gpt-academicc / crazy_functions /批量Markdown翻译.py
qingxu98's picture
up
5c0a088
raw
history blame
12.4 kB
import glob, time, os, re
from toolbox import update_ui, trimmed_format_exc, gen_time_str, disable_auto_promotion
from toolbox import CatchException, report_execption, write_history_to_file
from toolbox import promote_file_to_downloadzone, get_log_folder
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}.md")
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, language):
manifest = []
for path, res in zip(self.file_paths, self.file_result):
dst_file = os.path.join(get_log_folder(), f'{gen_time_str()}.md')
with open(dst_file, 'w', encoding='utf8') as f:
manifest.append(dst_file)
f.write(res)
return manifest
def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'):
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
# <-------- 读取Markdown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()
# 记录删除注释后的文本
pfg.file_paths.append(fp)
pfg.file_contents.append(file_content)
# <-------- 拆分过长的Markdown文件 ---------->
pfg.run_file_split(max_token_limit=1500)
n_split = len(pfg.sp_file_contents)
# <-------- 多线程翻译开始 ---------->
if language == 'en->zh':
inputs_array = ["This is a Markdown file, translate it into Chinese, do not modify any existing Markdown commands:" +
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"This is a Markdown file, translate it into English, do not modify any existing Markdown commands:" +
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)]
else:
inputs_array = [f"This is a Markdown file, translate it into {language}, do not modify any existing Markdown commands, only answer me with translated results:" +
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
)
try:
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)
pfg.merge_result()
pfg.write_result(language)
except:
print(trimmed_format_exc())
# <-------- 整理结果,退出 ---------->
create_report_file_name = gen_time_str() + f"-chatgpt.md"
res = write_history_to_file(gpt_response_collection, file_basename=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 get_files_from_everything(txt, preference=''):
if txt == "": return False, None, None
success = True
if txt.startswith('http'):
import requests
from toolbox import get_conf
proxies, = get_conf('proxies')
# 网络的远程文件
if preference == 'Github':
print('正在从github下载资源 ...')
if not txt.endswith('.md'):
# Make a request to the GitHub API to retrieve the repository information
url = txt.replace("https://github.com/", "https://api.github.com/repos/") + '/readme'
response = requests.get(url, proxies=proxies)
txt = response.json()['download_url']
else:
txt = txt.replace("https://github.com/", "https://raw.githubusercontent.com/")
txt = txt.replace("/blob/", "/")
r = requests.get(txt, proxies=proxies)
download_local = f'{get_log_folder(plugin_name="批量Markdown翻译")}/raw-readme-{gen_time_str()}.md'
project_folder = f'{get_log_folder(plugin_name="批量Markdown翻译")}'
with open(download_local, 'wb+') as f: f.write(r.content)
file_manifest = [download_local]
elif txt.endswith('.md'):
# 直接给定文件
file_manifest = [txt]
project_folder = os.path.dirname(txt)
elif os.path.exists(txt):
# 本地路径,递归搜索
project_folder = txt
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)]
else:
project_folder = None
file_manifest = []
success = False
return success, file_manifest, project_folder
@CatchException
def Markdown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Markdown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
disable_auto_promotion(chatbot)
# 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
success, file_manifest, project_folder = get_files_from_everything(txt, preference="Github")
if not success:
# 什么都没有
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
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md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')
@CatchException
def Markdown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Markdown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
disable_auto_promotion(chatbot)
# 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
success, file_manifest, project_folder = get_files_from_everything(txt)
if not success:
# 什么都没有
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
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md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')
@CatchException
def Markdown翻译指定语言(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Markdown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
disable_auto_promotion(chatbot)
# 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
success, file_manifest, project_folder = get_files_from_everything(txt)
if not success:
# 什么都没有
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
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
language = plugin_kwargs.get("advanced_arg", 'Chinese')
yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language=language)