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7 Commits

Author SHA1 Message Date
binary-husky
d2dd5d3eb1 construct idea 2024-11-11 15:35:01 +00:00
binary-husky
d152f62894 renamed plugins 2024-11-11 14:55:05 +00:00
binary-husky
197287fc30 Enhance archive extraction with error handling for tar and gzip formats 2024-11-09 10:10:46 +00:00
Bingchen Jiang
c37fcc9299 Adding support to new openai apikey format (#2030) 2024-11-09 13:41:19 +08:00
binary-husky
91f5e6b8f7 resolve pickle security issue 2024-11-04 13:49:49 +00:00
hcy2206
4f0851f703 增加了对于glm-4-plus的支持 (#2014)
* 增加对于讯飞星火大模型Spark4.0的支持

* Create github action sync.yml

* 增加对于智谱glm-4-plus的支持

* feat: change arxiv io param

* catch comment source code exception

* upgrade auto comment

* add security patch

---------

Co-authored-by: GH Action - Upstream Sync <action@github.com>
Co-authored-by: binary-husky <qingxu.fu@outlook.com>
2024-11-03 22:41:16 +08:00
binary-husky
2821f27756 add security patch 2024-11-03 14:34:17 +00:00
18 changed files with 301 additions and 1209 deletions

4
.gitignore vendored
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@@ -160,4 +160,6 @@ test.*
temp.*
objdump*
*.min.*.js
TODO
TODO
experimental_mods
search_results

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@@ -17,24 +17,24 @@ def get_crazy_functions():
from crazy_functions.SourceCode_Analyse import 解析一个前端项目
from crazy_functions.高级功能函数模板 import 高阶功能模板函数
from crazy_functions.高级功能函数模板 import Demo_Wrap
from crazy_functions.Latex全文润色 import Latex英文润色
from crazy_functions.Latex_Project_Polish import Latex英文润色
from crazy_functions.询问多个大语言模型 import 同时问询
from crazy_functions.SourceCode_Analyse import 解析一个Lua项目
from crazy_functions.SourceCode_Analyse import 解析一个CSharp项目
from crazy_functions.总结word文档 import 总结word文档
from crazy_functions.解析JupyterNotebook import 解析ipynb文件
from crazy_functions.Conversation_To_File import 载入对话历史存档
from crazy_functions.Conversation_To_File import 对话历史存档
from crazy_functions.Conversation_To_File import Conversation_To_File_Wrap
from crazy_functions.Conversation_To_File import 删除所有本地对话历史记录
from crazy_functions.辅助功能 import 清除缓存
from crazy_functions.批量文件询问 import 批量文件询问
from crazy_functions.Markdown_Translate import Markdown英译中
from crazy_functions.批量总结PDF文档 import 批量总结PDF文档
from crazy_functions.PDF_Translate import 批量翻译PDF文档
from crazy_functions.谷歌检索小助手 import 谷歌检索小助手
from crazy_functions.理解PDF文档内容 import 理解PDF文档内容标准文件输入
from crazy_functions.Latex全文润色 import Latex中文润色
from crazy_functions.Latex全文润色 import Latex英文纠错
from crazy_functions.Latex_Project_Polish import Latex中文润色
from crazy_functions.Latex_Project_Polish import Latex英文纠错
from crazy_functions.Markdown_Translate import Markdown中译英
from crazy_functions.虚空终端 import 虚空终端
from crazy_functions.生成多种Mermaid图表 import Mermaid_Gen
@@ -110,13 +110,12 @@ def get_crazy_functions():
"Function": HotReload(Latex翻译中文并重新编译PDF), # 当注册Class后Function旧接口仅会在“虚空终端”中起作用
"Class": Arxiv_Localize, # 新一代插件需要注册Class
},
"批量文件询问": {
"批量总结Word文档": {
"Group": "学术",
"Color": "stop",
"AsButton": False,
"AdvancedArgs": True,
"Info": "通过在高级参数区写入prompt可自定义询问逻辑默认情况下为总结逻辑 | 输入参数为路径",
"Function": HotReload(批量文件询问),
"Info": "批量总结word文档 | 输入参数为路径",
"Function": HotReload(总结word文档),
},
"解析整个Matlab项目": {
"Group": "编程",
@@ -741,19 +740,6 @@ def get_crazy_functions():
# logger.error(trimmed_format_exc())
# print('Load function plugin failed')
# try:
# from crazy_functions.chatglm微调工具 import 微调数据集生成
# function_plugins.update({
# "黑盒模型学习: 微调数据集生成 (先上传数据集)": {
# "Color": "stop",
# "AsButton": False,
# "AdvancedArgs": True,
# "ArgsReminder": "针对数据集输入(如 绿帽子*深蓝色衬衫*黑色运动裤)给出指令,例如您可以将以下命令复制到下方: --llm_to_learn=azure-gpt-3.5 --prompt_prefix='根据下面的服装类型提示想象一个穿着者对这个人外貌、身处的环境、内心世界、过去经历进行描写。要求100字以内用第二人称。' --system_prompt=''",
# "Function": HotReload(微调数据集生成)
# }
# })
# except:
# print('Load function plugin failed')
"""
设置默认值:

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@@ -0,0 +1,62 @@
from toolbox import get_conf, update_ui
from crazy_functions.Image_Generate import 图片生成_DALLE2, 图片生成_DALLE3, 图片修改_DALLE2
from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
def update_js_plugin_info():
# encode_plugin_info
...
class ImageGen_Wrap(GptAcademicPluginTemplate):
def __init__(self):
"""
请注意`execute`会执行在不同的线程中,因此您在定义和使用类变量时,应当慎之又慎!
"""
pass
def define_arg_selection_menu(self):
"""
定义插件的二级选项菜单
第一个参数,名称`main_input`,参数`type`声明这是一个文本框,文本框上方显示`title`,文本框内部显示`description``default_value`为默认值;
第二个参数,名称`advanced_arg`,参数`type`声明这是一个文本框,文本框上方显示`title`,文本框内部显示`description``default_value`为默认值;
"""
gui_definition = {
"main_input":
ArgProperty(title="输入图片描述", description="需要生成图像的文本描述,尽量使用英文", default_value="", type="string").model_dump_json(), # 主输入,自动从输入框同步
"model_name":
ArgProperty(title="模型", options=["DALLE2", "DALLE3"], default_value="DALLE3", description="", type="dropdown").model_dump_json(),
"resolution":
ArgProperty(title="分辨率", options=["256x256(限DALLE2)", "512x512(限DALLE2)", "1024x1024", "1792x1024(限DALLE3)", "1024x1792(限DALLE3)"], default_value="1024x1024", description="", type="dropdown").model_dump_json(),
"quality (仅DALLE3生效)":
ArgProperty(title="质量", options=["standard", "hd"], default_value="standard", description="", type="dropdown").model_dump_json(),
"style (仅DALLE3生效)":
ArgProperty(title="风格", options=["vivid", "natural"], default_value="vivid", description="", type="dropdown").model_dump_json(),
}
return gui_definition
def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
"""
执行插件
"""
# 分辨率
resolution = plugin_kwargs["resolution"].replace("(限DALLE2)", "").replace("(限DALLE3)", "")
if plugin_kwargs["model_name"] == "DALLE2":
plugin_kwargs["advanced_arg"] = resolution
yield from 图片生成_DALLE2(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
elif plugin_kwargs["model_name"] == "DALLE3":
quality = plugin_kwargs["quality (仅DALLE3生效)"]
style = plugin_kwargs["style (仅DALLE3生效)"]
plugin_kwargs["advanced_arg"] = f"{resolution}-{quality}-{style}"
yield from 图片生成_DALLE3(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
else:
chatbot.append([None, "抱歉,找不到该模型"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

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@@ -1,141 +0,0 @@
from toolbox import CatchException, update_ui, promote_file_to_downloadzone
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
import datetime, json
def fetch_items(list_of_items, batch_size):
for i in range(0, len(list_of_items), batch_size):
yield list_of_items[i:i + batch_size]
def string_to_options(arguments):
import argparse
import shlex
# Create an argparse.ArgumentParser instance
parser = argparse.ArgumentParser()
# Add command-line arguments
parser.add_argument("--llm_to_learn", type=str, help="LLM model to learn", default="gpt-3.5-turbo")
parser.add_argument("--prompt_prefix", type=str, help="Prompt prefix", default='')
parser.add_argument("--system_prompt", type=str, help="System prompt", default='')
parser.add_argument("--batch", type=int, help="System prompt", default=50)
parser.add_argument("--pre_seq_len", type=int, help="pre_seq_len", default=50)
parser.add_argument("--learning_rate", type=float, help="learning_rate", default=2e-2)
parser.add_argument("--num_gpus", type=int, help="num_gpus", default=1)
parser.add_argument("--json_dataset", type=str, help="json_dataset", default="")
parser.add_argument("--ptuning_directory", type=str, help="ptuning_directory", default="")
# Parse the arguments
args = parser.parse_args(shlex.split(arguments))
return args
@CatchException
def 微调数据集生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
"""
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
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
user_request 当前用户的请求信息IP地址等
"""
history = [] # 清空历史,以免输入溢出
chatbot.append(("这是什么功能?", "[Local Message] 微调数据集生成"))
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
args = plugin_kwargs.get("advanced_arg", None)
if args is None:
chatbot.append(("没给定指令", "退出"))
yield from update_ui(chatbot=chatbot, history=history); return
else:
arguments = string_to_options(arguments=args)
dat = []
with open(txt, 'r', encoding='utf8') as f:
for line in f.readlines():
json_dat = json.loads(line)
dat.append(json_dat["content"])
llm_kwargs['llm_model'] = arguments.llm_to_learn
for batch in fetch_items(dat, arguments.batch):
res = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
inputs_array=[f"{arguments.prompt_prefix}\n\n{b}" for b in (batch)],
inputs_show_user_array=[f"Show Nothing" for _ in (batch)],
llm_kwargs=llm_kwargs,
chatbot=chatbot,
history_array=[[] for _ in (batch)],
sys_prompt_array=[arguments.system_prompt for _ in (batch)],
max_workers=10 # OpenAI所允许的最大并行过载
)
with open(txt+'.generated.json', 'a+', encoding='utf8') as f:
for b, r in zip(batch, res[1::2]):
f.write(json.dumps({"content":b, "summary":r}, ensure_ascii=False)+'\n')
promote_file_to_downloadzone(txt+'.generated.json', rename_file='generated.json', chatbot=chatbot)
return
@CatchException
def 启动微调(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
"""
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
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
user_request 当前用户的请求信息IP地址等
"""
import subprocess
history = [] # 清空历史,以免输入溢出
chatbot.append(("这是什么功能?", "[Local Message] 微调数据集生成"))
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
args = plugin_kwargs.get("advanced_arg", None)
if args is None:
chatbot.append(("没给定指令", "退出"))
yield from update_ui(chatbot=chatbot, history=history); return
else:
arguments = string_to_options(arguments=args)
pre_seq_len = arguments.pre_seq_len # 128
learning_rate = arguments.learning_rate # 2e-2
num_gpus = arguments.num_gpus # 1
json_dataset = arguments.json_dataset # 't_code.json'
ptuning_directory = arguments.ptuning_directory # '/home/hmp/ChatGLM2-6B/ptuning'
command = f"torchrun --standalone --nnodes=1 --nproc-per-node={num_gpus} main.py \
--do_train \
--train_file AdvertiseGen/{json_dataset} \
--validation_file AdvertiseGen/{json_dataset} \
--preprocessing_num_workers 20 \
--prompt_column content \
--response_column summary \
--overwrite_cache \
--model_name_or_path THUDM/chatglm2-6b \
--output_dir output/clothgen-chatglm2-6b-pt-{pre_seq_len}-{learning_rate} \
--overwrite_output_dir \
--max_source_length 256 \
--max_target_length 256 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 16 \
--predict_with_generate \
--max_steps 100 \
--logging_steps 10 \
--save_steps 20 \
--learning_rate {learning_rate} \
--pre_seq_len {pre_seq_len} \
--quantization_bit 4"
process = subprocess.Popen(command, shell=True, cwd=ptuning_directory)
try:
process.communicate(timeout=3600*24)
except subprocess.TimeoutExpired:
process.kill()
return

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@@ -1,450 +0,0 @@
import os
import time
from abc import ABC, abstractmethod
from datetime import datetime
from docx import Document
from docx.enum.style import WD_STYLE_TYPE
from docx.enum.text import WD_PARAGRAPH_ALIGNMENT, WD_LINE_SPACING
from docx.oxml.ns import qn
from docx.shared import Inches, Cm
from docx.shared import Pt, RGBColor, Inches
from typing import Dict, List, Tuple
class DocumentFormatter(ABC):
"""文档格式化基类,定义文档格式化的基本接口"""
def __init__(self, final_summary: str, file_summaries_map: Dict, failed_files: List[Tuple]):
self.final_summary = final_summary
self.file_summaries_map = file_summaries_map
self.failed_files = failed_files
@abstractmethod
def format_failed_files(self) -> str:
"""格式化失败文件列表"""
pass
@abstractmethod
def format_file_summaries(self) -> str:
"""格式化文件总结内容"""
pass
@abstractmethod
def create_document(self) -> str:
"""创建完整文档"""
pass
class WordFormatter(DocumentFormatter):
"""Word格式文档生成器 - 符合中国政府公文格式规范(GB/T 9704-2012),并进行了优化"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.doc = Document()
self._setup_document()
self._create_styles()
# 初始化三级标题编号系统
self.numbers = {
1: 0, # 一级标题编号
2: 0, # 二级标题编号
3: 0 # 三级标题编号
}
def _setup_document(self):
"""设置文档基本格式,包括页面设置和页眉"""
sections = self.doc.sections
for section in sections:
# 设置页面大小为A4
section.page_width = Cm(21)
section.page_height = Cm(29.7)
# 设置页边距
section.top_margin = Cm(3.7) # 上边距37mm
section.bottom_margin = Cm(3.5) # 下边距35mm
section.left_margin = Cm(2.8) # 左边距28mm
section.right_margin = Cm(2.6) # 右边距26mm
# 设置页眉页脚距离
section.header_distance = Cm(2.0)
section.footer_distance = Cm(2.0)
# 添加页眉
header = section.header
header_para = header.paragraphs[0]
header_para.alignment = WD_PARAGRAPH_ALIGNMENT.RIGHT
header_run = header_para.add_run("该文档由GPT-academic生成")
header_run.font.name = '仿宋'
header_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
header_run.font.size = Pt(9)
def _create_styles(self):
"""创建文档样式"""
# 创建正文样式
style = self.doc.styles.add_style('Normal_Custom', WD_STYLE_TYPE.PARAGRAPH)
style.font.name = '仿宋'
style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
style.font.size = Pt(14)
style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
style.paragraph_format.space_after = Pt(0)
style.paragraph_format.first_line_indent = Pt(28)
# 创建各级标题样式
self._create_heading_style('Title_Custom', '方正小标宋简体', 32, WD_PARAGRAPH_ALIGNMENT.CENTER)
self._create_heading_style('Heading1_Custom', '黑体', 22, WD_PARAGRAPH_ALIGNMENT.LEFT)
self._create_heading_style('Heading2_Custom', '黑体', 18, WD_PARAGRAPH_ALIGNMENT.LEFT)
self._create_heading_style('Heading3_Custom', '黑体', 16, WD_PARAGRAPH_ALIGNMENT.LEFT)
def _create_heading_style(self, style_name: str, font_name: str, font_size: int, alignment):
"""创建标题样式"""
style = self.doc.styles.add_style(style_name, WD_STYLE_TYPE.PARAGRAPH)
style.font.name = font_name
style._element.rPr.rFonts.set(qn('w:eastAsia'), font_name)
style.font.size = Pt(font_size)
style.font.bold = True
style.paragraph_format.alignment = alignment
style.paragraph_format.space_before = Pt(12)
style.paragraph_format.space_after = Pt(12)
style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
return style
def _get_heading_number(self, level: int) -> str:
"""
生成标题编号
Args:
level: 标题级别 (0-3)
Returns:
str: 格式化的标题编号
"""
if level == 0: # 主标题不需要编号
return ""
self.numbers[level] += 1 # 增加当前级别的编号
# 重置下级标题编号
for i in range(level + 1, 4):
self.numbers[i] = 0
# 根据级别返回不同格式的编号
if level == 1:
return f"{self.numbers[1]}. "
elif level == 2:
return f"{self.numbers[1]}.{self.numbers[2]} "
elif level == 3:
return f"{self.numbers[1]}.{self.numbers[2]}.{self.numbers[3]} "
return ""
def _add_heading(self, text: str, level: int):
"""
添加带编号的标题
Args:
text: 标题文本
level: 标题级别 (0-3)
"""
style_map = {
0: 'Title_Custom',
1: 'Heading1_Custom',
2: 'Heading2_Custom',
3: 'Heading3_Custom'
}
number = self._get_heading_number(level)
paragraph = self.doc.add_paragraph(style=style_map[level])
if number:
number_run = paragraph.add_run(number)
font_size = 22 if level == 1 else (18 if level == 2 else 16)
self._get_run_style(number_run, '黑体', font_size, True)
text_run = paragraph.add_run(text)
font_size = 32 if level == 0 else (22 if level == 1 else (18 if level == 2 else 16))
self._get_run_style(text_run, '黑体', font_size, True)
# 主标题添加日期
if level == 0:
date_paragraph = self.doc.add_paragraph()
date_paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
date_run = date_paragraph.add_run(datetime.now().strftime('%Y年%m月%d'))
self._get_run_style(date_run, '仿宋', 16, False)
return paragraph
def _get_run_style(self, run, font_name: str, font_size: int, bold: bool = False):
"""设置文本运行对象的样式"""
run.font.name = font_name
run._element.rPr.rFonts.set(qn('w:eastAsia'), font_name)
run.font.size = Pt(font_size)
run.font.bold = bold
def format_failed_files(self) -> str:
"""格式化失败文件列表"""
result = []
if not self.failed_files:
return "\n".join(result)
result.append("处理失败文件:")
for fp, reason in self.failed_files:
result.append(f"{os.path.basename(fp)}: {reason}")
self._add_heading("处理失败文件", 1)
for fp, reason in self.failed_files:
self._add_content(f"{os.path.basename(fp)}: {reason}", indent=False)
self.doc.add_paragraph()
return "\n".join(result)
def _add_content(self, text: str, indent: bool = True):
"""添加正文内容"""
paragraph = self.doc.add_paragraph(text, style='Normal_Custom')
if not indent:
paragraph.paragraph_format.first_line_indent = Pt(0)
return paragraph
def format_file_summaries(self) -> str:
"""
格式化文件总结内容,确保正确的标题层级
返回:
str: 格式化后的文件总结字符串
标题层级规则:
1. 一级标题为"各文件详细总结"
2. 如果文件有目录路径:
- 目录路径作为二级标题 (2.1, 2.2 等)
- 该目录下所有文件作为三级标题 (2.1.1, 2.1.2 等)
3. 如果文件没有目录路径:
- 文件直接作为二级标题 (2.1, 2.2 等)
"""
result = []
# 首先对文件路径进行分组整理
file_groups = {}
for path in sorted(self.file_summaries_map.keys()):
dir_path = os.path.dirname(path)
if dir_path not in file_groups:
file_groups[dir_path] = []
file_groups[dir_path].append(path)
# 处理没有目录的文件
root_files = file_groups.get("", [])
if root_files:
for path in sorted(root_files):
file_name = os.path.basename(path)
result.append(f"\n📄 {file_name}")
result.append(self.file_summaries_map[path])
# 无目录的文件作为二级标题
self._add_heading(f"📄 {file_name}", 2)
self._add_content(self.file_summaries_map[path])
self.doc.add_paragraph()
# 处理有目录的文件
for dir_path in sorted(file_groups.keys()):
if dir_path == "": # 跳过已处理的根目录文件
continue
# 添加目录作为二级标题
result.append(f"\n📁 {dir_path}")
self._add_heading(f"📁 {dir_path}", 2)
# 该目录下的所有文件作为三级标题
for path in sorted(file_groups[dir_path]):
file_name = os.path.basename(path)
result.append(f"\n📄 {file_name}")
result.append(self.file_summaries_map[path])
# 添加文件名作为三级标题
self._add_heading(f"📄 {file_name}", 3)
self._add_content(self.file_summaries_map[path])
self.doc.add_paragraph()
return "\n".join(result)
def create_document(self):
"""创建完整Word文档并返回文档对象"""
# 重置所有编号
for level in self.numbers:
self.numbers[level] = 0
# 添加主标题
self._add_heading("文档总结报告", 0)
self.doc.add_paragraph()
# 添加总体摘要
self._add_heading("总体摘要", 1)
self._add_content(self.final_summary)
self.doc.add_paragraph()
# 添加失败文件列表(如果有)
if self.failed_files:
self.format_failed_files()
# 添加文件详细总结
self._add_heading("各文件详细总结", 1)
self.format_file_summaries()
return self.doc
class MarkdownFormatter(DocumentFormatter):
"""Markdown格式文档生成器"""
def format_failed_files(self) -> str:
if not self.failed_files:
return ""
formatted_text = ["\n## ⚠️ 处理失败的文件"]
for fp, reason in self.failed_files:
formatted_text.append(f"- {os.path.basename(fp)}: {reason}")
formatted_text.append("\n---")
return "\n".join(formatted_text)
def format_file_summaries(self) -> str:
formatted_text = []
sorted_paths = sorted(self.file_summaries_map.keys())
current_dir = ""
for path in sorted_paths:
dir_path = os.path.dirname(path)
if dir_path != current_dir:
if dir_path:
formatted_text.append(f"\n## 📁 {dir_path}")
current_dir = dir_path
file_name = os.path.basename(path)
formatted_text.append(f"\n### 📄 {file_name}")
formatted_text.append(self.file_summaries_map[path])
formatted_text.append("\n---")
return "\n".join(formatted_text)
def create_document(self) -> str:
document = [
"# 📑 文档总结报告",
"\n## 总体摘要",
self.final_summary
]
if self.failed_files:
document.append(self.format_failed_files())
document.extend([
"\n# 📚 各文件详细总结",
self.format_file_summaries()
])
return "\n".join(document)
class HtmlFormatter(DocumentFormatter):
"""HTML格式文档生成器"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.css_styles = """
body {
font-family: "Microsoft YaHei", Arial, sans-serif;
line-height: 1.6;
max-width: 1000px;
margin: 0 auto;
padding: 20px;
color: #333;
}
h1 {
color: #2c3e50;
border-bottom: 2px solid #eee;
padding-bottom: 10px;
font-size: 24px;
text-align: center;
}
h2 {
color: #34495e;
margin-top: 30px;
font-size: 20px;
border-left: 4px solid #3498db;
padding-left: 10px;
}
h3 {
color: #2c3e50;
font-size: 18px;
margin-top: 20px;
}
.summary {
background-color: #f8f9fa;
padding: 20px;
border-radius: 5px;
margin: 20px 0;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.details {
margin-top: 40px;
}
.failed-files {
background-color: #fff3f3;
padding: 15px;
border-left: 4px solid #e74c3c;
margin: 20px 0;
}
.file-summary {
background-color: #fff;
padding: 15px;
margin: 15px 0;
border-radius: 4px;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
}
"""
def format_failed_files(self) -> str:
if not self.failed_files:
return ""
failed_files_html = ['<div class="failed-files">']
failed_files_html.append("<h2>⚠️ 处理失败的文件</h2>")
failed_files_html.append("<ul>")
for fp, reason in self.failed_files:
failed_files_html.append(f"<li><strong>{os.path.basename(fp)}:</strong> {reason}</li>")
failed_files_html.append("</ul></div>")
return "\n".join(failed_files_html)
def format_file_summaries(self) -> str:
formatted_html = []
sorted_paths = sorted(self.file_summaries_map.keys())
current_dir = ""
for path in sorted_paths:
dir_path = os.path.dirname(path)
if dir_path != current_dir:
if dir_path:
formatted_html.append(f'<h2>📁 {dir_path}</h2>')
current_dir = dir_path
file_name = os.path.basename(path)
formatted_html.append('<div class="file-summary">')
formatted_html.append(f'<h3>📄 {file_name}</h3>')
formatted_html.append(f'<p>{self.file_summaries_map[path]}</p>')
formatted_html.append('</div>')
return "\n".join(formatted_html)
def create_document(self) -> str:
return f"""
<!DOCTYPE html>
<html>
<head>
<meta charset='utf-8'>
<title>文档总结报告</title>
<style>{self.css_styles}</style>
</head>
<body>
<h1>📑 文档总结报告</h1>
<h2>总体摘要</h2>
<div class="summary">{self.final_summary}</div>
{self.format_failed_files()}
<div class="details">
<h2>📚 各文件详细总结</h2>
{self.format_file_summaries()}
</div>
</body>
</html>
"""

View File

@@ -6,12 +6,16 @@ class SafeUnpickler(pickle.Unpickler):
def get_safe_classes(self):
from crazy_functions.latex_fns.latex_actions import LatexPaperFileGroup, LatexPaperSplit
from crazy_functions.latex_fns.latex_toolbox import LinkedListNode
from numpy.core.multiarray import scalar
from numpy import dtype
# 定义允许的安全类
safe_classes = {
# 在这里添加其他安全的类
'LatexPaperFileGroup': LatexPaperFileGroup,
'LatexPaperSplit': LatexPaperSplit,
'LinkedListNode': LinkedListNode,
'scalar': scalar,
'dtype': dtype,
}
return safe_classes
@@ -22,8 +26,6 @@ class SafeUnpickler(pickle.Unpickler):
for class_name in self.safe_classes.keys():
if (class_name in f'{module}.{name}'):
match_class_name = class_name
if module == 'numpy' or module.startswith('numpy.'):
return super().find_class(module, name)
if match_class_name is not None:
return self.safe_classes[match_class_name]
# 如果尝试加载未授权的类,则抛出异常

View File

@@ -1,13 +1,17 @@
import llama_index
import os
import atexit
from loguru import logger
from typing import List
from llama_index.core import Document
from llama_index.core.ingestion import run_transformations
from llama_index.core.schema import TextNode
from crazy_functions.rag_fns.vector_store_index import GptacVectorStoreIndex
from request_llms.embed_models.openai_embed import OpenAiEmbeddingModel
from shared_utils.connect_void_terminal import get_chat_default_kwargs
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from crazy_functions.rag_fns.vector_store_index import GptacVectorStoreIndex
from llama_index.core.ingestion import run_transformations
from llama_index.core import PromptTemplate
from llama_index.core.response_synthesizers import TreeSummarize
DEFAULT_QUERY_GENERATION_PROMPT = """\
Now, you have context information as below:
@@ -59,7 +63,7 @@ class SaveLoad():
def purge(self):
import shutil
shutil.rmtree(self.checkpoint_dir, ignore_errors=True)
self.vs_index = self.create_new_vs(self.checkpoint_dir)
self.vs_index = self.create_new_vs()
class LlamaIndexRagWorker(SaveLoad):
@@ -71,7 +75,7 @@ class LlamaIndexRagWorker(SaveLoad):
if auto_load_checkpoint:
self.vs_index = self.load_from_checkpoint(checkpoint_dir)
else:
self.vs_index = self.create_new_vs()
self.vs_index = self.create_new_vs(checkpoint_dir)
atexit.register(lambda: self.save_to_checkpoint(checkpoint_dir))
def assign_embedding_model(self):
@@ -87,52 +91,40 @@ class LlamaIndexRagWorker(SaveLoad):
logger.info('oo --------inspect_vector_store end--------')
return vector_store_preview
def add_documents_to_vector_store(self, document_list: List[Document]):
"""
Adds a list of Document objects to the vector store after processing.
"""
documents = document_list
def add_documents_to_vector_store(self, document_list):
documents = [Document(text=t) for t in document_list]
documents_nodes = run_transformations(
documents, # type: ignore
self.vs_index._transformations,
show_progress=True
)
documents, # type: ignore
self.vs_index._transformations,
show_progress=True
)
self.vs_index.insert_nodes(documents_nodes)
if self.debug_mode:
self.inspect_vector_store()
if self.debug_mode: self.inspect_vector_store()
def add_text_to_vector_store(self, text: str):
def add_text_to_vector_store(self, text):
node = TextNode(text=text)
documents_nodes = run_transformations(
[node],
self.vs_index._transformations,
show_progress=True
)
[node],
self.vs_index._transformations,
show_progress=True
)
self.vs_index.insert_nodes(documents_nodes)
if self.debug_mode:
self.inspect_vector_store()
if self.debug_mode: self.inspect_vector_store()
def remember_qa(self, question, answer):
formatted_str = QUESTION_ANSWER_RECORD.format(question=question, answer=answer)
self.add_text_to_vector_store(formatted_str)
def retrieve_from_store_with_query(self, query):
if self.debug_mode:
self.inspect_vector_store()
if self.debug_mode: self.inspect_vector_store()
retriever = self.vs_index.as_retriever()
return retriever.retrieve(query)
def build_prompt(self, query, nodes):
context_str = self.generate_node_array_preview(nodes)
return DEFAULT_QUERY_GENERATION_PROMPT.format(context_str=context_str, query_str=query)
def generate_node_array_preview(self, nodes):
buf = "\n".join(([f"(No.{i+1} | score {n.score:.3f}): {n.text}" for i, n in enumerate(nodes)]))
if self.debug_mode: logger.info(buf)
return buf
def purge_vector_store(self):
"""
Purges the current vector store and creates a new one.
"""
self.purge()

View File

@@ -1,45 +0,0 @@
import os
from llama_index.core import SimpleDirectoryReader
supports_format = ['.csv', '.docx','.doc', '.epub', '.ipynb', '.mbox', '.md', '.pdf', '.txt', '.ppt',
'.pptm', '.pptx','.py', '.xls', '.xlsx', '.html', '.json', '.xml', '.yaml', '.yml' ,'.m']
def read_docx_doc(file_path):
if file_path.split(".")[-1] == "docx":
from docx import Document
doc = Document(file_path)
file_content = "\n".join([para.text for para in doc.paragraphs])
else:
try:
import win32com.client
word = win32com.client.Dispatch("Word.Application")
word.visible = False
# 打开文件
doc = word.Documents.Open(os.getcwd() + '/' + file_path)
# file_content = doc.Content.Text
doc = word.ActiveDocument
file_content = doc.Range().Text
doc.Close()
word.Quit()
except:
raise RuntimeError('请先将.doc文档转换为.docx文档。')
return file_content
# 修改后的 extract_text 函数,结合 SimpleDirectoryReader 和自定义解析逻辑
import os
def extract_text(file_path):
_, ext = os.path.splitext(file_path.lower())
# 使用 SimpleDirectoryReader 处理它支持的文件格式
if ext in ['.docx', '.doc']:
return read_docx_doc(file_path)
try:
reader = SimpleDirectoryReader(input_files=[file_path])
documents = reader.load_data()
if len(documents) > 0:
return documents[0].text
except Exception as e:
pass
return None

View File

@@ -0,0 +1,127 @@
from toolbox import update_ui
from toolbox import CatchException, report_exception
from toolbox import write_history_to_file, promote_file_to_downloadzone
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
import time, os
# pip install python-docx 用于docx格式跨平台
# pip install pywin32 用于doc格式仅支持Win平台
for index, fp in enumerate(file_manifest):
if fp.split(".")[-1] == "docx":
from docx import Document
doc = Document(fp)
file_content = "\n".join([para.text for para in doc.paragraphs])
else:
try:
import win32com.client
word = win32com.client.Dispatch("Word.Application")
word.visible = False
# 打开文件
doc = word.Documents.Open(os.getcwd() + '/' + fp)
# file_content = doc.Content.Text
doc = word.ActiveDocument
file_content = doc.Range().Text
doc.Close()
word.Quit()
except:
raise RuntimeError('请先将.doc文档转换为.docx文档。')
# private_upload里面的文件名在解压zip后容易出现乱码rar和7z格式正常故可以只分析文章内容不输入文件名
from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
from request_llms.bridge_all import model_info
max_token = model_info[llm_kwargs['llm_model']]['max_token']
TOKEN_LIMIT_PER_FRAGMENT = max_token * 3 // 4
paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
this_paper_history = []
for i, paper_frag in enumerate(paper_fragments):
i_say = f'请对下面的文章片段用中文做概述,文件名是{os.path.relpath(fp, project_folder)},文章内容是 ```{paper_frag}```'
i_say_show_user = f'请对下面的文章片段做概述: {os.path.abspath(fp)}的第{i+1}/{len(paper_fragments)}个片段。'
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=i_say,
inputs_show_user=i_say_show_user,
llm_kwargs=llm_kwargs,
chatbot=chatbot,
history=[],
sys_prompt="总结文章。"
)
chatbot[-1] = (i_say_show_user, gpt_say)
history.extend([i_say_show_user,gpt_say])
this_paper_history.extend([i_say_show_user,gpt_say])
# 已经对该文章的所有片段总结完毕,如果文章被切分了,
if len(paper_fragments) > 1:
i_say = f"根据以上的对话,总结文章{os.path.abspath(fp)}的主要内容。"
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=this_paper_history,
sys_prompt="总结文章。"
)
history.extend([i_say,gpt_say])
this_paper_history.extend([i_say,gpt_say])
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("所有文件都总结完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@CatchException
def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
import glob, os
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"批量总结Word文档。函数插件贡献者: JasonGuo1。注意, 如果是.doc文件, 请先转化为.docx格式。"])
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:
from docx import Document
except:
report_exception(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 python-docx pywin32```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 清空历史,以免输入溢出
history = []
# 检测输入参数,如没有给定输入参数,直接退出
if os.path.exists(txt):
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
report_exception(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
# 搜索需要处理的文件清单
if txt.endswith('.docx') or txt.endswith('.doc'):
file_manifest = [txt]
else:
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.docx', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.doc', recursive=True)]
# 如果没找到任何文件
if len(file_manifest) == 0:
report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.docx或doc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docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)

View File

@@ -1,496 +0,0 @@
import os
import threading
import time
from dataclasses import dataclass
from typing import List, Tuple, Dict, Generator
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
from crazy_functions.rag_fns.rag_file_support import extract_text
from request_llms.bridge_all import model_info
from toolbox import update_ui, CatchException, report_exception
@dataclass
class FileFragment:
"""文件片段数据类,用于组织处理单元"""
file_path: str
content: str
rel_path: str
fragment_index: int
total_fragments: int
class BatchDocumentSummarizer:
"""优化的文档总结器 - 批处理版本"""
def __init__(self, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List, history: List, system_prompt: str):
"""初始化总结器"""
self.llm_kwargs = llm_kwargs
self.plugin_kwargs = plugin_kwargs
self.chatbot = chatbot
self.history = history
self.system_prompt = system_prompt
self.failed_files = []
self.file_summaries_map = {}
def _get_token_limit(self) -> int:
"""获取模型token限制"""
max_token = model_info[self.llm_kwargs['llm_model']]['max_token']
return max_token * 3 // 4
def _create_batch_inputs(self, fragments: List[FileFragment]) -> Tuple[List, List, List]:
"""创建批处理输入"""
inputs_array = []
inputs_show_user_array = []
history_array = []
for frag in fragments:
if self.plugin_kwargs.get("advanced_arg"):
i_say = (f'请按照用户要求对文件内容进行处理,文件名为{os.path.basename(frag.file_path)}'
f'用户要求为:{self.plugin_kwargs["advanced_arg"]}'
f'文件内容是 ```{frag.content}```')
i_say_show_user = (f'正在处理 {frag.rel_path} (片段 {frag.fragment_index + 1}/{frag.total_fragments})')
else:
i_say = (f'请对下面的内容用中文做总结不超过500字文件名是{os.path.basename(frag.file_path)}'
f'内容是 ```{frag.content}```')
i_say_show_user = f'正在处理 {frag.rel_path} (片段 {frag.fragment_index + 1}/{frag.total_fragments})'
inputs_array.append(i_say)
inputs_show_user_array.append(i_say_show_user)
history_array.append([])
return inputs_array, inputs_show_user_array, history_array
def _process_single_file_with_timeout(self, file_info: Tuple[str, str], mutable_status: List) -> List[FileFragment]:
"""包装了超时控制的文件处理函数"""
def timeout_handler():
thread = threading.current_thread()
if hasattr(thread, '_timeout_occurred'):
thread._timeout_occurred = True
# 设置超时标记
thread = threading.current_thread()
thread._timeout_occurred = False
# 设置超时定时器
timer = threading.Timer(self.watch_dog_patience, timeout_handler)
timer.start()
try:
fp, project_folder = file_info
fragments = []
# 定期检查是否超时
def check_timeout():
if hasattr(thread, '_timeout_occurred') and thread._timeout_occurred:
raise TimeoutError("处理超时")
# 更新状态
mutable_status[0] = "检查文件大小"
mutable_status[1] = time.time()
check_timeout()
# 文件大小检查
if os.path.getsize(fp) > self.max_file_size:
self.failed_files.append((fp, f"文件过大:超过{self.max_file_size / 1024 / 1024}MB"))
mutable_status[2] = "文件过大"
return fragments
check_timeout()
# 更新状态
mutable_status[0] = "提取文件内容"
mutable_status[1] = time.time()
# 提取内容
content = extract_text(fp)
if content is None:
self.failed_files.append((fp, "文件解析失败:不支持的格式或文件损坏"))
mutable_status[2] = "格式不支持"
return fragments
elif not content.strip():
self.failed_files.append((fp, "文件内容为空"))
mutable_status[2] = "内容为空"
return fragments
check_timeout()
# 更新状态
mutable_status[0] = "分割文本"
mutable_status[1] = time.time()
# 分割文本
try:
paper_fragments = breakdown_text_to_satisfy_token_limit(
txt=content,
limit=self._get_token_limit(),
llm_model=self.llm_kwargs['llm_model']
)
except Exception as e:
self.failed_files.append((fp, f"文本分割失败:{str(e)}"))
mutable_status[2] = "分割失败"
return fragments
check_timeout()
# 处理片段
rel_path = os.path.relpath(fp, project_folder)
for i, frag in enumerate(paper_fragments):
if frag.strip():
fragments.append(FileFragment(
file_path=fp,
content=frag,
rel_path=rel_path,
fragment_index=i,
total_fragments=len(paper_fragments)
))
mutable_status[2] = "处理完成"
return fragments
except TimeoutError as e:
self.failed_files.append((fp, "处理超时"))
mutable_status[2] = "处理超时"
return []
except Exception as e:
self.failed_files.append((fp, f"处理失败:{str(e)}"))
mutable_status[2] = "处理异常"
return []
finally:
timer.cancel()
def prepare_fragments(self, project_folder: str, file_paths: List[str]) -> Generator:
import concurrent.futures
from concurrent.futures import ThreadPoolExecutor
from typing import Generator, List
"""并行准备所有文件的处理片段"""
all_fragments = []
total_files = len(file_paths)
# 配置参数
self.refresh_interval = 0.2 # UI刷新间隔
self.watch_dog_patience = 5 # 看门狗超时时间
self.max_file_size = 10 * 1024 * 1024 # 10MB限制
self.max_workers = min(32, len(file_paths)) # 最多32个线程
# 创建有超时控制的线程池
executor = ThreadPoolExecutor(max_workers=self.max_workers)
# 用于跨线程状态传递的可变列表 - 增加文件名信息
mutable_status_array = [["等待中", time.time(), "pending", file_path] for file_path in file_paths]
# 创建文件处理任务
file_infos = [(fp, project_folder) for fp in file_paths]
# 提交所有任务,使用带超时控制的处理函数
futures = [
executor.submit(
self._process_single_file_with_timeout,
file_info,
mutable_status_array[i]
) for i, file_info in enumerate(file_infos)
]
# 更新UI的计数器
cnt = 0
try:
# 监控任务执行
while True:
time.sleep(self.refresh_interval)
cnt += 1
# 检查任务完成状态
worker_done = [f.done() for f in futures]
# 更新状态显示
status_str = ""
for i, (status, timestamp, desc, file_path) in enumerate(mutable_status_array):
# 获取文件名(去掉路径)
file_name = os.path.basename(file_path)
if worker_done[i]:
status_str += f"文件 {file_name}: {desc}\n"
else:
status_str += f"文件 {file_name}: {status} {desc}\n"
# 更新UI
self.chatbot[-1] = [
"处理进度",
f"正在处理文件...\n\n{status_str}" + "." * (cnt % 10 + 1)
]
yield from update_ui(chatbot=self.chatbot, history=self.history)
# 检查是否所有任务完成
if all(worker_done):
break
finally:
# 确保线程池正确关闭
executor.shutdown(wait=False)
# 收集结果
processed_files = 0
for future in futures:
try:
fragments = future.result(timeout=0.1) # 给予一个短暂的超时时间来获取结果
all_fragments.extend(fragments)
processed_files += 1
except concurrent.futures.TimeoutError:
# 处理获取结果超时
file_index = futures.index(future)
self.failed_files.append((file_paths[file_index], "结果获取超时"))
continue
except Exception as e:
# 处理其他异常
file_index = futures.index(future)
self.failed_files.append((file_paths[file_index], f"未知错误:{str(e)}"))
continue
# 最终进度更新
self.chatbot.append([
"文件处理完成",
f"成功处理 {len(all_fragments)} 个片段,失败 {len(self.failed_files)} 个文件"
])
yield from update_ui(chatbot=self.chatbot, history=self.history)
return all_fragments
def _process_fragments_batch(self, fragments: List[FileFragment]) -> Generator:
"""批量处理文件片段"""
from collections import defaultdict
batch_size = 64 # 每批处理的片段数
max_retries = 3 # 最大重试次数
retry_delay = 5 # 重试延迟(秒)
results = defaultdict(list)
# 按批次处理
for i in range(0, len(fragments), batch_size):
batch = fragments[i:i + batch_size]
inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(batch)
sys_prompt_array = ["请总结以下内容:"] * len(batch)
# 添加重试机制
for retry in range(max_retries):
try:
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=self.llm_kwargs,
chatbot=self.chatbot,
history_array=history_array,
sys_prompt_array=sys_prompt_array,
)
# 处理响应
for j, frag in enumerate(batch):
summary = response_collection[j * 2 + 1]
if summary and summary.strip():
results[frag.rel_path].append({
'index': frag.fragment_index,
'summary': summary,
'total': frag.total_fragments
})
break # 成功处理,跳出重试循环
except Exception as e:
if retry == max_retries - 1: # 最后一次重试失败
for frag in batch:
self.failed_files.append((frag.file_path, f"处理失败:{str(e)}"))
else:
yield from update_ui(self.chatbot.append([f"批次处理失败,{retry_delay}秒后重试...", str(e)]))
time.sleep(retry_delay)
return results
def _generate_final_summary_request(self) -> Tuple[List, List, List]:
"""准备最终总结请求"""
if not self.file_summaries_map:
return (["无可用的文件总结"], ["生成最终总结"], [[]])
summaries = list(self.file_summaries_map.values())
if all(not summary for summary in summaries):
return (["所有文件处理均失败"], ["生成最终总结"], [[]])
if self.plugin_kwargs.get("advanced_arg"):
i_say = "根据以上所有文件的处理结果,按要求进行综合处理:" + self.plugin_kwargs['advanced_arg']
else:
i_say = "请根据以上所有文件的处理结果生成最终的总结不超过1000字。"
return ([i_say], [i_say], [summaries])
def process_files(self, project_folder: str, file_paths: List[str]) -> Generator:
"""处理所有文件"""
total_files = len(file_paths)
self.chatbot.append([f"开始处理", f"总计 {total_files} 个文件"])
yield from update_ui(chatbot=self.chatbot, history=self.history)
# 1. 准备所有文件片段
# 在 process_files 函数中:
fragments = yield from self.prepare_fragments(project_folder, file_paths)
if not fragments:
self.chatbot.append(["处理失败", "没有可处理的文件内容"])
return "没有可处理的文件内容"
# 2. 批量处理所有文件片段
self.chatbot.append([f"文件分析", f"共计 {len(fragments)} 个处理单元"])
yield from update_ui(chatbot=self.chatbot, history=self.history)
try:
file_summaries = yield from self._process_fragments_batch(fragments)
except Exception as e:
self.chatbot.append(["处理错误", f"批处理过程失败:{str(e)}"])
return "处理过程发生错误"
# 3. 为每个文件生成整体总结
self.chatbot.append(["生成总结", "正在汇总文件内容..."])
yield from update_ui(chatbot=self.chatbot, history=self.history)
# 处理每个文件的总结
for rel_path, summaries in file_summaries.items():
if len(summaries) > 1: # 多片段文件需要生成整体总结
sorted_summaries = sorted(summaries, key=lambda x: x['index'])
if self.plugin_kwargs.get("advanced_arg"):
i_say = f'请按照用户要求对文件内容进行处理,用户要求为:{self.plugin_kwargs["advanced_arg"]}'
else:
i_say = f"请总结文件 {os.path.basename(rel_path)} 的主要内容不超过500字。"
try:
summary_texts = [s['summary'] for s in sorted_summaries]
response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
inputs_array=[i_say],
inputs_show_user_array=[f"生成 {rel_path} 的处理结果"],
llm_kwargs=self.llm_kwargs,
chatbot=self.chatbot,
history_array=[summary_texts],
sys_prompt_array=["你是一个优秀的助手,"],
)
self.file_summaries_map[rel_path] = response_collection[1]
except Exception as e:
self.chatbot.append(["警告", f"文件 {rel_path} 总结生成失败:{str(e)}"])
self.file_summaries_map[rel_path] = "总结生成失败"
else: # 单片段文件直接使用其唯一的总结
self.file_summaries_map[rel_path] = summaries[0]['summary']
# 4. 生成最终总结
if total_files ==1:
return "文件数为1此时不调用总结模块"
else:
try:
# 收集所有文件的总结用于生成最终总结
file_summaries_for_final = []
for rel_path, summary in self.file_summaries_map.items():
file_summaries_for_final.append(f"文件 {rel_path} 的总结:\n{summary}")
if self.plugin_kwargs.get("advanced_arg"):
final_summary_prompt = ("根据以下所有文件的总结内容,按要求进行综合处理:" +
self.plugin_kwargs['advanced_arg'])
else:
final_summary_prompt = "请根据以下所有文件的总结内容,生成最终的总结报告。"
response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
inputs_array=[final_summary_prompt],
inputs_show_user_array=["生成最终总结报告"],
llm_kwargs=self.llm_kwargs,
chatbot=self.chatbot,
history_array=[file_summaries_for_final],
sys_prompt_array=["总结所有文件内容。"],
max_workers=1
)
return response_collection[1] if len(response_collection) > 1 else "生成总结失败"
except Exception as e:
self.chatbot.append(["错误", f"最终总结生成失败:{str(e)}"])
return "生成总结失败"
def save_results(self, final_summary: str):
"""保存结果到文件"""
from toolbox import promote_file_to_downloadzone, write_history_to_file
from crazy_functions.doc_fns.batch_file_query_doc import MarkdownFormatter, HtmlFormatter, WordFormatter
import os
timestamp = time.strftime("%Y%m%d_%H%M%S")
# 创建各种格式化器
md_formatter = MarkdownFormatter(final_summary, self.file_summaries_map, self.failed_files)
html_formatter = HtmlFormatter(final_summary, self.file_summaries_map, self.failed_files)
word_formatter = WordFormatter(final_summary, self.file_summaries_map, self.failed_files)
result_files = []
# 保存 Markdown
md_content = md_formatter.create_document()
result_file_md = write_history_to_file(
history=[md_content], # 直接传入内容列表
file_basename=f"文档总结_{timestamp}.md"
)
result_files.append(result_file_md)
# 保存 HTML
html_content = html_formatter.create_document()
result_file_html = write_history_to_file(
history=[html_content],
file_basename=f"文档总结_{timestamp}.html"
)
result_files.append(result_file_html)
# 保存 Word
doc = word_formatter.create_document()
# 由于 Word 文档需要用 doc.save(),我们使用与 md 文件相同的目录
result_file_docx = os.path.join(
os.path.dirname(result_file_md),
f"文档总结_{timestamp}.docx"
)
doc.save(result_file_docx)
result_files.append(result_file_docx)
# 添加到下载区
for file in result_files:
promote_file_to_downloadzone(file, chatbot=self.chatbot)
self.chatbot.append(["处理完成", f"结果已保存至: {', '.join(result_files)}"])
@CatchException
def 批量文件询问(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
history: List, system_prompt: str, user_request: str):
"""主函数 - 优化版本"""
# 初始化
import glob
import re
from crazy_functions.rag_fns.rag_file_support import supports_format
from toolbox import report_exception
summarizer = BatchDocumentSummarizer(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
chatbot.append(["函数插件功能", f"作者lbykkkk批量总结文件。支持格式: {', '.join(supports_format)}等其他文本格式文件如果长时间卡在文件处理过程请查看处理进度然后删除所有处于“pending”状态的文件然后重新上传处理。"])
yield from update_ui(chatbot=chatbot, history=history)
# 验证输入路径
if not os.path.exists(txt):
report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history)
return
# 获取文件列表
project_folder = txt
extract_folder = next((d for d in glob.glob(f'{project_folder}/*')
if os.path.isdir(d) and d.endswith('.extract')), project_folder)
exclude_patterns = r'/[^/]+\.(zip|rar|7z|tar|gz)$'
file_manifest = [f for f in glob.glob(f'{extract_folder}/**', recursive=True)
if os.path.isfile(f) and not re.search(exclude_patterns, f)]
if not file_manifest:
report_exception(chatbot, history, a=f"解析项目: {txt}", b="未找到支持的文件类型")
yield from update_ui(chatbot=chatbot, history=history)
return
# 处理所有文件并生成总结
final_summary = yield from summarizer.process_files(project_folder, file_manifest)
yield from update_ui(chatbot=chatbot, history=history)
# 保存结果
summarizer.save_results(final_summary)
yield from update_ui(chatbot=chatbot, history=history)

View File

@@ -149,6 +149,19 @@
DEFINE_ARG_INPUT_INTERFACE = json.dumps(define_arg_selection)
return base64.b64encode(DEFINE_ARG_INPUT_INTERFACE.encode('utf-8')).decode('utf-8')
```
1-2. 预留4个动态插件按钮常规状态隐藏
点击 “+插件按钮”:跳转到插件市场
点击 加载插件:
- 下载文件
- 注册 exe_dynamic_plugin开始执行
- 执行浏览器js函数
点击动态插件按钮
- js 检查register_advanced_plugin_init_code_arr如果为空提示
- 如果非空,先跳二级菜单,设定诸元后,执行一个隐藏的按钮 -- 关联 exe_dynamic_plugin
- exe_dynamic_plugin开始执行
2. 用户加载阶段主javascript程序`common.js`中),浏览器加载`register_advanced_plugin_init_code_arr`,存入本地的字典`advanced_plugin_init_code_lib`

View File

@@ -385,6 +385,14 @@ model_info = {
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
"glm-4-plus":{
"fn_with_ui": zhipu_ui,
"fn_without_ui": zhipu_noui,
"endpoint": None,
"max_token": 10124 * 8,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
# api_2d (此后不需要在此处添加api2d的接口了因为下面的代码会自动添加)
"api2d-gpt-4": {

View File

@@ -138,7 +138,9 @@ def start_app(app_block, CONCURRENT_COUNT, AUTHENTICATION, PORT, SSL_KEYFILE, SS
app_block.is_sagemaker = False
gradio_app = App.create_app(app_block)
for route in list(gradio_app.router.routes):
if route.path == "/proxy={url_path:path}":
gradio_app.router.routes.remove(route)
# --- --- replace gradio endpoint to forbid access to sensitive files --- ---
if len(AUTHENTICATION) > 0:
dependencies = []
@@ -154,9 +156,13 @@ def start_app(app_block, CONCURRENT_COUNT, AUTHENTICATION, PORT, SSL_KEYFILE, SS
@gradio_app.head("/file={path_or_url:path}", dependencies=dependencies)
@gradio_app.get("/file={path_or_url:path}", dependencies=dependencies)
async def file(path_or_url: str, request: fastapi.Request):
if len(AUTHENTICATION) > 0:
if not _authorize_user(path_or_url, request, gradio_app):
return "越权访问!"
if not _authorize_user(path_or_url, request, gradio_app):
return "越权访问!"
stripped = path_or_url.lstrip().lower()
if stripped.startswith("https://") or stripped.startswith("http://"):
return "账户密码授权模式下, 禁止链接!"
if '../' in stripped:
return "非法路径!"
return await endpoint(path_or_url, request)
from fastapi import Request, status
@@ -167,6 +173,26 @@ def start_app(app_block, CONCURRENT_COUNT, AUTHENTICATION, PORT, SSL_KEYFILE, SS
response.delete_cookie('access-token')
response.delete_cookie('access-token-unsecure')
return response
else:
dependencies = []
endpoint = None
for route in list(gradio_app.router.routes):
if route.path == "/file/{path:path}":
gradio_app.router.routes.remove(route)
if route.path == "/file={path_or_url:path}":
dependencies = route.dependencies
endpoint = route.endpoint
gradio_app.router.routes.remove(route)
@gradio_app.get("/file/{path:path}", dependencies=dependencies)
@gradio_app.head("/file={path_or_url:path}", dependencies=dependencies)
@gradio_app.get("/file={path_or_url:path}", dependencies=dependencies)
async def file(path_or_url: str, request: fastapi.Request):
stripped = path_or_url.lstrip().lower()
if stripped.startswith("https://") or stripped.startswith("http://"):
return "账户密码授权模式下, 禁止链接!"
if '../' in stripped:
return "非法路径!"
return await endpoint(path_or_url, request)
# --- --- enable TTS (text-to-speech) functionality --- ---
TTS_TYPE = get_conf("TTS_TYPE")

View File

@@ -104,17 +104,27 @@ def extract_archive(file_path, dest_dir):
logger.info("Successfully extracted zip archive to {}".format(dest_dir))
elif file_extension in [".tar", ".gz", ".bz2"]:
with tarfile.open(file_path, "r:*") as tarobj:
# 清理提取路径,移除任何不安全的元素
for member in tarobj.getmembers():
member_path = os.path.normpath(member.name)
full_path = os.path.join(dest_dir, member_path)
full_path = os.path.abspath(full_path)
if not full_path.startswith(os.path.abspath(dest_dir) + os.sep):
raise Exception(f"Attempted Path Traversal in {member.name}")
try:
with tarfile.open(file_path, "r:*") as tarobj:
# 清理提取路径,移除任何不安全的元素
for member in tarobj.getmembers():
member_path = os.path.normpath(member.name)
full_path = os.path.join(dest_dir, member_path)
full_path = os.path.abspath(full_path)
if not full_path.startswith(os.path.abspath(dest_dir) + os.sep):
raise Exception(f"Attempted Path Traversal in {member.name}")
tarobj.extractall(path=dest_dir)
logger.info("Successfully extracted tar archive to {}".format(dest_dir))
tarobj.extractall(path=dest_dir)
logger.info("Successfully extracted tar archive to {}".format(dest_dir))
except tarfile.ReadError as e:
if file_extension == ".gz":
# 一些特别奇葩的项目是一个gz文件里面不是tar只有一个tex文件
import gzip
with gzip.open(file_path, 'rb') as f_in:
with open(os.path.join(dest_dir, 'main.tex'), 'wb') as f_out:
f_out.write(f_in.read())
else:
raise e
# 第三方库需要预先pip install rarfile
# 此外Windows上还需要安装winrar软件配置其Path环境变量如"C:\Program Files\WinRAR"才可以

View File

@@ -14,6 +14,7 @@ openai_regex = re.compile(
r"sk-[a-zA-Z0-9_-]{92}$|" +
r"sk-proj-[a-zA-Z0-9_-]{48}$|"+
r"sk-proj-[a-zA-Z0-9_-]{124}$|"+
r"sk-proj-[a-zA-Z0-9_-]{156}$|"+ #新版apikey位数不匹配故修改此正则表达式
r"sess-[a-zA-Z0-9]{40}$"
)
def is_openai_api_key(key):

View File

@@ -36,7 +36,7 @@ if __name__ == "__main__":
# plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc")
# plugin_test(plugin='crazy_functions.Latex全文润色->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
# plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
# plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md")
@@ -65,8 +65,3 @@ if __name__ == "__main__":
# plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629")
# advanced_arg = {"advanced_arg":"--llm_to_learn=gpt-3.5-turbo --prompt_prefix='根据下面的服装类型提示想象一个穿着者对这个人外貌、身处的环境、内心世界、人设进行描写。要求100字以内用第二人称。' --system_prompt=''" }
# plugin_test(plugin='crazy_functions.chatglm微调工具->微调数据集生成', main_input='build/dev.json', advanced_arg=advanced_arg)
# advanced_arg = {"advanced_arg":"--pre_seq_len=128 --learning_rate=2e-2 --num_gpus=1 --json_dataset='t_code.json' --ptuning_directory='/home/hmp/ChatGLM2-6B/ptuning' " }
# plugin_test(plugin='crazy_functions.chatglm微调工具->启动微调', main_input='build/dev.json', advanced_arg=advanced_arg)