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from toolbox import update_ui, promote_file_to_downloadzone | |
from toolbox import CatchException, report_execption, write_history_to_file | |
fast_debug = False | |
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 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'): | |
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) | |
# <-------- 抽取摘要 ----------> | |
# if language == 'en': | |
# abs_extract_inputs = f"Please write an abstract for this paper" | |
# # 单线,获取文章meta信息 | |
# paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
# inputs=abs_extract_inputs, | |
# inputs_show_user=f"正在抽取摘要信息。", | |
# llm_kwargs=llm_kwargs, | |
# chatbot=chatbot, history=[], | |
# sys_prompt="Your job is to collect information from materials。", | |
# ) | |
# <-------- 多线程润色开始 ----------> | |
if language == 'en->zh': | |
inputs_array = ["Below is a section from an English academic paper, translate it into Chinese, do not modify any latex command such as \section, \cite and equations:" + | |
f"\n\n{frag}" for frag in pfg.sp_file_contents] | |
inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag] | |
sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)] | |
elif language == 'zh->en': | |
inputs_array = [f"Below is a section from a Chinese academic paper, translate it into English, do not modify any latex command such as \section, \cite and equations:" + | |
f"\n\n{frag}" for frag in pfg.sp_file_contents] | |
inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag] | |
sys_prompt_array = ["You are a professional academic paper translator." 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, # OpenAI所允许的最大并行过载 | |
scroller_max_len = 80 | |
) | |
# <-------- 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_history_to_file(gpt_response_collection, create_report_file_name) | |
promote_file_to_downloadzone(res, chatbot=chatbot) | |
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 | |
def Latex英译中(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项目进行翻译。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 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en->zh') | |
def Latex中译英(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项目进行翻译。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 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh->en') |