比较提交

..

10 次代码提交

作者 SHA1 备注 提交日期
binary-husky
790a1cf12a 添加一些提示 2023-06-11 20:12:25 +08:00
binary-husky
3ecf2977a8 修复caption翻译 2023-06-11 18:23:54 +08:00
binary-husky
aeddf6b461 Update Latex输出PDF结果.py 2023-06-11 10:20:49 +08:00
binary-husky
3c00e7a143 file link in chatbot 2023-06-10 21:45:38 +08:00
binary-husky
ef1bfdd60f update pip install notice 2023-06-08 21:29:10 +08:00
qingxu fu
e48d92e82e update translation 2023-06-08 18:34:06 +08:00
binary-husky
110510997f Update README.md 2023-06-08 12:48:52 +08:00
binary-husky
b52695845e Update README.md 2023-06-08 12:44:05 +08:00
binary-husky
f30c9c6d3b Update README.md 2023-06-08 12:43:13 +08:00
binary-husky
ff5403eac6 Update README.md 2023-06-08 12:42:24 +08:00
共有 6 个文件被更改,包括 101 次插入46 次删除

查看文件

@@ -43,7 +43,7 @@ chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
[Arxiv小助手](https://www.bilibili.com/video/BV1LM4y1279X) | [函数插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
[谷歌学术统合小助手](https://www.bilibili.com/video/BV19L411U7ia) | [函数插件] 给定任意谷歌学术搜索页面URL,让gpt帮你[写relatedworks](https://www.bilibili.com/video/BV1GP411U7Az/)
互联网信息聚合+GPT | [函数插件] 一键[让GPT先从互联网获取信息](https://www.bilibili.com/video/BV1om4y127ck),再回答问题,让信息永不过时
Arxiv论文精翻译 | [函数插件] 一键[以超高质量翻译arxiv论文](https://www.bilibili.com/video/BV1dz4y1v77A/),迄今为止最好的论文翻译工具
Arxiv论文精翻译 | [函数插件] 一键[以超高质量翻译arxiv论文](https://www.bilibili.com/video/BV1dz4y1v77A/),迄今为止最好的论文翻译工具
公式/图片/表格显示 | 可以同时显示公式的[tex形式和渲染形式](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png),支持公式、代码高亮
多线程函数插件支持 | 支持多线调用chatgpt,一键处理[海量文本](https://www.bilibili.com/video/BV1FT411H7c5/)或程序
启动暗色gradio[主题](https://github.com/binary-husky/chatgpt_academic/issues/173) | 在浏览器url后面添加```/?__theme=dark```可以切换dark主题
@@ -233,66 +233,62 @@ 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
<img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
</div>
2. 生成报告。大部分插件都会在执行结束后,生成工作报告
2. ⭐Latex/Arxiv论文翻译功能⭐
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/227503770-fe29ce2c-53fd-47b0-b0ff-93805f0c2ff4.png" height="300" >
<img src="https://user-images.githubusercontent.com/96192199/227504617-7a497bb3-0a2a-4b50-9a8a-95ae60ea7afd.png" height="300" >
<img src="https://user-images.githubusercontent.com/96192199/227504005-efeaefe0-b687-49d0-bf95-2d7b7e66c348.png" height="300" >
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/002a1a75-ace0-4e6a-94e2-ec1406a746f1" height="250" > ===>
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/9fdcc391-f823-464f-9322-f8719677043b" height="250" >
</div>
3. 模块化功能设计,简单的接口却能支持强大的功能
3. 生成报告。大部分插件都会在执行结束后,生成工作报告
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/227503770-fe29ce2c-53fd-47b0-b0ff-93805f0c2ff4.png" height="250" >
<img src="https://user-images.githubusercontent.com/96192199/227504617-7a497bb3-0a2a-4b50-9a8a-95ae60ea7afd.png" height="250" >
</div>
4. 模块化功能设计,简单的接口却能支持强大的功能
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/229288270-093643c1-0018-487a-81e6-1d7809b6e90f.png" height="400" >
<img src="https://user-images.githubusercontent.com/96192199/227504931-19955f78-45cd-4d1c-adac-e71e50957915.png" height="400" >
</div>
4. 这是一个能够“自我译解”的开源项目
5. 这是一个能够“自我译解”的开源项目
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/226936850-c77d7183-0749-4c1c-9875-fd4891842d0c.png" width="500" >
</div>
5. 译解其他开源项目,不在话下
6. 译解其他开源项目,不在话下
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" width="500" >
<img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" height="250" >
<img src="https://user-images.githubusercontent.com/96192199/226969067-968a27c1-1b9c-486b-8b81-ab2de8d3f88a.png" height="250" >
</div>
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/226969067-968a27c1-1b9c-486b-8b81-ab2de8d3f88a.png" width="500" >
</div>
6. 装饰[live2d](https://github.com/fghrsh/live2d_demo)的小功能(默认关闭,需要修改`config.py`
7. 装饰[live2d](https://github.com/fghrsh/live2d_demo)的小功能(默认关闭,需要修改`config.py`
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/236432361-67739153-73e8-43fe-8111-b61296edabd9.png" width="500" >
</div>
7. 新增MOSS大语言模型支持
8. 新增MOSS大语言模型支持
<div align="center">
<img src="https://user-images.githubusercontent.com/96192199/236639178-92836f37-13af-4fdd-984d-b4450fe30336.png" width="500" >
</div>
8. OpenAI图像生成
9. OpenAI图像生成
<div align="center">
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/bc7ab234-ad90-48a0-8d62-f703d9e74665" width="500" >
</div>
9. OpenAI音频解析与总结
10. OpenAI音频解析与总结
<div align="center">
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/709ccf95-3aee-498a-934a-e1c22d3d5d5b" width="500" >
</div>
10. Latex全文校对纠错
11. Latex全文校对纠错
<div align="center">
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/651ccd98-02c9-4464-91e1-77a6b7d1b033" height="250" > ===>
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/476f66d9-7716-4537-b5c1-735372c25adb" height="250">
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/651ccd98-02c9-4464-91e1-77a6b7d1b033" height="200" > ===>
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/476f66d9-7716-4537-b5c1-735372c25adb" height="200">
</div>
10. Latex/Arxiv论文翻译功能
<div align="center">
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/002a1a75-ace0-4e6a-94e2-ec1406a746f1" height="250" >
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/9fdcc391-f823-464f-9322-f8719677043b" height="250" >
</div>
## 版本:
- version 3.5(Todo): 使用自然语言调用本项目的所有函数插件(高优先级)

查看文件

@@ -146,7 +146,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
from .latex_utils 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。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
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
@@ -216,7 +216,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
from .latex_utils 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。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
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

查看文件

@@ -23,13 +23,38 @@ def split_worker(text, mask, pattern, flags=0):
mask[res.span()[0]:res.span()[1]] = PRESERVE
return text, mask
def split_worker_reverse_caption(text, mask, pattern, flags=0):
def split_worker_careful_brace(text, mask, pattern, flags=0):
"""
Move caption area out of preserve area
Move area into preserve area
"""
pattern_compile = re.compile(pattern, flags)
for res in pattern_compile.finditer(text):
mask[res.regs[1][0]:res.regs[1][1]] = TRANSFORM
brace_level = -1
p = begin = end = res.regs[0][0]
for _ in range(1024*16):
if text[p] == '}' and brace_level == 0: break
elif text[p] == '}': brace_level -= 1
elif text[p] == '{': brace_level += 1
p += 1
end = p+1
mask[begin:end] = PRESERVE
return text, mask
def split_worker_reverse_careful_brace(text, mask, pattern, flags=0):
"""
Move area out of preserve area
"""
pattern_compile = re.compile(pattern, flags)
for res in pattern_compile.finditer(text):
brace_level = 0
p = begin = end = res.regs[1][0]
for _ in range(1024*16):
if text[p] == '}' and brace_level == 0: break
elif text[p] == '}': brace_level -= 1
elif text[p] == '{': brace_level += 1
p += 1
end = p
mask[begin:end] = TRANSFORM
return text, mask
def split_worker_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
@@ -97,6 +122,7 @@ def 寻找Latex主文件(file_manifest, mode):
else:
continue
raise RuntimeError('无法找到一个主Tex文件包含documentclass关键字')
def rm_comments(main_file):
new_file_remove_comment_lines = []
for l in main_file.splitlines():
@@ -108,6 +134,7 @@ def rm_comments(main_file):
main_file = '\n'.join(new_file_remove_comment_lines)
main_file = re.sub(r'(?<!\\)%.*', '', main_file) # 使用正则表达式查找半行注释, 并替换为空字符串
return main_file
def merge_tex_files_(project_foler, main_file, mode):
"""
Merge Tex project recrusively
@@ -185,14 +212,39 @@ def fix_content(final_tex, node_string):
if node_string.count('\_') > 0 and node_string.count('\_') > final_tex.count('\_'):
# walk and replace any _ without \
final_tex = re.sub(r"(?<!\\)_", "\\_", final_tex)
if node_string.count('{') != node_string.count('}'):
if final_tex.count('{') != node_string.count('{'):
final_tex = node_string # 出问题了,还原原文
if final_tex.count('}') != node_string.count('}'):
final_tex = node_string # 出问题了,还原原文
def compute_brace_level(string):
# this function count the number of { and }
brace_level = 0
for c in string:
if c == "{": brace_level += 1
elif c == "}": brace_level -= 1
return brace_level
def join_most(tex_t, tex_o):
# this function join translated string and original string when something goes wrong
p_t = 0
p_o = 0
def find_next(string, chars, begin):
p = begin
while p < len(string):
if string[p] in chars: return p, string[p]
p += 1
return None, None
while True:
res1, char = find_next(tex_o, ['{','}'], p_o)
if res1 is None: break
res2, char = find_next(tex_t, [char], p_t)
if res2 is None: break
p_o = res1 + 1
p_t = res2 + 1
return tex_t[:p_t] + tex_o[p_o:]
if compute_brace_level(final_tex) != compute_brace_level(node_string):
# 出问题了,还原部分原文,保证括号正确
final_tex = join_most(final_tex, node_string)
return final_tex
def split_subprocess(txt, project_folder, return_dict):
def split_subprocess(txt, project_folder, return_dict, opts):
"""
break down latex file to a linked list,
each node use a preserve flag to indicate whether it should
@@ -239,7 +291,8 @@ def split_subprocess(txt, project_folder, return_dict):
text, mask = split_worker(text, mask, r"\\vspace\{(.*?)\}")
text, mask = split_worker(text, mask, r"\\hspace\{(.*?)\}")
text, mask = split_worker(text, mask, r"\\end\{(.*?)\}")
# text, mask = split_worker_reverse_caption(text, mask, r"\\caption\{(.*?)\}", re.DOTALL)
text, mask = split_worker_careful_brace(text, mask, r"\\hl\{(.*?)\}", re.DOTALL)
text, mask = split_worker_reverse_careful_brace(text, mask, r"\\caption\{(.*?)\}", re.DOTALL)
root = convert_to_linklist(text, mask)
# 修复括号
@@ -369,7 +422,7 @@ class LatexPaperSplit():
result_string = result_string[:position] + self.msg + msg + self.msg_declare + result_string[position:]
return result_string
def split(self, txt, project_folder):
def split(self, txt, project_folder, opts):
"""
break down latex file to a linked list,
each node use a preserve flag to indicate whether it should
@@ -381,7 +434,7 @@ class LatexPaperSplit():
return_dict = manager.dict()
p = multiprocessing.Process(
target=split_subprocess,
args=(txt, project_folder, return_dict))
args=(txt, project_folder, return_dict, opts))
p.start()
p.join()
self.nodes = return_dict['nodes']
@@ -440,7 +493,7 @@ class LatexPaperFileGroup():
def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread', switch_prompt=None):
def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread', switch_prompt=None, opts=[]):
import time, os, re
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
from .latex_utils import LatexPaperFileGroup, merge_tex_files, LatexPaperSplit, 寻找Latex主文件
@@ -469,8 +522,10 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
f.write(merged_content)
# <-------- 精细切分latex文件 ---------->
chatbot.append((f"Latex文件融合完成", f'[Local Message] 正在精细切分latex文件,这需要一段时间计算,文档越长耗时越长,请耐心等待。'))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
lps = LatexPaperSplit()
res = lps.split(merged_content, project_folder) # 消耗时间的函数
res = lps.split(merged_content, project_folder, opts) # 消耗时间的函数
# <-------- 拆分过长的latex片段 ---------->
pfg = LatexPaperFileGroup()
@@ -567,7 +622,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
current_dir = os.getcwd()
n_fix = 1
max_try = 32
chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder},如果程序停顿5分钟以上,则大概率是卡死在Latex里面了。不幸卡死时请直接去该路径下取回翻译结果,或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder},如果程序停顿5分钟以上,请直接去该路径下取回翻译结果,或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
yield from update_ui_lastest_msg('编译已经开始...', chatbot, history) # 刷新Gradio前端界面

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@@ -8,7 +8,7 @@ def inspect_dependency(chatbot, history):
import manim
return True
except:
chatbot.append(["导入依赖失败", "使用该模块需要额外依赖,安装方法:```pip install manimgl```"])
chatbot.append(["导入依赖失败", "使用该模块需要额外依赖,安装方法:```pip install manim manimgl```"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return False

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@@ -58,6 +58,8 @@
"连接网络回答问题": "ConnectToNetworkToAnswerQuestions",
"联网的ChatGPT": "ChatGPTConnectedToNetwork",
"解析任意code项目": "ParseAnyCodeProject",
"读取知识库作答": "ReadKnowledgeArchiveAnswerQuestions",
"知识库问答": "UpdateKnowledgeArchive",
"同时问询_指定模型": "InquireSimultaneously_SpecifiedModel",
"图片生成": "ImageGeneration",
"test_解析ipynb文件": "Test_ParseIpynbFile",

查看文件

@@ -483,7 +483,9 @@ def on_report_generated(files, chatbot):
if len(report_files) == 0:
return None, chatbot
# files.extend(report_files)
chatbot.append(['报告如何远程获取?', '报告已经添加到右侧“文件上传区”(可能处于折叠状态),请查收。'])
file_links = ''
for f in report_files: file_links += f'<br/><a href="file={os.path.abspath(f)}" target="_blank">{f}</a>'
chatbot.append(['报告如何远程获取?', f'报告已经添加到右侧“文件上传区”(可能处于折叠状态),请查收。{file_links}'])
return report_files, chatbot
def is_openai_api_key(key):