比较提交

..

40 次代码提交

作者 SHA1 备注 提交日期
binary-husky
34784333dc 融合PDF左右比例调整到95% 2023-09-10 17:22:35 +08:00
binary-husky
28d777a96b 修正报错消息 2023-09-10 16:52:35 +08:00
qingxu fu
c45fa88684 update translation matrix 2023-09-09 21:57:24 +08:00
binary-husky
ad9807dd14 更新虚空终端的提示 2023-09-09 20:32:44 +08:00
binary-husky
2a51715075 修复Dockerfile 2023-09-09 20:15:46 +08:00
binary-husky
7c307d8964 修复源代码解析模块与虚空终端的兼容性 2023-09-09 19:33:05 +08:00
binary-husky
baaacc5a7b Update README.md 2023-09-09 19:11:21 +08:00
binary-husky
6faf5947c9 Merge branch 'master' of github.com:binary-husky/chatgpt_academic 2023-09-09 18:30:59 +08:00
binary-husky
571335cbc4 fix docker file 2023-09-09 18:30:43 +08:00
binary-husky
7d5abb6d69 Merge pull request #1077 from jsz14897502/master
更改谷歌学术搜索助手获取摘要的逻辑
2023-09-09 18:24:30 +08:00
binary-husky
a0f592308a Merge branch 'master' into jsz14897502-master 2023-09-09 18:22:29 +08:00
binary-husky
e512d99879 添加一定的延迟,防止触发反爬虫机制 2023-09-09 18:22:22 +08:00
binary-husky
e70b636513 修复数学公式判定的Bug 2023-09-09 17:50:38 +08:00
binary-husky
408b8403fe Merge branch 'master' of github.com:binary-husky/chatgpt_academic 2023-09-08 12:10:22 +08:00
binary-husky
74f8cb3511 update dockerfile 2023-09-08 12:10:16 +08:00
qingxu fu
2202cf3701 remove proxy message 2023-09-08 11:11:53 +08:00
qingxu fu
cce69beee9 update error message 2023-09-08 11:08:02 +08:00
qingxu fu
347124c967 update scipdf_parser dep 2023-09-08 10:43:20 +08:00
qingxu fu
77a6105a9a 修改demo案例 2023-09-08 09:52:29 +08:00
qingxu fu
13c9606af7 修正下载PDF失败时产生的错误提示 2023-09-08 09:47:29 +08:00
binary-husky
bac6810e75 修改操作提示 2023-09-08 09:38:16 +08:00
binary-husky
c176187d24 修复因为函数返回值导致的不准确错误提示 2023-09-07 23:46:54 +08:00
binary-husky
31d5ee6ccc Update README.md 2023-09-07 23:05:54 +08:00
binary-husky
5e0dc9b9ad 修复PDF下载路径时间戳的问题 2023-09-07 18:51:09 +08:00
binary-husky
4c6f3aa427 CodeInterpreter 2023-09-07 17:45:44 +08:00
binary-husky
d7331befc1 add note 2023-09-07 17:42:47 +08:00
binary-husky
63219baa21 修正语音对话时 句子末尾显示异常的问题 2023-09-07 17:04:40 +08:00
binary-husky
97cb9a4adc full capacity docker file 2023-09-07 15:09:38 +08:00
binary-husky
24f41b0a75 new docker file 2023-09-07 00:45:03 +08:00
binary-husky
bfec29e9bc new docker file 2023-09-07 00:43:31 +08:00
binary-husky
dd9e624761 add new dockerfile 2023-09-07 00:40:11 +08:00
binary-husky
7855325ff9 update dockerfiles 2023-09-06 23:33:15 +08:00
binary-husky
2c039ff5c9 add session 2023-09-06 22:19:32 +08:00
binary-husky
9a5ee86434 Merge pull request #1084 from eltociear/patch-2
Update README.md
2023-09-06 21:56:39 +08:00
binary-husky
d6698db257 nougat翻译PDF论文 2023-09-06 15:32:11 +08:00
Ikko Eltociear Ashimine
b2d03bf2a3 Update README.md
arbitary -> arbitrary
2023-09-06 15:30:12 +09:00
binary-husky
d183e34461 添加一个全版本搜索的开关 2023-09-06 11:42:29 +08:00
binary-husky
fb78569335 Merge branch 'master' of https://github.com/jsz14897502/gpt_academic into jsz14897502-master 2023-09-06 10:27:52 +08:00
jsz14
03164bcb6f fix:没有获取到所有版本时的处理 2023-09-02 19:58:24 +08:00
jsz14
d052d425af 更改谷歌学术搜索助手获取摘要的逻辑 2023-08-30 19:14:01 +08:00
共有 27 个文件被更改,包括 860 次插入234 次删除

查看文件

@@ -0,0 +1,44 @@
# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
name: build-with-all-capacity
on:
push:
branches:
- 'master'
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}_with_all_capacity
jobs:
build-and-push-image:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- name: Checkout repository
uses: actions/checkout@v3
- name: Log in to the Container registry
uses: docker/login-action@v2
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@v4
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
- name: Build and push Docker image
uses: docker/build-push-action@v4
with:
context: .
push: true
file: docs/GithubAction+AllCapacity
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}

查看文件

@@ -10,7 +10,7 @@
**如果喜欢这个项目,请给它一个Star;如果您发明了好用的快捷键或函数插件,欢迎发pull requests** **如果喜欢这个项目,请给它一个Star;如果您发明了好用的快捷键或函数插件,欢迎发pull requests**
If you like this project, please give it a Star. If you've come up with more useful academic shortcuts or functional plugins, feel free to open an issue or pull request. We also have a README in [English|](docs/README_EN.md)[日本語|](docs/README_JP.md)[한국어|](https://github.com/mldljyh/ko_gpt_academic)[Русский|](docs/README_RS.md)[Français](docs/README_FR.md) translated by this project itself. If you like this project, please give it a Star. If you've come up with more useful academic shortcuts or functional plugins, feel free to open an issue or pull request. We also have a README in [English|](docs/README_EN.md)[日本語|](docs/README_JP.md)[한국어|](https://github.com/mldljyh/ko_gpt_academic)[Русский|](docs/README_RS.md)[Français](docs/README_FR.md) translated by this project itself.
To translate this project to arbitary language with GPT, read and run [`multi_language.py`](multi_language.py) (experimental). To translate this project to arbitrary language with GPT, read and run [`multi_language.py`](multi_language.py) (experimental).
> **Note** > **Note**
> >
@@ -54,7 +54,7 @@ Latex论文一键校对 | [函数插件] 仿Grammarly对Latex文章进行语法
⭐ChatGLM2微调模型 | 支持加载ChatGLM2微调模型,提供ChatGLM2微调辅助插件 ⭐ChatGLM2微调模型 | 支持加载ChatGLM2微调模型,提供ChatGLM2微调辅助插件
更多LLM模型接入,支持[huggingface部署](https://huggingface.co/spaces/qingxu98/gpt-academic) | 加入Newbing接口(新必应),引入清华[Jittorllms](https://github.com/Jittor/JittorLLMs)支持[LLaMA](https://github.com/facebookresearch/llama)和[盘古α](https://openi.org.cn/pangu/) 更多LLM模型接入,支持[huggingface部署](https://huggingface.co/spaces/qingxu98/gpt-academic) | 加入Newbing接口(新必应),引入清华[Jittorllms](https://github.com/Jittor/JittorLLMs)支持[LLaMA](https://github.com/facebookresearch/llama)和[盘古α](https://openi.org.cn/pangu/)
⭐[void-terminal](https://github.com/binary-husky/void-terminal) pip包 | 脱离GUI,在Python中直接调用本项目的所有函数插件开发中 ⭐[void-terminal](https://github.com/binary-husky/void-terminal) pip包 | 脱离GUI,在Python中直接调用本项目的所有函数插件开发中
⭐虚空终端插件 | 用自然语言,直接调度本项目其他插件 ⭐虚空终端插件 | [函数插件] 用自然语言,直接调度本项目其他插件
更多新功能展示 (图像生成等) …… | 见本文档结尾处 …… 更多新功能展示 (图像生成等) …… | 见本文档结尾处 ……
</div> </div>
@@ -149,11 +149,14 @@ python main.py
### 安装方法II使用Docker ### 安装方法II使用Docker
[![fullcapacity](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-all-capacity.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
1. 仅ChatGPT推荐大多数人选择,等价于docker-compose方案1 1. 仅ChatGPT推荐大多数人选择,等价于docker-compose方案1
[![basic](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml) [![basic](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml)
[![basiclatex](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml) [![basiclatex](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml)
[![basicaudio](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml) [![basicaudio](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
``` sh ``` sh
git clone --depth=1 https://github.com/binary-husky/gpt_academic.git # 下载项目 git clone --depth=1 https://github.com/binary-husky/gpt_academic.git # 下载项目
cd gpt_academic # 进入路径 cd gpt_academic # 进入路径
@@ -252,7 +255,7 @@ Tip不指定文件直接点击 `载入对话历史存档` 可以查看历史h
3. 虚空终端(从自然语言输入中,理解用户意图+自动调用其他插件) 3. 虚空终端(从自然语言输入中,理解用户意图+自动调用其他插件)
- 步骤一:输入 “ 请调用插件翻译PDF论文,地址为https://www.nature.com/articles/s41586-019-1724-z.pdf - 步骤一:输入 “ 请调用插件翻译PDF论文,地址为https://openreview.net/pdf?id=rJl0r3R9KX
- 步骤二:点击“虚空终端” - 步骤二:点击“虚空终端”
<div align="center"> <div align="center">

查看文件

@@ -5,7 +5,7 @@ def check_proxy(proxies):
try: try:
response = requests.get("https://ipapi.co/json/", proxies=proxies, timeout=4) response = requests.get("https://ipapi.co/json/", proxies=proxies, timeout=4)
data = response.json() data = response.json()
print(f'查询代理的地理位置,返回的结果是{data}') # print(f'查询代理的地理位置,返回的结果是{data}')
if 'country_name' in data: if 'country_name' in data:
country = data['country_name'] country = data['country_name']
result = f"代理配置 {proxies_https}, 代理所在地:{country}" result = f"代理配置 {proxies_https}, 代理所在地:{country}"

查看文件

@@ -501,6 +501,32 @@ def get_crazy_functions():
except: except:
print('Load function plugin failed') print('Load function plugin failed')
try:
from crazy_functions.批量翻译PDF文档_NOUGAT import 批量翻译PDF文档
function_plugins.update({
"精准翻译PDF文档NOUGAT": {
"Group": "学术",
"Color": "stop",
"AsButton": False,
"Function": HotReload(批量翻译PDF文档)
}
})
except:
print('Load function plugin failed')
# try:
# from crazy_functions.CodeInterpreter import 虚空终端CodeInterpreter
# function_plugins.update({
# "CodeInterpreter开发中,仅供测试": {
# "Group": "编程|对话",
# "Color": "stop",
# "AsButton": False,
# "Function": HotReload(虚空终端CodeInterpreter)
# }
# })
# except:
# print('Load function plugin failed')
# try: # try:
# from crazy_functions.chatglm微调工具 import 微调数据集生成 # from crazy_functions.chatglm微调工具 import 微调数据集生成

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@@ -0,0 +1,231 @@
from collections.abc import Callable, Iterable, Mapping
from typing import Any
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, promote_file_to_downloadzone, clear_file_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from .crazy_utils import input_clipping, try_install_deps
from multiprocessing import Process, Pipe
import os
import time
templete = """
```python
import ... # Put dependencies here, e.g. import numpy as np
class TerminalFunction(object): # Do not change the name of the class, The name of the class must be `TerminalFunction`
def run(self, path): # The name of the function must be `run`, it takes only a positional argument.
# rewrite the function you have just written here
...
return generated_file_path
```
"""
def inspect_dependency(chatbot, history):
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return True
def get_code_block(reply):
import re
pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
matches = re.findall(pattern, reply) # find all code blocks in text
if len(matches) == 1:
return matches[0].strip('python') # code block
for match in matches:
if 'class TerminalFunction' in match:
return match.strip('python') # code block
raise RuntimeError("GPT is not generating proper code.")
def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
# 输入
prompt_compose = [
f'Your job:\n'
f'1. write a single Python function, which takes a path of a `{file_type}` file as the only argument and returns a `string` containing the result of analysis or the path of generated files. \n',
f"2. You should write this function to perform following task: " + txt + "\n",
f"3. Wrap the output python function with markdown codeblock."
]
i_say = "".join(prompt_compose)
demo = []
# 第一步
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=i_say, inputs_show_user=i_say,
llm_kwargs=llm_kwargs, chatbot=chatbot, history=demo,
sys_prompt= r"You are a programmer."
)
history.extend([i_say, gpt_say])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
# 第二步
prompt_compose = [
"If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n",
templete
]
i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. "
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=i_say, inputs_show_user=inputs_show_user,
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
sys_prompt= r"You are a programmer."
)
code_to_return = gpt_say
history.extend([i_say, gpt_say])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
# # 第三步
# i_say = "Please list to packages to install to run the code above. Then show me how to use `try_install_deps` function to install them."
# i_say += 'For instance. `try_install_deps(["opencv-python", "scipy", "numpy"])`'
# installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive(
# inputs=i_say, inputs_show_user=inputs_show_user,
# llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
# sys_prompt= r"You are a programmer."
# )
# # # 第三步
# i_say = "Show me how to use `pip` to install packages to run the code above. "
# i_say += 'For instance. `pip install -r opencv-python scipy numpy`'
# installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive(
# inputs=i_say, inputs_show_user=i_say,
# llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
# sys_prompt= r"You are a programmer."
# )
installation_advance = ""
return code_to_return, installation_advance, txt, file_type, llm_kwargs, chatbot, history
def make_module(code):
module_file = 'gpt_fn_' + gen_time_str().replace('-','_')
with open(f'gpt_log/{module_file}.py', 'w', encoding='utf8') as f:
f.write(code)
def get_class_name(class_string):
import re
# Use regex to extract the class name
class_name = re.search(r'class (\w+)\(', class_string).group(1)
return class_name
class_name = get_class_name(code)
return f"gpt_log.{module_file}->{class_name}"
def init_module_instance(module):
import importlib
module_, class_ = module.split('->')
init_f = getattr(importlib.import_module(module_), class_)
return init_f()
def for_immediate_show_off_when_possible(file_type, fp, chatbot):
if file_type in ['png', 'jpg']:
image_path = os.path.abspath(fp)
chatbot.append(['这是一张图片, 展示如下:',
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
return chatbot
def subprocess_worker(instance, file_path, return_dict):
return_dict['result'] = instance.run(file_path)
def have_any_recent_upload_files(chatbot):
_5min = 5 * 60
if not chatbot: return False # chatbot is None
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
if not most_recent_uploaded: return False # most_recent_uploaded is None
if time.time() - most_recent_uploaded["time"] < _5min: return True # most_recent_uploaded is new
else: return False # most_recent_uploaded is too old
def get_recent_file_prompt_support(chatbot):
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
path = most_recent_uploaded['path']
return path
@CatchException
def 虚空终端CodeInterpreter(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
"""
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
plugin_kwargs 插件模型的参数,暂时没有用武之地
chatbot 聊天显示框的句柄,用于显示给用户
history 聊天历史,前情提要
system_prompt 给gpt的静默提醒
web_port 当前软件运行的端口号
"""
raise NotImplementedError
# 清空历史,以免输入溢出
history = []; clear_file_downloadzone(chatbot)
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"CodeInterpreter开源版, 此插件处于开发阶段, 建议暂时不要使用, 插件初始化中 ..."
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if have_any_recent_upload_files(chatbot):
file_path = get_recent_file_prompt_support(chatbot)
else:
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 读取文件
if ("recently_uploaded_files" in plugin_kwargs) and (plugin_kwargs["recently_uploaded_files"] == ""): plugin_kwargs.pop("recently_uploaded_files")
recently_uploaded_files = plugin_kwargs.get("recently_uploaded_files", None)
file_path = recently_uploaded_files[-1]
file_type = file_path.split('.')[-1]
# 粗心检查
if 'private_upload' in txt:
chatbot.append([
"...",
f"请在输入框内填写需求,然后再次点击该插件(文件路径 {file_path} 已经被记忆)"
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 开始干正事
for j in range(5): # 最多重试5次
try:
code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
code = get_code_block(code)
res = make_module(code)
instance = init_module_instance(res)
break
except Exception as e:
chatbot.append([f"{j}次代码生成尝试,失败了", f"错误追踪\n```\n{trimmed_format_exc()}\n```\n"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 代码生成结束, 开始执行
try:
import multiprocessing
manager = multiprocessing.Manager()
return_dict = manager.dict()
p = multiprocessing.Process(target=subprocess_worker, args=(instance, file_path, return_dict))
# only has 10 seconds to run
p.start(); p.join(timeout=10)
if p.is_alive(): p.terminate(); p.join()
p.close()
res = return_dict['result']
# res = instance.run(file_path)
except Exception as e:
chatbot.append(["执行失败了", f"错误追踪\n```\n{trimmed_format_exc()}\n```\n"])
# chatbot.append(["如果是缺乏依赖,请参考以下建议", installation_advance])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 顺利完成,收尾
res = str(res)
if os.path.exists(res):
chatbot.append(["执行成功了,结果是一个有效文件", "结果:" + res])
new_file_path = promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot = for_immediate_show_off_when_possible(file_type, new_file_path, chatbot)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
else:
chatbot.append(["执行成功了,结果是一个字符串", "结果:" + res])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
"""
测试:
裁剪图像,保留下半部分
交换图像的蓝色通道和红色通道
将图像转为灰度图像
将csv文件转excel表格
"""

查看文件

@@ -109,7 +109,7 @@ def arxiv_download(chatbot, history, txt):
url_ = txt # https://arxiv.org/abs/1707.06690 url_ = txt # https://arxiv.org/abs/1707.06690
if not txt.startswith('https://arxiv.org/abs/'): 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_}" 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 yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history) # 刷新界面
return msg, None return msg, None
# <-------------- set format -------------> # <-------------- set format ------------->
@@ -255,7 +255,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
project_folder = txt project_folder = txt
else: else:
if txt == "": txt = '空空如也的输入栏' 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}") report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无法处理: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return return

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@@ -469,6 +469,7 @@ def read_and_clean_pdf_text(fp):
'- ', '') for t in text_areas['blocks'] if 'lines' in t] '- ', '') for t in text_areas['blocks'] if 'lines' in t]
############################## <第 2 步,获取正文主字体> ################################## ############################## <第 2 步,获取正文主字体> ##################################
try:
fsize_statiscs = {} fsize_statiscs = {}
for span in meta_span: for span in meta_span:
if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0 if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
@@ -476,7 +477,8 @@ def read_and_clean_pdf_text(fp):
main_fsize = max(fsize_statiscs, key=fsize_statiscs.get) main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
if REMOVE_FOOT_NOTE: if REMOVE_FOOT_NOTE:
give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
except:
raise RuntimeError(f'抱歉, 我们暂时无法解析此PDF文档: {fp}')
############################## <第 3 步,切分和重新整合> ################################## ############################## <第 3 步,切分和重新整合> ##################################
mega_sec = [] mega_sec = []
sec = [] sec = []
@@ -591,11 +593,16 @@ def get_files_from_everything(txt, type): # type='.md'
# 网络的远程文件 # 网络的远程文件
import requests import requests
from toolbox import get_conf from toolbox import get_conf
from toolbox import get_log_folder, gen_time_str
proxies, = get_conf('proxies') proxies, = get_conf('proxies')
try:
r = requests.get(txt, proxies=proxies) r = requests.get(txt, proxies=proxies)
with open('./gpt_log/temp'+type, 'wb+') as f: f.write(r.content) except:
project_folder = './gpt_log/' raise ConnectionRefusedError(f"无法下载资源{txt},请检查。")
file_manifest = ['./gpt_log/temp'+type] path = os.path.join(get_log_folder(plugin_name='web_download'), gen_time_str()+type)
with open(path, 'wb+') as f: f.write(r.content)
project_folder = get_log_folder(plugin_name='web_download')
file_manifest = [path]
elif txt.endswith(type): elif txt.endswith(type):
# 直接给定文件 # 直接给定文件
file_manifest = [txt] file_manifest = [txt]

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@@ -423,7 +423,7 @@ def compile_latex_with_timeout(command, cwd, timeout=60):
def merge_pdfs(pdf1_path, pdf2_path, output_path): def merge_pdfs(pdf1_path, pdf2_path, output_path):
import PyPDF2 import PyPDF2
Percent = 0.8 Percent = 0.95
# Open the first PDF file # Open the first PDF file
with open(pdf1_path, 'rb') as pdf1_file: with open(pdf1_path, 'rb') as pdf1_file:
pdf1_reader = PyPDF2.PdfFileReader(pdf1_file) pdf1_reader = PyPDF2.PdfFileReader(pdf1_file)

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@@ -1,4 +1,4 @@
import time, threading, json import time, logging, json
class AliyunASR(): class AliyunASR():
@@ -12,14 +12,14 @@ class AliyunASR():
message = json.loads(message) message = json.loads(message)
self.parsed_sentence = message['payload']['result'] self.parsed_sentence = message['payload']['result']
self.event_on_entence_end.set() self.event_on_entence_end.set()
print(self.parsed_sentence) # print(self.parsed_sentence)
def test_on_start(self, message, *args): def test_on_start(self, message, *args):
# print("test_on_start:{}".format(message)) # print("test_on_start:{}".format(message))
pass pass
def test_on_error(self, message, *args): def test_on_error(self, message, *args):
print("on_error args=>{}".format(args)) logging.error("on_error args=>{}".format(args))
pass pass
def test_on_close(self, *args): def test_on_close(self, *args):
@@ -36,7 +36,6 @@ class AliyunASR():
# print("on_completed:args=>{} message=>{}".format(args, message)) # print("on_completed:args=>{} message=>{}".format(args, message))
pass pass
def audio_convertion_thread(self, uuid): def audio_convertion_thread(self, uuid):
# 在一个异步线程中采集音频 # 在一个异步线程中采集音频
import nls # pip install git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git import nls # pip install git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git

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@@ -20,6 +20,11 @@ def get_avail_grobid_url():
def parse_pdf(pdf_path, grobid_url): def parse_pdf(pdf_path, grobid_url):
import scipdf # pip install scipdf_parser import scipdf # pip install scipdf_parser
if grobid_url.endswith('/'): grobid_url = grobid_url.rstrip('/') if grobid_url.endswith('/'): grobid_url = grobid_url.rstrip('/')
try:
article_dict = scipdf.parse_pdf_to_dict(pdf_path, grobid_url=grobid_url) article_dict = scipdf.parse_pdf_to_dict(pdf_path, grobid_url=grobid_url)
except GROBID_OFFLINE_EXCEPTION:
raise GROBID_OFFLINE_EXCEPTION("GROBID服务不可用,请修改config中的GROBID_URL,可修改成本地GROBID服务。")
except:
raise RuntimeError("解析PDF失败,请检查PDF是否损坏。")
return article_dict return article_dict

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@@ -0,0 +1,271 @@
from toolbox import CatchException, report_execption, gen_time_str
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
from toolbox import write_history_to_file, get_log_folder
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
from .crazy_utils import read_and_clean_pdf_text
from .pdf_fns.parse_pdf import parse_pdf, get_avail_grobid_url
from colorful import *
import os
import math
import logging
def markdown_to_dict(article_content):
import markdown
from bs4 import BeautifulSoup
cur_t = ""
cur_c = ""
results = {}
for line in article_content:
if line.startswith('#'):
if cur_t!="":
if cur_t not in results:
results.update({cur_t:cur_c.lstrip('\n')})
else:
# 处理重名的章节
results.update({cur_t + " " + gen_time_str():cur_c.lstrip('\n')})
cur_t = line.rstrip('\n')
cur_c = ""
else:
cur_c += line
results_final = {}
for k in list(results.keys()):
if k.startswith('# '):
results_final['title'] = k.split('# ')[-1]
results_final['authors'] = results.pop(k).lstrip('\n')
if k.startswith('###### Abstract'):
results_final['abstract'] = results.pop(k).lstrip('\n')
results_final_sections = []
for k,v in results.items():
results_final_sections.append({
'heading':k.lstrip("# "),
'text':v if len(v) > 0 else f"The beginning of {k.lstrip('# ')} section."
})
results_final['sections'] = results_final_sections
return results_final
@CatchException
def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
disable_auto_promotion(chatbot)
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"批量翻译PDF文档。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 nougat
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 nougat-ocr tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 清空历史,以免输入溢出
history = []
from .crazy_utils import get_files_from_everything
success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf')
# 检测输入参数,如没有给定输入参数,直接退出
if not success:
if txt == "": txt = '空空如也的输入栏'
# 如果没找到任何文件
if len(file_manifest) == 0:
report_execption(chatbot, history,
a=f"解析项目: {txt}", b=f"找不到任何.tex或.pdf文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 开始正式执行任务
yield from 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
def nougat_with_timeout(command, cwd, timeout=3600):
import subprocess
process = subprocess.Popen(command, shell=True, 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 NOUGAT_parse_pdf(fp):
import glob
from toolbox import get_log_folder, gen_time_str
dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
os.makedirs(dst)
nougat_with_timeout(f'nougat --out "{os.path.abspath(dst)}" "{os.path.abspath(fp)}"', os.getcwd())
res = glob.glob(os.path.join(dst,'*.mmd'))
if len(res) == 0:
raise RuntimeError("Nougat解析论文失败。")
return res[0]
def 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
import copy
import tiktoken
TOKEN_LIMIT_PER_FRAGMENT = 1280
generated_conclusion_files = []
generated_html_files = []
DST_LANG = "中文"
for index, fp in enumerate(file_manifest):
chatbot.append(["当前进度:", f"正在解析论文,请稍候。第一次运行时,需要花费较长时间下载NOUGAT参数"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
fpp = NOUGAT_parse_pdf(fp)
with open(fpp, 'r', encoding='utf8') as f:
article_content = f.readlines()
article_dict = markdown_to_dict(article_content)
logging.info(article_dict)
prompt = "以下是一篇学术论文的基本信息:\n"
# title
title = article_dict.get('title', '无法获取 title'); prompt += f'title:{title}\n\n'
# authors
authors = article_dict.get('authors', '无法获取 authors'); prompt += f'authors:{authors}\n\n'
# abstract
abstract = article_dict.get('abstract', '无法获取 abstract'); prompt += f'abstract:{abstract}\n\n'
# command
prompt += f"请将题目和摘要翻译为{DST_LANG}"
meta = [f'# Title:\n\n', title, f'# Abstract:\n\n', abstract ]
# 单线,获取文章meta信息
paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=prompt,
inputs_show_user=prompt,
llm_kwargs=llm_kwargs,
chatbot=chatbot, history=[],
sys_prompt="You are an academic paper reader。",
)
# 多线,翻译
inputs_array = []
inputs_show_user_array = []
# get_token_num
from request_llm.bridge_all import model_info
enc = model_info[llm_kwargs['llm_model']]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
def break_down(txt):
raw_token_num = get_token_num(txt)
if raw_token_num <= TOKEN_LIMIT_PER_FRAGMENT:
return [txt]
else:
# raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
# find a smooth token limit to achieve even seperation
count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
token_limit_smooth = raw_token_num // count + count
return breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn=get_token_num, limit=token_limit_smooth)
for section in article_dict.get('sections'):
if len(section['text']) == 0: continue
section_frags = break_down(section['text'])
for i, fragment in enumerate(section_frags):
heading = section['heading']
if len(section_frags) > 1: heading += f' Part-{i+1}'
inputs_array.append(
f"你需要翻译{heading}章节,内容如下: \n\n{fragment}"
)
inputs_show_user_array.append(
f"# {heading}\n\n{fragment}"
)
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=[meta for _ in inputs_array],
sys_prompt_array=[
"请你作为一个学术翻译,负责把学术论文准确翻译成中文。注意文章中的每一句话都要翻译。" for _ in inputs_array],
)
res_path = write_history_to_file(meta + ["# Meta Translation" , paper_meta_info] + gpt_response_collection, file_basename=None, file_fullname=None)
promote_file_to_downloadzone(res_path, rename_file=os.path.basename(fp)+'.md', chatbot=chatbot)
generated_conclusion_files.append(res_path)
ch = construct_html()
orig = ""
trans = ""
gpt_response_collection_html = copy.deepcopy(gpt_response_collection)
for i,k in enumerate(gpt_response_collection_html):
if i%2==0:
gpt_response_collection_html[i] = inputs_show_user_array[i//2]
else:
gpt_response_collection_html[i] = gpt_response_collection_html[i]
final = ["", "", "一、论文概况", "", "Abstract", paper_meta_info, "二、论文翻译", ""]
final.extend(gpt_response_collection_html)
for i, k in enumerate(final):
if i%2==0:
orig = k
if i%2==1:
trans = k
ch.add_row(a=orig, b=trans)
create_report_file_name = f"{os.path.basename(fp)}.trans.html"
html_file = ch.save_file(create_report_file_name)
generated_html_files.append(html_file)
promote_file_to_downloadzone(html_file, rename_file=os.path.basename(html_file), chatbot=chatbot)
chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
class construct_html():
def __init__(self) -> None:
self.css = """
.row {
display: flex;
flex-wrap: wrap;
}
.column {
flex: 1;
padding: 10px;
}
.table-header {
font-weight: bold;
border-bottom: 1px solid black;
}
.table-row {
border-bottom: 1px solid lightgray;
}
.table-cell {
padding: 5px;
}
"""
self.html_string = f'<!DOCTYPE html><head><meta charset="utf-8"><title>翻译结果</title><style>{self.css}</style></head>'
def add_row(self, a, b):
tmp = """
<div class="row table-row">
<div class="column table-cell">REPLACE_A</div>
<div class="column table-cell">REPLACE_B</div>
</div>
"""
from toolbox import markdown_convertion
tmp = tmp.replace('REPLACE_A', markdown_convertion(a))
tmp = tmp.replace('REPLACE_B', markdown_convertion(b))
self.html_string += tmp
def save_file(self, file_name):
with open(os.path.join(get_log_folder(), file_name), 'w', encoding='utf8') as f:
f.write(self.html_string.encode('utf-8', 'ignore').decode())
return os.path.join(get_log_folder(), file_name)

查看文件

@@ -24,10 +24,11 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
try: try:
import fitz import fitz
import tiktoken import tiktoken
import scipdf
except: except:
report_execption(chatbot, history, report_execption(chatbot, history,
a=f"解析项目: {txt}", 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 pymupdf tiktoken```。") 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 pymupdf tiktoken scipdf_parser```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return return
@@ -58,7 +59,6 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url): def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url):
import copy import copy
import tiktoken
TOKEN_LIMIT_PER_FRAGMENT = 1280 TOKEN_LIMIT_PER_FRAGMENT = 1280
generated_conclusion_files = [] generated_conclusion_files = []
generated_html_files = [] generated_html_files = []
@@ -66,7 +66,7 @@ def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwa
for index, fp in enumerate(file_manifest): for index, fp in enumerate(file_manifest):
chatbot.append(["当前进度:", f"正在连接GROBID服务,请稍候: {grobid_url}\n如果等待时间过长,请修改config中的GROBID_URL,可修改成本地GROBID服务。"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 chatbot.append(["当前进度:", f"正在连接GROBID服务,请稍候: {grobid_url}\n如果等待时间过长,请修改config中的GROBID_URL,可修改成本地GROBID服务。"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
article_dict = parse_pdf(fp, grobid_url) article_dict = parse_pdf(fp, grobid_url)
print(article_dict) if article_dict is None: raise RuntimeError("解析PDF失败,请检查PDF是否损坏。")
prompt = "以下是一篇学术论文的基本信息:\n" prompt = "以下是一篇学术论文的基本信息:\n"
# title # title
title = article_dict.get('title', '无法获取 title'); prompt += f'title:{title}\n\n' title = article_dict.get('title', '无法获取 title'); prompt += f'title:{title}\n\n'

查看文件

@@ -24,12 +24,13 @@ explain_msg = """
## 虚空终端插件说明: ## 虚空终端插件说明:
1. 请用**自然语言**描述您需要做什么。例如: 1. 请用**自然语言**描述您需要做什么。例如:
- 「请调用插件,为我翻译PDF论文,论文我刚刚放到上传区了 - 「请调用插件,为我翻译PDF论文,论文我刚刚放到上传区了」
- 「请调用插件翻译PDF论文,地址为https://www.nature.com/articles/s41586-019-1724-z.pdf - 「请调用插件翻译PDF论文,地址为https://openreview.net/pdf?id=rJl0r3R9KX
- 「生成一张图片,图中鲜花怒放,绿草如茵,用插件实现。 - 「把Arxiv论文翻译成中文PDF,arxiv论文的ID是1812.10695,记得用插件!
- 「生成一张图片,图中鲜花怒放,绿草如茵,用插件实现」
- 「用插件翻译README,Github网址是https://github.com/facebookresearch/co-tracker」 - 「用插件翻译README,Github网址是https://github.com/facebookresearch/co-tracker」
- 「给爷翻译Arxiv论文,arxiv论文的ID是1812.10695,记得用插件,不要自己瞎搞! - 「我不喜欢当前的界面颜色,修改配置,把主题THEME更换为THEME="High-Contrast"
- 「我不喜欢当前的界面颜色,修改配置,把主题THEME更换为THEME="High-Contrast" - 「请调用插件,解析python源代码项目,代码我刚刚打包拖到上传区了
- 「请问Transformer网络的结构是怎样的?」 - 「请问Transformer网络的结构是怎样的?」
2. 您可以打开插件下拉菜单以了解本项目的各种能力。 2. 您可以打开插件下拉菜单以了解本项目的各种能力。

查看文件

@@ -1,12 +1,13 @@
from toolbox import update_ui from toolbox import update_ui, promote_file_to_downloadzone, disable_auto_promotion
from toolbox import CatchException, report_execption, write_results_to_file from toolbox import CatchException, report_execption, write_history_to_file
from .crazy_utils import input_clipping from .crazy_utils import input_clipping
def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt): def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
import os, copy import os, copy
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
msg = '正常' disable_auto_promotion(chatbot=chatbot)
summary_batch_isolation = True summary_batch_isolation = True
inputs_array = [] inputs_array = []
inputs_show_user_array = [] inputs_show_user_array = []
@@ -43,7 +44,8 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
# 全部文件解析完成,结果写入文件,准备对工程源代码进行汇总分析 # 全部文件解析完成,结果写入文件,准备对工程源代码进行汇总分析
report_part_1 = copy.deepcopy(gpt_response_collection) report_part_1 = copy.deepcopy(gpt_response_collection)
history_to_return = report_part_1 history_to_return = report_part_1
res = write_results_to_file(report_part_1) res = write_history_to_file(report_part_1)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成?", "逐个文件分析已完成。" + res + "\n\n正在开始汇总。")) chatbot.append(("完成?", "逐个文件分析已完成。" + res + "\n\n正在开始汇总。"))
yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面 yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面
@@ -97,7 +99,8 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
############################## <END> ################################## ############################## <END> ##################################
history_to_return.extend(report_part_2) history_to_return.extend(report_part_2)
res = write_results_to_file(history_to_return) res = write_history_to_file(history_to_return)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res)) chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面 yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面

查看文件

@@ -80,9 +80,9 @@ class InterviewAssistant(AliyunASR):
def __init__(self): def __init__(self):
self.capture_interval = 0.5 # second self.capture_interval = 0.5 # second
self.stop = False self.stop = False
self.parsed_text = "" self.parsed_text = "" # 下个句子中已经说完的部分, 由 test_on_result_chg() 写入
self.parsed_sentence = "" self.parsed_sentence = "" # 某段话的整个句子,由 test_on_sentence_end() 写入
self.buffered_sentence = "" self.buffered_sentence = "" #
self.event_on_result_chg = threading.Event() self.event_on_result_chg = threading.Event()
self.event_on_entence_end = threading.Event() self.event_on_entence_end = threading.Event()
self.event_on_commit_question = threading.Event() self.event_on_commit_question = threading.Event()
@@ -132,7 +132,7 @@ class InterviewAssistant(AliyunASR):
self.plugin_wd.feed() self.plugin_wd.feed()
if self.event_on_result_chg.is_set(): if self.event_on_result_chg.is_set():
# update audio decode result # called when some words have finished
self.event_on_result_chg.clear() self.event_on_result_chg.clear()
chatbot[-1] = list(chatbot[-1]) chatbot[-1] = list(chatbot[-1])
chatbot[-1][0] = self.buffered_sentence + self.parsed_text chatbot[-1][0] = self.buffered_sentence + self.parsed_text
@@ -144,7 +144,11 @@ class InterviewAssistant(AliyunASR):
# called when a sentence has ended # called when a sentence has ended
self.event_on_entence_end.clear() self.event_on_entence_end.clear()
self.parsed_text = self.parsed_sentence self.parsed_text = self.parsed_sentence
self.buffered_sentence += self.parsed_sentence self.buffered_sentence += self.parsed_text
chatbot[-1] = list(chatbot[-1])
chatbot[-1][0] = self.buffered_sentence
history = chatbot2history(chatbot)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if self.event_on_commit_question.is_set(): if self.event_on_commit_question.is_set():
# called when a question should be commited # called when a question should be commited

查看文件

@@ -1,26 +1,75 @@
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from toolbox import CatchException, report_execption, write_results_to_file from toolbox import CatchException, report_execption, promote_file_to_downloadzone
from toolbox import update_ui from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
import logging
import requests
import time
import random
ENABLE_ALL_VERSION_SEARCH = True
def get_meta_information(url, chatbot, history): def get_meta_information(url, chatbot, history):
import requests
import arxiv import arxiv
import difflib import difflib
import re
from bs4 import BeautifulSoup from bs4 import BeautifulSoup
from toolbox import get_conf from toolbox import get_conf
from urllib.parse import urlparse
session = requests.session()
proxies, = get_conf('proxies') proxies, = get_conf('proxies')
headers = { headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'en-US,en;q=0.9,zh-CN;q=0.8,zh;q=0.7',
'Cache-Control':'max-age=0',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
'Connection': 'keep-alive'
} }
# 发送 GET 请求 session.proxies.update(proxies)
response = requests.get(url, proxies=proxies, headers=headers) session.headers.update(headers)
response = session.get(url)
# 解析网页内容 # 解析网页内容
soup = BeautifulSoup(response.text, "html.parser") soup = BeautifulSoup(response.text, "html.parser")
def string_similar(s1, s2): def string_similar(s1, s2):
return difflib.SequenceMatcher(None, s1, s2).quick_ratio() return difflib.SequenceMatcher(None, s1, s2).quick_ratio()
if ENABLE_ALL_VERSION_SEARCH:
def search_all_version(url):
time.sleep(random.randint(1,5)) # 睡一会防止触发google反爬虫
response = session.get(url)
soup = BeautifulSoup(response.text, "html.parser")
for result in soup.select(".gs_ri"):
try:
url = result.select_one(".gs_rt").a['href']
except:
continue
arxiv_id = extract_arxiv_id(url)
if not arxiv_id:
continue
search = arxiv.Search(
id_list=[arxiv_id],
max_results=1,
sort_by=arxiv.SortCriterion.Relevance,
)
try: paper = next(search.results())
except: paper = None
return paper
return None
def extract_arxiv_id(url):
# 返回给定的url解析出的arxiv_id,如url未成功匹配返回None
pattern = r'arxiv.org/abs/([^/]+)'
match = re.search(pattern, url)
if match:
return match.group(1)
else:
return None
profile = [] profile = []
# 获取所有文章的标题和作者 # 获取所有文章的标题和作者
for result in soup.select(".gs_ri"): for result in soup.select(".gs_ri"):
@@ -31,32 +80,45 @@ def get_meta_information(url, chatbot, history):
except: except:
citation = 'cited by 0' citation = 'cited by 0'
abstract = result.select_one(".gs_rs").text.strip() # 摘要在 .gs_rs 中的文本,需要清除首尾空格 abstract = result.select_one(".gs_rs").text.strip() # 摘要在 .gs_rs 中的文本,需要清除首尾空格
# 首先在arxiv上搜索,获取文章摘要
search = arxiv.Search( search = arxiv.Search(
query = title, query = title,
max_results = 1, max_results = 1,
sort_by = arxiv.SortCriterion.Relevance, sort_by = arxiv.SortCriterion.Relevance,
) )
try: try: paper = next(search.results())
paper = next(search.results()) except: paper = None
if string_similar(title, paper.title) > 0.90: # same paper
is_match = paper is not None and string_similar(title, paper.title) > 0.90
# 如果在Arxiv上匹配失败,检索文章的历史版本的题目
if not is_match and ENABLE_ALL_VERSION_SEARCH:
other_versions_page_url = [tag['href'] for tag in result.select_one('.gs_flb').select('.gs_nph') if 'cluster' in tag['href']]
if len(other_versions_page_url) > 0:
other_versions_page_url = other_versions_page_url[0]
paper = search_all_version('http://' + urlparse(url).netloc + other_versions_page_url)
is_match = paper is not None and string_similar(title, paper.title) > 0.90
if is_match:
# same paper
abstract = paper.summary.replace('\n', ' ') abstract = paper.summary.replace('\n', ' ')
is_paper_in_arxiv = True is_paper_in_arxiv = True
else: # different paper else:
# different paper
abstract = abstract abstract = abstract
is_paper_in_arxiv = False is_paper_in_arxiv = False
paper = next(search.results())
except: logging.info('[title]:' + title)
abstract = abstract logging.info('[author]:' + author)
is_paper_in_arxiv = False logging.info('[citation]:' + citation)
print(title)
print(author)
print(citation)
profile.append({ profile.append({
'title':title, 'title': title,
'author':author, 'author': author,
'citation':citation, 'citation': citation,
'abstract':abstract, 'abstract': abstract,
'is_paper_in_arxiv':is_paper_in_arxiv, 'is_paper_in_arxiv': is_paper_in_arxiv,
}) })
chatbot[-1] = [chatbot[-1][0], title + f'\n\n是否在arxiv中不在arxiv中无法获取完整摘要:{is_paper_in_arxiv}\n\n' + abstract] chatbot[-1] = [chatbot[-1][0], title + f'\n\n是否在arxiv中不在arxiv中无法获取完整摘要:{is_paper_in_arxiv}\n\n' + abstract]
@@ -65,6 +127,7 @@ def get_meta_information(url, chatbot, history):
@CatchException @CatchException
def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
disable_auto_promotion(chatbot=chatbot)
# 基本信息:功能、贡献者 # 基本信息:功能、贡献者
chatbot.append([ chatbot.append([
"函数插件功能?", "函数插件功能?",
@@ -86,6 +149,9 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
# 清空历史,以免输入溢出 # 清空历史,以免输入溢出
history = [] history = []
meta_paper_info_list = yield from get_meta_information(txt, chatbot, history) meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
if len(meta_paper_info_list) == 0:
yield from update_ui_lastest_msg(lastmsg='获取文献失败,可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
return
batchsize = 5 batchsize = 5
for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)): for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):
if len(meta_paper_info_list[:batchsize]) > 0: if len(meta_paper_info_list[:batchsize]) > 0:
@@ -107,6 +173,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
"已经全部完成,您可以试试让AI写一个Related Works,例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."]) "已经全部完成,您可以试试让AI写一个Related Works,例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."])
msg = '正常' msg = '正常'
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
res = write_results_to_file(history) path = write_history_to_file(history)
chatbot.append(("完成了吗?", res)); promote_file_to_downloadzone(path, chatbot=chatbot)
chatbot.append(("完成了吗?", path));
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面

查看文件

@@ -1,62 +1,2 @@
# How to build | 如何构建: docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM . # 此Dockerfile不再维护,请前往docs/GithubAction+ChatGLM+Moss
# How to run | (1) 我想直接一键运行选择0号GPU: docker run --rm -it --net=host --gpus \"device=0\" gpt-academic
# How to run | (2) 我想运行之前进容器做一些调整选择1号GPU: docker run --rm -it --net=host --gpus \"device=1\" gpt-academic bash
# 从NVIDIA源,从而支持显卡运损检查宿主的nvidia-smi中的cuda版本必须>=11.3
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
ARG useProxyNetwork=''
RUN apt-get update
RUN apt-get install -y curl proxychains curl
RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
# 配置代理网络构建Docker镜像时使用
# # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
RUN $useProxyNetwork curl cip.cc
RUN sed -i '$ d' /etc/proxychains.conf
RUN sed -i '$ d' /etc/proxychains.conf
# 在这里填写主机的代理协议用于从github拉取代码
RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
ARG useProxyNetwork=proxychains
# # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
# use python3 as the system default python
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
# 下载pytorch
RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
# 下载分支
WORKDIR /gpt
RUN $useProxyNetwork git clone https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
RUN $useProxyNetwork python3 -m pip install -r requirements.txt
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_newbing.txt
# 预热CHATGLM参数非必要 可选步骤)
RUN echo ' \n\
from transformers import AutoModel, AutoTokenizer \n\
chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) \n\
chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float() ' >> warm_up_chatglm.py
RUN python3 -u warm_up_chatglm.py
# 禁用缓存,确保更新代码
ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
RUN $useProxyNetwork git pull
# 预热Tiktoken模块
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
# 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
# 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,fkxxxx-api2dkey2,........"
# LLM_MODEL 是选择初始的模型
# LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
# [说明: 以下内容与`config.py`一一对应,请查阅config.py来完成一下配置的填写]
RUN echo ' \n\
API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
USE_PROXY = True \n\
LLM_MODEL = "chatglm" \n\
LOCAL_MODEL_DEVICE = "cuda" \n\
proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
# 启动
CMD ["python3", "-u", "main.py"]

查看文件

@@ -1,59 +1 @@
# How to build | 如何构建: docker build -t gpt-academic-jittor --network=host -f Dockerfile+ChatGLM . # 此Dockerfile不再维护,请前往docs/GithubAction+JittorLLMs
# How to run | (1) 我想直接一键运行选择0号GPU: docker run --rm -it --net=host --gpus \"device=0\" gpt-academic-jittor bash
# How to run | (2) 我想运行之前进容器做一些调整选择1号GPU: docker run --rm -it --net=host --gpus \"device=1\" gpt-academic-jittor bash
# 从NVIDIA源,从而支持显卡运损检查宿主的nvidia-smi中的cuda版本必须>=11.3
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
ARG useProxyNetwork=''
RUN apt-get update
RUN apt-get install -y curl proxychains curl g++
RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
# 配置代理网络构建Docker镜像时使用
# # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
RUN $useProxyNetwork curl cip.cc
RUN sed -i '$ d' /etc/proxychains.conf
RUN sed -i '$ d' /etc/proxychains.conf
# 在这里填写主机的代理协议用于从github拉取代码
RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
ARG useProxyNetwork=proxychains
# # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
# use python3 as the system default python
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
# 下载pytorch
RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
# 下载分支
WORKDIR /gpt
RUN $useProxyNetwork git clone https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
RUN $useProxyNetwork python3 -m pip install -r requirements.txt
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_newbing.txt
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I
# 下载JittorLLMs
RUN $useProxyNetwork git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llm/jittorllms
# 禁用缓存,确保更新代码
ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
RUN $useProxyNetwork git pull
# 预热Tiktoken模块
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
# 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
# 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,fkxxxx-api2dkey2,........"
# LLM_MODEL 是选择初始的模型
# LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
# [说明: 以下内容与`config.py`一一对应,请查阅config.py来完成一下配置的填写]
RUN echo ' \n\
API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
USE_PROXY = True \n\
LLM_MODEL = "chatglm" \n\
LOCAL_MODEL_DEVICE = "cuda" \n\
proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
# 启动
CMD ["python3", "-u", "main.py"]

查看文件

@@ -1,27 +1 @@
# 此Dockerfile适用于“无本地模型”的环境构建,如果需要使用chatglm等本地模型,请参考 docs/Dockerfile+ChatGLM # 此Dockerfile不再维护,请前往docs/GithubAction+NoLocal+Latex
# - 1 修改 `config.py`
# - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/Dockerfile+NoLocal+Latex .
# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
FROM fuqingxu/python311_texlive_ctex:latest
# 指定路径
WORKDIR /gpt
ARG useProxyNetwork=''
RUN $useProxyNetwork pip3 install gradio openai numpy arxiv rich -i https://pypi.douban.com/simple/
RUN $useProxyNetwork pip3 install colorama Markdown pygments pymupdf -i https://pypi.douban.com/simple/
# 装载项目文件
COPY . .
# 安装依赖
RUN $useProxyNetwork pip3 install -r requirements.txt -i https://pypi.douban.com/simple/
# 可选步骤,用于预热模块
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
# 启动
CMD ["python3", "-u", "main.py"]

查看文件

@@ -0,0 +1,37 @@
# docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacity --network=host --build-arg http_proxy=http://localhost:10881 --build-arg https_proxy=http://localhost:10881 .
# 从NVIDIA源,从而支持显卡检查宿主的nvidia-smi中的cuda版本必须>=11.3
FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
# use python3 as the system default python
WORKDIR /gpt
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
# 下载pytorch
RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
# 准备pip依赖
RUN python3 -m pip install openai numpy arxiv rich
RUN python3 -m pip install colorama Markdown pygments pymupdf
RUN python3 -m pip install python-docx moviepy pdfminer
RUN python3 -m pip install zh_langchain==0.2.1
RUN python3 -m pip install nougat-ocr
RUN python3 -m pip install rarfile py7zr
RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
# 下载分支
WORKDIR /gpt
RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
RUN git clone https://github.com/OpenLMLab/MOSS.git request_llm/moss
RUN python3 -m pip install -r requirements.txt
RUN python3 -m pip install -r request_llm/requirements_moss.txt
RUN python3 -m pip install -r request_llm/requirements_qwen.txt
RUN python3 -m pip install -r request_llm/requirements_chatglm.txt
RUN python3 -m pip install -r request_llm/requirements_newbing.txt
# 预热Tiktoken模块
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
# 启动
CMD ["python3", "-u", "main.py"]

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@@ -1,7 +1,6 @@
# 从NVIDIA源,从而支持显卡运损检查宿主的nvidia-smi中的cuda版本必须>=11.3 # 从NVIDIA源,从而支持显卡运损检查宿主的nvidia-smi中的cuda版本必须>=11.3
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04 FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
ARG useProxyNetwork=''
RUN apt-get update RUN apt-get update
RUN apt-get install -y curl proxychains curl gcc RUN apt-get install -y curl proxychains curl gcc
RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing

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@@ -1,6 +1,6 @@
# 此Dockerfile适用于“无本地模型”的环境构建,如果需要使用chatglm等本地模型,请参考 docs/Dockerfile+ChatGLM # 此Dockerfile适用于“无本地模型”的环境构建,如果需要使用chatglm等本地模型,请参考 docs/Dockerfile+ChatGLM
# - 1 修改 `config.py` # - 1 修改 `config.py`
# - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/Dockerfile+NoLocal+Latex . # - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/GithubAction+NoLocal+Latex .
# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex # - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
FROM fuqingxu/python311_texlive_ctex:latest FROM fuqingxu/python311_texlive_ctex:latest
@@ -10,6 +10,10 @@ WORKDIR /gpt
RUN pip3 install gradio openai numpy arxiv rich RUN pip3 install gradio openai numpy arxiv rich
RUN pip3 install colorama Markdown pygments pymupdf RUN pip3 install colorama Markdown pygments pymupdf
RUN pip3 install python-docx moviepy pdfminer
RUN pip3 install zh_langchain==0.2.1
RUN pip3 install nougat-ocr
RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
# 装载项目文件 # 装载项目文件
COPY . . COPY . .

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@@ -2448,5 +2448,49 @@
"插件说明": "Plugin description", "插件说明": "Plugin description",
"├── CODE_HIGHLIGHT 代码高亮": "├── CODE_HIGHLIGHT Code highlighting", "├── CODE_HIGHLIGHT 代码高亮": "├── CODE_HIGHLIGHT Code highlighting",
"记得用插件": "Remember to use the plugin", "记得用插件": "Remember to use the plugin",
"谨慎操作": "Handle with caution" "谨慎操作": "Handle with caution",
"请检查PDF是否损坏": "#",
"执行成功了": "#",
"请在输入框内填写需求": "#",
"结果": "#",
"开始干正事": "#",
"次代码生成尝试": "#",
"代码生成结束": "#",
"Nougat解析论文失败": "#",
"受到google限制": "#",
"收尾": "#",
"结果是一个有效文件": "#",
"然后再次点击该插件": "#",
"用插件实现」": "#",
"文件路径": "#",
"仅供测试": "#",
"将csv文件转excel表格": "#",
"开始执行": "#",
"测试": "#",
"睡一会防止触发google反爬虫": "#",
"某段话的整个句子": "#",
"使用tex格式公式 测试2 给出柯西不等式": "#",
"找不到本地项目或无法处理": "#",
"交换图像的蓝色通道和红色通道": "#",
"第三步": "#",
"返回给定的url解析出的arxiv_id": "#",
"裁剪图像": "#",
"已经被记忆": "#",
"无法从bing获取信息": "#",
"可能触发了google反爬虫机制": "#",
"检索文章的历史版本的题目": "#",
"请配置讯飞星火大模型的XFYUN_APPID": "#",
"执行失败了": "#",
"需要花费较长时间下载NOUGAT参数": "#",
"请检查": "#",
"写入": "#",
"下个句子中已经说完的部分": "#",
"精准翻译PDF文档": "#",
"解析python源代码项目": "#",
"首先在arxiv上搜索": "#",
"错误追踪": "#",
"结果是一个字符串": "#",
"由 test_on_sentence_end": "#",
"获取文章摘要": "#",
"受到bing限制": "#"
} }

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@@ -88,5 +88,7 @@
"辅助功能": "Accessibility", "辅助功能": "Accessibility",
"虚空终端": "VoidTerminal", "虚空终端": "VoidTerminal",
"解析PDF_基于GROBID": "ParsePDF_BasedOnGROBID", "解析PDF_基于GROBID": "ParsePDF_BasedOnGROBID",
"虚空终端主路由": "VoidTerminalMainRoute" "虚空终端主路由": "VoidTerminalMainRoute",
"批量翻译PDF文档_NOUGAT": "BatchTranslatePDFDocuments_NOUGAT",
"解析PDF_基于NOUGAT": "ParsePDF_NOUGAT"
} }

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@@ -20,4 +20,4 @@ arxiv
rich rich
pypdf2==2.12.1 pypdf2==2.12.1
websocket-client websocket-client
scipdf_parser==0.3 scipdf_parser>=0.3

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@@ -10,8 +10,9 @@ from tests.test_utils import plugin_test
if __name__ == "__main__": if __name__ == "__main__":
# plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep') # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件,对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析') # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件,对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析')
# plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表') # plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表')

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@@ -281,8 +281,7 @@ def report_execption(chatbot, history, a, b):
向chatbot中添加错误信息 向chatbot中添加错误信息
""" """
chatbot.append((a, b)) chatbot.append((a, b))
history.append(a) history.extend([a, b])
history.append(b)
def text_divide_paragraph(text): def text_divide_paragraph(text):
@@ -305,6 +304,7 @@ def text_divide_paragraph(text):
text = "</br>".join(lines) text = "</br>".join(lines)
return pre + text + suf return pre + text + suf
@lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度 @lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度
def markdown_convertion(txt): def markdown_convertion(txt):
""" """
@@ -359,19 +359,41 @@ def markdown_convertion(txt):
content = content.replace('</script>\n</script>', '</script>') content = content.replace('</script>\n</script>', '</script>')
return content return content
def no_code(txt): def is_equation(txt):
if '```' not in txt: """
return True 判定是否为公式 | 测试1 写出洛伦兹定律,使用tex格式公式 测试2 给出柯西不等式,使用latex格式 测试3 写出麦克斯韦方程组
"""
if '```' in txt and '```reference' not in txt: return False
if '$' not in txt and '\\[' not in txt: return False
mathpatterns = {
r'(?<!\\|\$)(\$)([^\$]+)(\$)': {'allow_multi_lines': False}, #  $...$
r'(?<!\\)(\$\$)([^\$]+)(\$\$)': {'allow_multi_lines': True}, # $$...$$
r'(?<!\\)(\\\[)(.+?)(\\\])': {'allow_multi_lines': False}, # \[...\]
# r'(?<!\\)(\\\()(.+?)(\\\))': {'allow_multi_lines': False}, # \(...\)
# r'(?<!\\)(\\begin{([a-z]+?\*?)})(.+?)(\\end{\2})': {'allow_multi_lines': True}, # \begin...\end
# r'(?<!\\)(\$`)([^`]+)(`\$)': {'allow_multi_lines': False}, # $`...`$
}
matches = []
for pattern, property in mathpatterns.items():
flags = re.ASCII|re.DOTALL if property['allow_multi_lines'] else re.ASCII
matches.extend(re.findall(pattern, txt, flags))
if len(matches) == 0: return False
contain_any_eq = False
illegal_pattern = re.compile(r'[^\x00-\x7F]|echo')
for match in matches:
if len(match) != 3: return False
eq_canidate = match[1]
if illegal_pattern.search(eq_canidate):
return False
else: else:
if '```reference' in txt: return True # newbing contain_any_eq = True
else: return False return contain_any_eq
if ('$' in txt) and no_code(txt): # 有$标识的公式符号,且没有代码段```的标识 if is_equation(txt): # 有$标识的公式符号,且没有代码段```的标识
# convert everything to html format # convert everything to html format
split = markdown.markdown(text='---') split = markdown.markdown(text='---')
convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs) convert_stage_1 = markdown.markdown(text=txt, extensions=['sane_lists', 'tables', 'mdx_math', 'fenced_code'], extension_configs=markdown_extension_configs)
convert_stage_1 = markdown_bug_hunt(convert_stage_1) convert_stage_1 = markdown_bug_hunt(convert_stage_1)
# re.DOTALL: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline. Corresponds to the inline flag (?s).
# 1. convert to easy-to-copy tex (do not render math) # 1. convert to easy-to-copy tex (do not render math)
convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL) convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
# 2. convert to rendered equation # 2. convert to rendered equation
@@ -379,7 +401,7 @@ def markdown_convertion(txt):
# cat them together # cat them together
return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf
else: else:
return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf return pre + markdown.markdown(txt, extensions=['sane_lists', 'tables', 'fenced_code', 'codehilite']) + suf
def close_up_code_segment_during_stream(gpt_reply): def close_up_code_segment_during_stream(gpt_reply):
@@ -561,7 +583,7 @@ def on_file_uploaded(files, chatbot, txt, txt2, checkboxes, cookies):
chatbot.append(['我上传了文件,请查收', chatbot.append(['我上传了文件,请查收',
f'[Local Message] 收到以下文件: \n\n{moved_files_str}' + f'[Local Message] 收到以下文件: \n\n{moved_files_str}' +
f'\n\n调用路径参数已自动修正到: \n\n{txt}' + f'\n\n调用路径参数已自动修正到: \n\n{txt}' +
f'\n\n现在您点击任意“红颜色”标识的函数插件时,以上文件将被作为输入参数'+err_msg]) f'\n\n现在您点击任意函数插件时,以上文件将被作为输入参数'+err_msg])
cookies.update({ cookies.update({
'most_recent_uploaded': { 'most_recent_uploaded': {
'path': f'private_upload/{time_tag}', 'path': f'private_upload/{time_tag}',