学术标准,提高语法、清晰度和整体可读性,不要修改任何LaTeX命令,例如\section,\cite和方程式:" +
f"\n\n{frag}" for frag in pfg.sp_file_contents]
else:
inputs_array = [f"以下是一篇学术论文中的一段内容,请对这部分内容进行语法矫正。不要修改任何LaTeX命令,例如\section,\cite和方程式:" +
f"\n\n{frag}" for frag in pfg.sp_file_contents]
inputs_show_user_array = [f"润色 {f}" for f in pfg.sp_file_tag]
sys_prompt_array=["你是一位专业的中文学术论文作家。" for _ in range(n_split)]
gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
inputs_array=inputs_array,
inputs_show_user_array=inputs_show_user_array,
llm_kwargs=llm_kwargs,
chatbot=chatbot,
history_array=[[""] for _ in range(n_split)],
sys_prompt_array=sys_prompt_array,
# max_workers=5, # 并行任务数量限制,最多同时执行5个,其他的排队等待
scroller_max_len = 80
)
pfg.sp_file_result = []
for i_say, gpt_say in zip(gpt_response_collection[0::2], gpt_response_collection[1::2]):
pfg.sp_file_result.append(gpt_say)
# <-------- 文本碎片重组为完整的tex文件,整理结果为压缩包 ---------->
try:
pfg.merge_result()
pfg.write_result()
pfg.zip_result()
except:
print(trimmed_format_exc())
# <-------- 整理结果,退出 ---------->
create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name)
history = gpt_response_collection
chatbot.append((f"{fp}完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@CatchException
def Latex英文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"对整个Latex项目进行润色。函数插件贡献者: Binary-Husky"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import tiktoken
except:
report_execption(chatbot, history,
a=f"解析项目: {txt}",
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
history = [] # 清空历史,以免输入溢出
import glob, os
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
yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en')
@CatchException
def Latex中文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"对整个Latex项目进行润色。函数插件贡献者: Binary-Husky"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import tiktoken
except:
report_execption(chatbot, history,
a=f"解析项目: {txt}",
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
history = [] # 清空历史,以免输入溢出
import glob, os
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
yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh')
@CatchException
def Latex英文纠错(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"对整个Latex项目进行纠错。函数插件贡献者: Binary-Husky"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import tiktoken
except:
report_execption(chatbot, history,
a=f"解析项目: {txt}",
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
history = [] # 清空历史,以免输入溢出
import glob, os
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
yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en', mode='proofread')
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