up

.github/workflows/conda-pack-windows.yml

@@ -1,56 +0,0 @@
-name: Create Conda Environment Package
-
-on:
-  workflow_dispatch:
-
-jobs:
-  build:
-    runs-on: windows-latest
-    
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@v4
-      
-    - name: Setup Miniconda
-      uses: conda-incubator/setup-miniconda@v3
-      with:
-        auto-activate-base: true
-        activate-environment: ""
-        
-    - name: Create new Conda environment
-      shell: bash -l {0}
-      run: |
-        conda create -n gpt python=3.11 -y
-        conda activate gpt
-        
-    - name: Install requirements
-      shell: bash -l {0}
-      run: |
-        conda activate gpt
-        pip install -r requirements.txt
-        
-    - name: Install conda-pack
-      shell: bash -l {0}
-      run: |
-        conda activate gpt
-        conda install conda-pack -y
-        
-    - name: Pack conda environment
-      shell: bash -l {0}
-      run: |
-        conda activate gpt
-        conda pack -n gpt -o gpt.tar.gz
-      
-    - name: Create workspace zip
-      shell: pwsh
-      run: |
-        mkdir workspace
-        Get-ChildItem -Exclude "workspace" | Copy-Item -Destination workspace -Recurse
-        Remove-Item -Path workspace/.git* -Recurse -Force -ErrorAction SilentlyContinue
-        Copy-Item gpt.tar.gz workspace/ -Force
-    
-    - name: Upload packed files
-      uses: actions/upload-artifact@v4
-      with:
-        name: gpt-academic-package
-        path: workspace

.github/workflows/stale.yml

@@ -7,7 +7,7 @@
 name: 'Close stale issues and PRs'
 on:
   schedule:
-    - cron: '*/30 * * * *'
+    - cron: '*/5 * * * *'
 
 jobs:
   stale:
@@ -19,6 +19,7 @@ jobs:
     steps:
       - uses: actions/stale@v8
         with:
-          stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 7 days.'
+          stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 1 days.'
           days-before-stale: 100
-          days-before-close: 7
+          days-before-close: 1
+          debug-only: true

.gitignore

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

Dockerfile

@@ -3,36 +3,37 @@
 # - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . `
 # - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic `
 # - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic `
+FROM python:3.11
 
-FROM ghcr.io/astral-sh/uv:python3.12-bookworm
 
 # 非必要步骤，更换pip源 （以下三行，可以删除）
 RUN echo '[global]' > /etc/pip.conf && \
     echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
     echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
 
-# 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除） 
+
-RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
+# 语音输出功能（以下两行，第一行更换阿里源，第二行安装ffmpeg，都可以删除）
-    sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
+RUN UBUNTU_VERSION=$(awk -F= '/^VERSION_CODENAME=/{print $2}' /etc/os-release); echo "deb https://mirrors.aliyun.com/debian/ $UBUNTU_VERSION main non-free contrib" > /etc/apt/sources.list; apt-get update
-    apt-get update
 RUN apt-get install ffmpeg -y
-RUN apt-get clean
+
 
 # 进入工作路径（必要）
 WORKDIR /gpt
 
+
 # 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
 COPY requirements.txt ./
-RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
+RUN pip3 install -r requirements.txt
-ENV PATH="/gpt/.venv/bin:$PATH"
+
-RUN python -c 'import loguru'
 
 # 装载项目文件，安装剩余依赖（必要）
 COPY . .
-RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
+RUN pip3 install -r requirements.txt
+
+
+# 非必要步骤，用于预热模块（可以删除）
+RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
-# # 非必要步骤，用于预热模块（可以删除）
-RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
 # 启动（必要）
-CMD ["bash", "-c", "python main.py"]
+CMD ["python3", "-u", "main.py"]

README.md

@@ -1,15 +1,9 @@
 > [!IMPORTANT]
-> `master主分支`最新动态(2025.7.31): 新GUI前端，Coming Soon
+> 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/file/d/19U_hsLoMrjOlQSzYS3pzWX9fTzyusArP/view?usp=sharing)的文件服务器  
-> `master主分支`最新动态(2025.3.2): 修复大量代码typo / 联网组件支持Jina的api / 增加deepseek-r1支持  
+> 2024.10.8: 版本3.90加入对llama-index的初步支持，版本3.80加入插件二级菜单功能（详见wiki）  
-> `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能，优化xelatex论文翻译  
-> `wiki文档`最新动态(2024.12.5): 更新ollama接入指南  
->
-> 2025.2.2: 三分钟快速接入最强qwen2.5-max[视频](https://www.bilibili.com/video/BV1LeFuerEG4)  
-> 2025.2.1: 支持自定义字体  
-> 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/drive/folders/14kR-3V-lIbvGxri4AHc8TpiA1fqsw7SK?usp=sharing)的文件服务器  
 > 2024.5.1: 加入Doc2x翻译PDF论文的功能，[查看详情](https://github.com/binary-husky/gpt_academic/wiki/Doc2x)  
 > 2024.3.11: 全力支持Qwen、GLM、DeepseekCoder等中文大语言模型！ SoVits语音克隆模块，[查看详情](https://www.bilibili.com/video/BV1Rp421S7tF/) 
-> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。
+> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。本项目完全开源免费，您可通过订阅[在线服务](https://github.com/binary-husky/gpt_academic/wiki/online)的方式鼓励本项目的发展。
 
 <br>
 
@@ -130,20 +124,20 @@ Latex论文一键校对 | [插件] 仿Grammarly对Latex文章进行语法、拼
 
 ```mermaid
 flowchart TD
-    A{"安装方法"} --> W1("I 🔑直接运行 (Windows, Linux or MacOS)")
+    A{"安装方法"} --> W1("I. 🔑直接运行 (Windows, Linux or MacOS)")
-    W1 --> W11["1 Python pip包管理依赖"]
+    W1 --> W11["1. Python pip包管理依赖"]
-    W1 --> W12["2 Anaconda包管理依赖（推荐⭐）"]
+    W1 --> W12["2. Anaconda包管理依赖（推荐⭐）"]
 
-    A --> W2["II 🐳使用Docker (Windows, Linux or MacOS)"]
+    A --> W2["II. 🐳使用Docker (Windows, Linux or MacOS)"]
 
-    W2 --> k1["1 部署项目全部能力的大镜像（推荐⭐）"]
+    W2 --> k1["1. 部署项目全部能力的大镜像（推荐⭐）"]
-    W2 --> k2["2 仅在线模型（GPT, GLM4等）镜像"]
+    W2 --> k2["2. 仅在线模型（GPT, GLM4等）镜像"]
-    W2 --> k3["3 在线模型 + Latex的大镜像"]
+    W2 --> k3["3. 在线模型 + Latex的大镜像"]
 
-    A --> W4["IV 🚀其他部署方法"]
+    A --> W4["IV. 🚀其他部署方法"]
-    W4 --> C1["1 Windows/MacOS 一键安装运行脚本（推荐⭐）"]
+    W4 --> C1["1. Windows/MacOS 一键安装运行脚本（推荐⭐）"]
-    W4 --> C2["2 Huggingface, Sealos远程部署"]
+    W4 --> C2["2. Huggingface, Sealos远程部署"]
-    W4 --> C4["3 其他 ..."]
+    W4 --> C4["3. ... 其他 ..."]
 ```
 
 ### 安装方法I：直接运行 (Windows, Linux or MacOS)
@@ -176,32 +170,26 @@ flowchart TD
     ```
 
 
-<details><summary>如果需要支持清华ChatGLM系列/复旦MOSS/RWKV作为后端，请点击展开此处</summary>
+<details><summary>如果需要支持清华ChatGLM2/复旦MOSS/RWKV作为后端，请点击展开此处</summary>
 <p>
 
-【可选步骤】如果需要支持清华ChatGLM系列/复旦MOSS作为后端，需要额外安装更多依赖（前提条件：熟悉Python + 用过Pytorch + 电脑配置够强）：
+【可选步骤】如果需要支持清华ChatGLM3/复旦MOSS作为后端，需要额外安装更多依赖（前提条件：熟悉Python + 用过Pytorch + 电脑配置够强）：
 
 ```sh
 # 【可选步骤I】支持清华ChatGLM3。清华ChatGLM备注：如果遇到"Call ChatGLM fail 不能正常加载ChatGLM的参数" 错误，参考如下： 1：以上默认安装的为torch+cpu版，使用cuda需要卸载torch重新安装torch+cuda； 2：如因本机配置不够无法加载模型，可以修改request_llm/bridge_chatglm.py中的模型精度, 将 AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) 都修改为 AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
 python -m pip install -r request_llms/requirements_chatglm.txt
 
-# 【可选步骤II】支持清华ChatGLM4 注意：此模型至少需要24G显存
+# 【可选步骤II】支持复旦MOSS
-python -m pip install -r request_llms/requirements_chatglm4.txt
-# 可使用modelscope下载ChatGLM4模型
-# pip install modelscope
-# modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat
-
-# 【可选步骤III】支持复旦MOSS
 python -m pip install -r request_llms/requirements_moss.txt
 git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss  # 注意执行此行代码时，必须处于项目根路径
 
-# 【可选步骤IV】支持RWKV Runner
+# 【可选步骤III】支持RWKV Runner
 参考wiki：https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
 
-# 【可选步骤V】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型，目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)：
+# 【可选步骤IV】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型，目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)：
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
 
-# 【可选步骤VI】支持本地模型INT8,INT4量化（这里所指的模型本身不是量化版本，目前deepseek-coder支持，后面测试后会加入更多模型量化选择）
+# 【可选步骤V】支持本地模型INT8,INT4量化（这里所指的模型本身不是量化版本，目前deepseek-coder支持，后面测试后会加入更多模型量化选择）
 pip install bitsandbyte
 # windows用户安装bitsandbytes需要使用下面bitsandbytes-windows-webui
 python -m pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui
@@ -429,6 +417,7 @@ timeline LR
 1. `master` 分支: 主分支，稳定版
 2. `frontier` 分支: 开发分支，测试版
 3. 如何[接入其他大模型](request_llms/README.md)
+4. 访问GPT-Academic的[在线服务并支持我们](https://github.com/binary-husky/gpt_academic/wiki/online)
 
 ### V：参考与学习
 

config.py

@@ -7,16 +7,11 @@
     Configuration reading priority: environment variable > config_private.py > config.py
 """
 
-# [step 1-1]>> ( 接入OpenAI模型家族 ) API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
+# [step 1]>> API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
-API_KEY = "在此处填写APIKEY"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey3,azure-apikey4"
+API_KEY = "此处填API密钥"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey3,azure-apikey4"
 
-# [step 1-2]>> ( 强烈推荐！接入通义家族 & 大模型服务平台百炼 ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/
-DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY（用于接入qwen-max，dashscope-qwen3-14b，dashscope-deepseek-r1等）
 
-# [step 1-3]>> ( 接入 deepseek-reasoner, 即 deepseek-r1 ) 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
+# [step 2]>> 改为True应用代理，如果直接在海外服务器部署，此处不修改；如果使用本地或无地域限制的大模型时，此处也不需要修改
-DEEPSEEK_API_KEY = ""
-
-# [step 2]>> 改为True应用代理。如果使用本地或无地域限制的大模型时，此处不修改；如果直接在海外服务器部署，此处不修改
 USE_PROXY = False
 if USE_PROXY:
     """
@@ -37,16 +32,11 @@ else:
 
 # [step 3]>> 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
 LLM_MODEL = "gpt-3.5-turbo-16k" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["qwen-max", "o1-mini", "o1-mini-2024-09-12", "o1", "o1-2024-12-17", "o1-preview", "o1-preview-2024-09-12",
+AVAIL_LLM_MODELS = ["gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-preview",
-                    "gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-preview",
                     "gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4-turbo-2024-04-09",
                     "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo",
-                    "gemini-1.5-pro", "chatglm3", "chatglm4",
+                    "gemini-1.5-pro", "chatglm3"
-                    "deepseek-chat", "deepseek-coder", "deepseek-reasoner", 
-                    "volcengine-deepseek-r1-250120", "volcengine-deepseek-v3-241226",
-                    "dashscope-deepseek-r1", "dashscope-deepseek-v3",
-                    "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-32b",
                     ]
 
 EMBEDDING_MODEL = "text-embedding-3-small"
@@ -57,7 +47,7 @@ EMBEDDING_MODEL = "text-embedding-3-small"
 #   "glm-4-0520", "glm-4-air", "glm-4-airx", "glm-4-flash",
 #   "qianfan", "deepseekcoder",
 #   "spark", "sparkv2", "sparkv3", "sparkv3.5", "sparkv4",
-#   "qwen-turbo", "qwen-plus", "qwen-local",
+#   "qwen-turbo", "qwen-plus", "qwen-max", "qwen-local",
 #   "moonshot-v1-128k", "moonshot-v1-32k", "moonshot-v1-8k",
 #   "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo-0125", "gpt-4o-2024-05-13"
 #   "claude-3-haiku-20240307","claude-3-sonnet-20240229","claude-3-opus-20240229", "claude-2.1", "claude-instant-1.2",
@@ -65,7 +55,6 @@ EMBEDDING_MODEL = "text-embedding-3-small"
 #   "deepseek-chat" ,"deepseek-coder",
 #   "gemini-1.5-flash",
 #   "yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview",
-#   "grok-beta",
 # ]
 # --- --- --- ---
 # 此外，您还可以在接入one-api/vllm/ollama/Openroute时，
@@ -84,7 +73,7 @@ API_URL_REDIRECT = {}
 
 # 多线程函数插件中，默认允许多少路线程同时访问OpenAI。Free trial users的限制是每分钟3次，Pay-as-you-go users的限制是每分钟3500次
 # 一言以蔽之：免费（5刀）用户填3，OpenAI绑了信用卡的用户可以填 16 或者更高。提高限制请查询：https://platform.openai.com/docs/guides/rate-limits/overview
-DEFAULT_WORKER_NUM = 8
+DEFAULT_WORKER_NUM = 3
 
 
 # 色彩主题, 可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
@@ -92,31 +81,6 @@ DEFAULT_WORKER_NUM = 8
 THEME = "Default"
 AVAIL_THEMES = ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast", "Gstaff/Xkcd", "NoCrypt/Miku"]
 
-FONT = "Theme-Default-Font"
-AVAIL_FONTS = [
-    "默认值(Theme-Default-Font)", 
-    "宋体(SimSun)",  
-    "黑体(SimHei)",  
-    "楷体(KaiTi)",  
-    "仿宋(FangSong)",  
-    "华文细黑(STHeiti Light)",
-    "华文楷体(STKaiti)",  
-    "华文仿宋(STFangsong)",  
-    "华文宋体(STSong)",  
-    "华文中宋(STZhongsong)",  
-    "华文新魏(STXinwei)",  
-    "华文隶书(STLiti)", 
-    # 备注：以下字体需要网络支持，您可以自定义任意您喜欢的字体，如下所示，需要满足的格式为 "字体昵称(字体英文真名@字体css下载链接)" 
-    "思源宋体(Source Han Serif CN VF@https://chinese-fonts-cdn.deno.dev/packages/syst/dist/SourceHanSerifCN/result.css)",
-    "月星楷(Moon Stars Kai HW@https://chinese-fonts-cdn.deno.dev/packages/moon-stars-kai/dist/MoonStarsKaiHW-Regular/result.css)",
-    "珠圆体(MaokenZhuyuanTi@https://chinese-fonts-cdn.deno.dev/packages/mkzyt/dist/猫啃珠圆体/result.css)",
-    "平方萌萌哒(PING FANG MENG MNEG DA@https://chinese-fonts-cdn.deno.dev/packages/pfmmd/dist/平方萌萌哒/result.css)",
-    "Helvetica",
-    "ui-sans-serif",
-    "sans-serif",
-    "system-ui"
-]
-
 
 # 默认的系统提示词（system prompt）
 INIT_SYS_PROMPT = "Serve me as a writing and programming assistant."
@@ -168,15 +132,16 @@ MULTI_QUERY_LLM_MODELS = "gpt-3.5-turbo&chatglm3"
 QWEN_LOCAL_MODEL_SELECTION = "Qwen/Qwen-1_8B-Chat-Int8"
 
 
+# 接入通义千问在线大模型 https://dashscope.console.aliyun.com/
+DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY
+
+
 # 百度千帆（LLM_MODEL="qianfan"）
 BAIDU_CLOUD_API_KEY = ''
 BAIDU_CLOUD_SECRET_KEY = ''
 BAIDU_CLOUD_QIANFAN_MODEL = 'ERNIE-Bot'    # 可选 "ERNIE-Bot-4"(文心大模型4.0), "ERNIE-Bot"(文心一言), "ERNIE-Bot-turbo", "BLOOMZ-7B", "Llama-2-70B-Chat", "Llama-2-13B-Chat", "Llama-2-7B-Chat", "ERNIE-Speed-128K", "ERNIE-Speed-8K", "ERNIE-Lite-8K"
 
 
-# 如果使用ChatGLM3或ChatGLM4本地模型，请把 LLM_MODEL="chatglm3" 或LLM_MODEL="chatglm4"，并在此处指定模型路径
-CHATGLM_LOCAL_MODEL_PATH = "THUDM/glm-4-9b-chat" # 例如"/home/hmp/ChatGLM3-6B/"
-
 # 如果使用ChatGLM2微调模型，请把 LLM_MODEL="chatglmft"，并在此处指定模型路径
 CHATGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b-pt-128-1e-2/checkpoint-100"
 
@@ -270,15 +235,13 @@ MOONSHOT_API_KEY = ""
 YIMODEL_API_KEY = ""
 
 
-# 接入火山引擎的在线大模型)，api-key获取地址 https://console.volcengine.com/ark/region:ark+cn-beijing/endpoint
+# 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
-ARK_API_KEY = "00000000-0000-0000-0000-000000000000" # 火山引擎 API KEY
+DEEPSEEK_API_KEY = ""
 
 
 # 紫东太初大模型 https://ai-maas.wair.ac.cn
 TAICHU_API_KEY = ""
 
-# Grok API KEY
-GROK_API_KEY = ""
 
 # Mathpix 拥有执行PDF的OCR功能，但是需要注册账号
 MATHPIX_APPID = ""
@@ -310,8 +273,8 @@ GROBID_URLS = [
 ]
 
 
-# Searxng互联网检索服务（这是一个huggingface空间，请前往huggingface复制该空间，然后把自己新的空间地址填在这里）
+# Searxng互联网检索服务
-SEARXNG_URLS = [ f"https://kaletianlre-beardvs{i}dd.hf.space/" for i in range(1,5) ]
+SEARXNG_URL = "https://cloud-1.agent-matrix.com/"
 
 
 # 是否允许通过自然语言描述修改本页的配置，该功能具有一定的危险性，默认关闭
@@ -335,7 +298,7 @@ ARXIV_CACHE_DIR = "gpt_log/arxiv_cache"
 
 
 # 除了连接OpenAI之外，还有哪些场合允许使用代理，请尽量不要修改
-WHEN_TO_USE_PROXY = ["Connect_OpenAI", "Download_LLM", "Download_Gradio_Theme", "Connect_Grobid",
+WHEN_TO_USE_PROXY = ["Download_LLM", "Download_Gradio_Theme", "Connect_Grobid",
                      "Warmup_Modules", "Nougat_Download", "AutoGen", "Connect_OpenAI_Embedding"]
 
 
@@ -347,23 +310,6 @@ PLUGIN_HOT_RELOAD = False
 NUM_CUSTOM_BASIC_BTN = 4
 
 
-# 媒体智能体的服务地址（这是一个huggingface空间，请前往huggingface复制该空间，然后把自己新的空间地址填在这里）
-DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in range(1,5) ]
-
-
-# 在互联网搜索组件中，负责将搜索结果整理成干净的Markdown
-JINA_API_KEY = ""
-
-
-# 是否自动裁剪上下文长度（是否启动，默认不启动）
-AUTO_CONTEXT_CLIP_ENABLE = False
-# 目标裁剪上下文的token长度（如果超过这个长度，则会自动裁剪）
-AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN = 30*1000
-# 无条件丢弃x以上的轮数
-AUTO_CONTEXT_MAX_ROUND = 64
-# 在裁剪上下文时，倒数第x次对话能“最多”保留的上下文token的比例占 AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN 的多少
-AUTO_CONTEXT_MAX_CLIP_RATIO = [0.80, 0.60, 0.45, 0.25, 0.20, 0.18, 0.16, 0.14, 0.12, 0.10, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01]
-
 
 """
 --------------- 配置关联关系说明 ---------------
@@ -423,7 +369,6 @@ AUTO_CONTEXT_MAX_CLIP_RATIO = [0.80, 0.60, 0.45, 0.25, 0.20, 0.18, 0.16, 0.14, 0
 
 本地大模型示意图
 │
-├── "chatglm4"
 ├── "chatglm3"
 ├── "chatglm"
 ├── "chatglm_onnx"
@@ -454,7 +399,7 @@ AUTO_CONTEXT_MAX_CLIP_RATIO = [0.80, 0.60, 0.45, 0.25, 0.20, 0.18, 0.16, 0.14, 0
 插件在线服务配置依赖关系示意图
 │
 ├── 互联网检索
-│   └── SEARXNG_URLS
+│   └── SEARXNG_URL
 │
 ├── 语音功能
 │   ├── ENABLE_AUDIO

config_private.py

@@ -1,444 +0,0 @@
-"""
-    以下所有配置也都支持利用环境变量覆写，环境变量配置格式见docker-compose.yml。
-    读取优先级：环境变量 > config_private.py > config.py
-    --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- --- ---
-    All the following configurations also support using environment variables to override,
-    and the environment variable configuration format can be seen in docker-compose.yml.
-    Configuration reading priority: environment variable > config_private.py > config.py
-"""
-
-# [step 1-1]>> ( 接入GPT等模型 ) API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
-API_KEY = "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"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey1,fkxxxx-api2dkey2"
-
-# [step 1-2]>> ( 接入通义 qwen-max ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/
-DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY
-
-# [step 1-3]>> ( 接入 deepseek-reasoner, 即 deepseek-r1 ) 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
-DEEPSEEK_API_KEY = "sk-d99b8cc6b7414cc88a5d950a3ff7585e"
-
-# [step 2]>> 改为True应用代理。如果使用本地或无地域限制的大模型时，此处不修改；如果直接在海外服务器部署，此处不修改
-USE_PROXY = True
-if USE_PROXY:
-    proxies = {
-        "http":"socks5h://192.168.8.9:1070",  # 再例如  "http":  "http://127.0.0.1:7890",
-        "https":"socks5h://192.168.8.9:1070",  # 再例如  "https": "http://127.0.0.1:7890",
-    }
-else:
-    proxies = None
-DEFAULT_WORKER_NUM = 256
-
-# [step 3]>> 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
-LLM_MODEL = "gpt-4-32k" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["deepseek-chat", "deepseek-coder", "deepseek-reasoner",
-                    "gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-preview",
-                    "gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4-turbo-2024-04-09",
-                    "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
-                    "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo",
-                    "gemini-1.5-pro", "chatglm3", "chatglm4",
-                    ]
-
-EMBEDDING_MODEL = "text-embedding-3-small"
-
-# --- --- --- ---
-# P.S. 其他可用的模型还包括
-# AVAIL_LLM_MODELS = [
-#   "glm-4-0520", "glm-4-air", "glm-4-airx", "glm-4-flash",
-#   "qianfan", "deepseekcoder",
-#   "spark", "sparkv2", "sparkv3", "sparkv3.5", "sparkv4",
-#   "qwen-turbo", "qwen-plus", "qwen-local",
-#   "moonshot-v1-128k", "moonshot-v1-32k", "moonshot-v1-8k",
-#   "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo-0125", "gpt-4o-2024-05-13"
-#   "claude-3-haiku-20240307","claude-3-sonnet-20240229","claude-3-opus-20240229", "claude-2.1", "claude-instant-1.2",
-#   "moss", "llama2", "chatglm_onnx", "internlm", "jittorllms_pangualpha", "jittorllms_llama",
-#   "deepseek-chat" ,"deepseek-coder",
-#   "gemini-1.5-flash",
-#   "yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview",
-#   "grok-beta",
-# ]
-# --- --- --- ---
-# 此外，您还可以在接入one-api/vllm/ollama/Openroute时，
-# 使用"one-api-*","vllm-*","ollama-*","openrouter-*"前缀直接使用非标准方式接入的模型，例如
-# AVAIL_LLM_MODELS = ["one-api-claude-3-sonnet-20240229(max_token=100000)", "ollama-phi3(max_token=4096)","openrouter-openai/gpt-4o-mini","openrouter-openai/chatgpt-4o-latest"]
-# --- --- --- ---
-
-
-# --------------- 以下配置可以优化体验 ---------------
-
-# 重新URL重新定向，实现更换API_URL的作用（高危设置! 常规情况下不要修改! 通过修改此设置，您将把您的API-KEY和对话隐私完全暴露给您设定的中间人！）
-# 格式: API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "在这里填写重定向的api.openai.com的URL"}
-# 举例: API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "https://reverse-proxy-url/v1/chat/completions", "http://localhost:11434/api/chat": "在这里填写您ollama的URL"}
-API_URL_REDIRECT = {}
-
-
-# 多线程函数插件中，默认允许多少路线程同时访问OpenAI。Free trial users的限制是每分钟3次，Pay-as-you-go users的限制是每分钟3500次
-# 一言以蔽之：免费（5刀）用户填3，OpenAI绑了信用卡的用户可以填 16 或者更高。提高限制请查询：https://platform.openai.com/docs/guides/rate-limits/overview
-DEFAULT_WORKER_NUM = 64
-
-
-# 色彩主题, 可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
-# 更多主题, 请查阅Gradio主题商店: https://huggingface.co/spaces/gradio/theme-gallery 可选 ["Gstaff/Xkcd", "NoCrypt/Miku", ...]
-THEME = "Default"
-AVAIL_THEMES = ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast", "Gstaff/Xkcd", "NoCrypt/Miku"]
-
-FONT = "Theme-Default-Font"
-AVAIL_FONTS = [
-    "默认值(Theme-Default-Font)",
-    "宋体(SimSun)",
-    "黑体(SimHei)",
-    "楷体(KaiTi)",
-    "仿宋(FangSong)",
-    "华文细黑(STHeiti Light)",
-    "华文楷体(STKaiti)",
-    "华文仿宋(STFangsong)",
-    "华文宋体(STSong)",
-    "华文中宋(STZhongsong)",
-    "华文新魏(STXinwei)",
-    "华文隶书(STLiti)",
-    "思源宋体(Source Han Serif CN VF@https://chinese-fonts-cdn.deno.dev/packages/syst/dist/SourceHanSerifCN/result.css)",
-    "月星楷(Moon Stars Kai HW@https://chinese-fonts-cdn.deno.dev/packages/moon-stars-kai/dist/MoonStarsKaiHW-Regular/result.css)",
-    "珠圆体(MaokenZhuyuanTi@https://chinese-fonts-cdn.deno.dev/packages/mkzyt/dist/猫啃珠圆体/result.css)",
-    "平方萌萌哒(PING FANG MENG MNEG DA@https://chinese-fonts-cdn.deno.dev/packages/pfmmd/dist/平方萌萌哒/result.css)",
-    "Helvetica",
-    "ui-sans-serif",
-    "sans-serif",
-    "system-ui"
-]
-
-
-# 默认的系统提示词（system prompt）
-INIT_SYS_PROMPT = " "
-
-
-# 对话窗的高度 （仅在LAYOUT="TOP-DOWN"时生效）
-CHATBOT_HEIGHT = 1115
-
-
-# 代码高亮
-CODE_HIGHLIGHT = True
-
-
-# 窗口布局
-LAYOUT = "LEFT-RIGHT"   # "LEFT-RIGHT"（左右布局） # "TOP-DOWN"（上下布局）
-
-
-# 暗色模式 / 亮色模式
-DARK_MODE = True
-
-
-# 发送请求到OpenAI后，等待多久判定为超时
-TIMEOUT_SECONDS = 60
-
-
-# 网页的端口, -1代表随机端口
-WEB_PORT = 19998
-
-# 是否自动打开浏览器页面
-AUTO_OPEN_BROWSER = True
-
-
-# 如果OpenAI不响应（网络卡顿、代理失败、KEY失效），重试的次数限制
-MAX_RETRY = 5
-
-
-# 插件分类默认选项
-DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
-
-
-# 定义界面上“询问多个GPT模型”插件应该使用哪些模型，请从AVAIL_LLM_MODELS中选择，并在不同模型之间用`&`间隔，例如"gpt-3.5-turbo&chatglm3&azure-gpt-4"
-MULTI_QUERY_LLM_MODELS = "gpt-3.5-turbo&chatglm3"
-
-
-# 选择本地模型变体（只有当AVAIL_LLM_MODELS包含了对应本地模型时，才会起作用）
-# 如果你选择Qwen系列的模型，那么请在下面的QWEN_MODEL_SELECTION中指定具体的模型
-# 也可以是具体的模型路径
-QWEN_LOCAL_MODEL_SELECTION = "Qwen/Qwen-1_8B-Chat-Int8"
-
-
-# 百度千帆（LLM_MODEL="qianfan"）
-BAIDU_CLOUD_API_KEY = ''
-BAIDU_CLOUD_SECRET_KEY = ''
-BAIDU_CLOUD_QIANFAN_MODEL = 'ERNIE-Bot'    # 可选 "ERNIE-Bot-4"(文心大模型4.0), "ERNIE-Bot"(文心一言), "ERNIE-Bot-turbo", "BLOOMZ-7B", "Llama-2-70B-Chat", "Llama-2-13B-Chat", "Llama-2-7B-Chat", "ERNIE-Speed-128K", "ERNIE-Speed-8K", "ERNIE-Lite-8K"
-
-
-# 如果使用ChatGLM3或ChatGLM4本地模型，请把 LLM_MODEL="chatglm3" 或LLM_MODEL="chatglm4"，并在此处指定模型路径
-CHATGLM_LOCAL_MODEL_PATH = "THUDM/glm-4-9b-chat" # 例如"/home/hmp/ChatGLM3-6B/"
-
-# 如果使用ChatGLM2微调模型，请把 LLM_MODEL="chatglmft"，并在此处指定模型路径
-CHATGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b-pt-128-1e-2/checkpoint-100"
-
-
-# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
-LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
-LOCAL_MODEL_QUANT = "FP16" # 默认 "FP16" "INT4" 启用量化INT4版本 "INT8" 启用量化INT8版本
-
-
-# 设置gradio的并行线程数（不需要修改）
-CONCURRENT_COUNT = 100
-
-
-# 是否在提交时自动清空输入框
-AUTO_CLEAR_TXT = False
-
-
-# 加一个live2d装饰
-ADD_WAIFU = False
-
-
-# 设置用户名和密码（不需要修改）（相关功能不稳定，与gradio版本和网络都相关，如果本地使用不建议加这个）
-# [("username", "password"), ("username2", "password2"), ...]
-AUTHENTICATION = [("van", "L807878712"),("林", "L807878712"),("源", "L807878712"),("欣", "L807878712"),("z", "czh123456789")]
-
-
-# 如果需要在二级路径下运行（常规情况下，不要修改!!）
-# （举例 CUSTOM_PATH = "/gpt_academic"，可以让软件运行在 http://ip:port/gpt_academic/ 下。）
-CUSTOM_PATH = "/"
-
-
-# HTTPS 秘钥和证书（不需要修改）
-SSL_KEYFILE = ""
-SSL_CERTFILE = ""
-
-
-# 极少数情况下，openai的官方KEY需要伴随组织编码（格式如org-xxxxxxxxxxxxxxxxxxxxxxxx）使用
-API_ORG = ""
-
-
-# 如果需要使用Slack Claude，使用教程详情见 request_llms/README.md
-SLACK_CLAUDE_BOT_ID = ''
-SLACK_CLAUDE_USER_TOKEN = ''
-
-
-# 如果需要使用AZURE（方法一：单个azure模型部署）详情请见额外文档 docs\use_azure.md
-AZURE_ENDPOINT = "https://你亲手写的api名称.openai.azure.com/"
-AZURE_API_KEY = "填入azure openai api的密钥"    # 建议直接在API_KEY处填写，该选项即将被弃用
-AZURE_ENGINE = "填入你亲手写的部署名"            # 读 docs\use_azure.md
-
-
-# 如果需要使用AZURE（方法二：多个azure模型部署+动态切换）详情请见额外文档 docs\use_azure.md
-AZURE_CFG_ARRAY = {}
-
-
-# 阿里云实时语音识别 配置难度较高
-# 参考 https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md
-ENABLE_AUDIO = False
-ALIYUN_TOKEN=""     # 例如 f37f30e0f9934c34a992f6f64f7eba4f
-ALIYUN_APPKEY=""    # 例如 RoPlZrM88DnAFkZK
-ALIYUN_ACCESSKEY="" # （无需填写）
-ALIYUN_SECRET=""    # （无需填写）
-
-
-# GPT-SOVITS 文本转语音服务的运行地址（将语言模型的生成文本朗读出来）
-TTS_TYPE = "DISABLE" # EDGE_TTS / LOCAL_SOVITS_API / DISABLE
-GPT_SOVITS_URL = ""
-EDGE_TTS_VOICE = "zh-CN-XiaoxiaoNeural"
-
-
-# 接入讯飞星火大模型 https://console.xfyun.cn/services/iat
-XFYUN_APPID = "00000000"
-XFYUN_API_SECRET = "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb"
-XFYUN_API_KEY = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
-
-
-# 接入智谱大模型
-ZHIPUAI_API_KEY = ""
-ZHIPUAI_MODEL = "" # 此选项已废弃，不再需要填写
-
-
-# Claude API KEY
-ANTHROPIC_API_KEY = ""
-
-
-# 月之暗面 API KEY
-MOONSHOT_API_KEY = ""
-
-
-# 零一万物(Yi Model) API KEY
-YIMODEL_API_KEY = ""
-
-
-# 紫东太初大模型 https://ai-maas.wair.ac.cn
-TAICHU_API_KEY = ""
-
-# Grok API KEY
-GROK_API_KEY = ""
-
-# Mathpix 拥有执行PDF的OCR功能，但是需要注册账号
-MATHPIX_APPID = ""
-MATHPIX_APPKEY = ""
-
-
-# DOC2X的PDF解析服务，注册账号并获取API KEY: https://doc2x.noedgeai.com/login
-DOC2X_API_KEY = ""
-
-
-# 自定义API KEY格式
-CUSTOM_API_KEY_PATTERN = ""
-
-
-# Google Gemini API-Key
-GEMINI_API_KEY = ''
-
-
-# HUGGINGFACE的TOKEN，下载LLAMA时起作用 https://huggingface.co/docs/hub/security-tokens
-HUGGINGFACE_ACCESS_TOKEN = "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"
-
-
-# GROBID服务器地址（填写多个可以均衡负载），用于高质量地读取PDF文档
-# 获取方法：复制以下空间https://huggingface.co/spaces/qingxu98/grobid，设为public，然后GROBID_URL = "https://(你的hf用户名如qingxu98)-(你的填写的空间名如grobid).hf.space"
-GROBID_URLS = [
-    "https://qingxu98-grobid.hf.space","https://qingxu98-grobid2.hf.space","https://qingxu98-grobid3.hf.space",
-    "https://qingxu98-grobid4.hf.space","https://qingxu98-grobid5.hf.space", "https://qingxu98-grobid6.hf.space",
-    "https://qingxu98-grobid7.hf.space", "https://qingxu98-grobid8.hf.space",
-]
-
-
-# Searxng互联网检索服务（这是一个huggingface空间，请前往huggingface复制该空间，然后把自己新的空间地址填在这里）
-SEARXNG_URLS = [ f"https://kaletianlre-beardvs{i}dd.hf.space/" for i in range(1,5) ]
-
-
-# 是否允许通过自然语言描述修改本页的配置，该功能具有一定的危险性，默认关闭
-ALLOW_RESET_CONFIG = False
-
-
-# 在使用AutoGen插件时，是否使用Docker容器运行代码
-AUTOGEN_USE_DOCKER = False
-
-
-# 临时的上传文件夹位置，请尽量不要修改
-PATH_PRIVATE_UPLOAD = "private_upload"
-
-
-# 日志文件夹的位置，请尽量不要修改
-PATH_LOGGING = "gpt_log"
-
-
-# 存储翻译好的arxiv论文的路径，请尽量不要修改
-ARXIV_CACHE_DIR = "gpt_log/arxiv_cache"
-
-
-# 除了连接OpenAI之外，还有哪些场合允许使用代理，请尽量不要修改
-WHEN_TO_USE_PROXY = ["Connect_OpenAI", "Download_LLM", "Download_Gradio_Theme", "Connect_Grobid",
-                     "Warmup_Modules", "Nougat_Download", "AutoGen", "Connect_OpenAI_Embedding"]
-
-
-# 启用插件热加载
-PLUGIN_HOT_RELOAD = False
-
-
-# 自定义按钮的最大数量限制
-NUM_CUSTOM_BASIC_BTN = 4
-
-
-# 媒体智能体的服务地址（这是一个huggingface空间，请前往huggingface复制该空间，然后把自己新的空间地址填在这里）
-DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in range(1,5) ]
-
-
-
-"""
---------------- 配置关联关系说明 ---------------
-
-在线大模型配置关联关系示意图
-│
-├── "gpt-3.5-turbo" 等openai模型
-│   ├── API_KEY
-│   ├── CUSTOM_API_KEY_PATTERN（不常用）
-│   ├── API_ORG（不常用）
-│   └── API_URL_REDIRECT（不常用）
-│
-├── "azure-gpt-3.5" 等azure模型（单个azure模型，不需要动态切换）
-│   ├── API_KEY
-│   ├── AZURE_ENDPOINT
-│   ├── AZURE_API_KEY
-│   ├── AZURE_ENGINE
-│   └── API_URL_REDIRECT
-│
-├── "azure-gpt-3.5" 等azure模型（多个azure模型，需要动态切换，高优先级）
-│   └── AZURE_CFG_ARRAY
-│
-├── "spark" 星火认知大模型 spark & sparkv2
-│   ├── XFYUN_APPID
-│   ├── XFYUN_API_SECRET
-│   └── XFYUN_API_KEY
-│
-├── "claude-3-opus-20240229" 等claude模型
-│   └── ANTHROPIC_API_KEY
-│
-├── "stack-claude"
-│   ├── SLACK_CLAUDE_BOT_ID
-│   └── SLACK_CLAUDE_USER_TOKEN
-│
-├── "qianfan" 百度千帆大模型库
-│   ├── BAIDU_CLOUD_QIANFAN_MODEL
-│   ├── BAIDU_CLOUD_API_KEY
-│   └── BAIDU_CLOUD_SECRET_KEY
-│
-├── "glm-4", "glm-3-turbo", "zhipuai" 智谱AI大模型
-│   └── ZHIPUAI_API_KEY
-│
-├── "yi-34b-chat-0205", "yi-34b-chat-200k" 等零一万物(Yi Model)大模型
-│   └── YIMODEL_API_KEY
-│
-├── "qwen-turbo" 等通义千问大模型
-│   └──  DASHSCOPE_API_KEY
-│
-├── "Gemini"
-│   └──  GEMINI_API_KEY
-│
-└── "one-api-...(max_token=...)" 用一种更方便的方式接入one-api多模型管理界面
-    ├── AVAIL_LLM_MODELS
-    ├── API_KEY
-    └── API_URL_REDIRECT
-
-
-本地大模型示意图
-│
-├── "chatglm4"
-├── "chatglm3"
-├── "chatglm"
-├── "chatglm_onnx"
-├── "chatglmft"
-├── "internlm"
-├── "moss"
-├── "jittorllms_pangualpha"
-├── "jittorllms_llama"
-├── "deepseekcoder"
-├── "qwen-local"
-├──  RWKV的支持见Wiki
-└── "llama2"
-
-
-用户图形界面布局依赖关系示意图
-│
-├── CHATBOT_HEIGHT 对话窗的高度
-├── CODE_HIGHLIGHT 代码高亮
-├── LAYOUT 窗口布局
-├── DARK_MODE 暗色模式 / 亮色模式
-├── DEFAULT_FN_GROUPS 插件分类默认选项
-├── THEME 色彩主题
-├── AUTO_CLEAR_TXT 是否在提交时自动清空输入框
-├── ADD_WAIFU 加一个live2d装饰
-└── ALLOW_RESET_CONFIG 是否允许通过自然语言描述修改本页的配置，该功能具有一定的危险性
-
-
-插件在线服务配置依赖关系示意图
-│
-├── 互联网检索
-│   └── SEARXNG_URLS
-│
-├── 语音功能
-│   ├── ENABLE_AUDIO
-│   ├── ALIYUN_TOKEN
-│   ├── ALIYUN_APPKEY
-│   ├── ALIYUN_ACCESSKEY
-│   └── ALIYUN_SECRET
-│
-└── PDF文档精准解析
-    ├── GROBID_URLS
-    ├── MATHPIX_APPID
-    └── MATHPIX_APPKEY
-
-
-"""
-
-
-

crazy_functional.py

@@ -2,6 +2,7 @@ from toolbox import HotReload  # HotReload 的意思是热更新，修改函数
 from toolbox import trimmed_format_exc
 from loguru import logger
 
+
 def get_crazy_functions():
     from crazy_functions.读文章写摘要 import 读文章写摘要
     from crazy_functions.生成函数注释 import 批量生成函数注释
@@ -16,7 +17,7 @@ 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_Project_Polish import Latex英文润色
+    from crazy_functions.Latex全文润色 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
@@ -27,13 +28,14 @@ def get_crazy_functions():
     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_Project_Polish import Latex中文润色
+    from crazy_functions.Latex全文润色 import Latex中文润色
-    from crazy_functions.Latex_Project_Polish import Latex英文纠错
+    from crazy_functions.Latex全文润色 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
@@ -49,16 +51,8 @@ def get_crazy_functions():
     from crazy_functions.Image_Generate_Wrap import ImageGen_Wrap
     from crazy_functions.SourceCode_Comment import 注释Python项目
     from crazy_functions.SourceCode_Comment_Wrap import SourceCodeComment_Wrap
-    from crazy_functions.VideoResource_GPT import 多媒体任务
 
     function_plugins = {
-        "多媒体智能体": {
-            "Group": "智能体",
-            "Color": "stop",
-            "AsButton": False,
-            "Info": "【仅测试】多媒体任务",
-            "Function": HotReload(多媒体任务),
-        },
         "虚空终端": {
             "Group": "对话|编程|学术|智能体",
             "Color": "stop",
@@ -113,16 +107,17 @@ def get_crazy_functions():
             "Group": "学术",
             "Color": "stop",
             "AsButton": True,
-            "Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
+            "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
             "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
         },
-        "批量总结Word文档": {
+        "批量文件询问": {
             "Group": "学术",
             "Color": "stop",
             "AsButton": False,
-            "Info": "批量总结word文档 | 输入参数为路径",
+            "AdvancedArgs": True,
-            "Function": HotReload(总结word文档),
+            "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),
         },
         "解析整个Matlab项目": {
             "Group": "编程",
@@ -245,7 +240,7 @@ def get_crazy_functions():
             "AsButton": True,  # 加入下拉菜单中
             # "Info": "连接网络回答问题（需要访问谷歌）| 输入参数是一个问题",
             "Function": HotReload(连接网络回答问题),
-            "Class": NetworkGPT_Wrap     # 新一代插件需要注册Class
+            # "Class": NetworkGPT_Wrap     # 新一代插件需要注册Class
         },
         "历史上的今天": {
             "Group": "对话",
@@ -352,7 +347,7 @@ def get_crazy_functions():
             "ArgsReminder": r"如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "
                             r"例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: "
                             r'If the term "agent" is used in this section, it should be translated to "智能体". ',
-            "Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
+            "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
             "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
         },
@@ -434,6 +429,36 @@ def get_crazy_functions():
         logger.error(trimmed_format_exc())
         logger.error("Load function plugin failed")
 
+    # try:
+    #     from crazy_functions.联网的ChatGPT import 连接网络回答问题
+
+    #     function_plugins.update(
+    #         {
+    #             "连接网络回答问题（输入问题后点击该插件，需要访问谷歌）": {
+    #                 "Group": "对话",
+    #                 "Color": "stop",
+    #                 "AsButton": False,  # 加入下拉菜单中
+    #                 # "Info": "连接网络回答问题（需要访问谷歌）| 输入参数是一个问题",
+    #                 "Function": HotReload(连接网络回答问题),
+    #             }
+    #         }
+    #     )
+    #     from crazy_functions.联网的ChatGPT_bing版 import 连接bing搜索回答问题
+
+    #     function_plugins.update(
+    #         {
+    #             "连接网络回答问题（中文Bing版，输入问题后点击该插件）": {
+    #                 "Group": "对话",
+    #                 "Color": "stop",
+    #                 "AsButton": False,  # 加入下拉菜单中
+    #                 "Info": "连接网络回答问题（需要访问中文Bing）| 输入参数是一个问题",
+    #                 "Function": HotReload(连接bing搜索回答问题),
+    #             }
+    #         }
+    #     )
+    # except:
+    #     logger.error(trimmed_format_exc())
+    #     logger.error("Load function plugin failed")
 
     try:
         from crazy_functions.SourceCode_Analyse import 解析任意code项目
@@ -697,6 +722,12 @@ def get_crazy_functions():
         logger.error("Load function plugin failed")
 
 
+    
+
+
+
+
+
     # try:
     #     from crazy_functions.高级功能函数模板 import 测试图表渲染
     #     function_plugins.update({
@@ -711,6 +742,19 @@ 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:
@@ -730,26 +774,3 @@ def get_crazy_functions():
             function_plugins[name]["Color"] = "secondary"
 
     return function_plugins
-
-
-
-
-def get_multiplex_button_functions():
-    """多路复用主提交按钮的功能映射
-    """
-    return {
-        "常规对话":
-            "",
-
-        "查互联网后回答":
-            "查互联网后回答",
-
-        "多模型对话": 
-            "询问多个GPT模型", # 映射到上面的 `询问多个GPT模型` 插件
-
-        "智能召回 RAG": 
-            "Rag智能召回", # 映射到上面的 `Rag智能召回` 插件
-
-        "多媒体查询": 
-            "多媒体智能体", # 映射到上面的 `多媒体智能体` 插件
-    }

crazy_functions/Conversation_To_File.py

@@ -1,11 +1,10 @@
-import re
+from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user
-from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user, update_ui_latest_msg
 from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
-from loguru import logger
+import re
 
 f_prefix = 'GPT-Academic对话存档'
 
-def write_chat_to_file_legacy(chatbot, history=None, file_name=None):
+def write_chat_to_file(chatbot, history=None, file_name=None):
     """
     将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
     """
@@ -13,9 +12,6 @@ def write_chat_to_file_legacy(chatbot, history=None, file_name=None):
     import time
     from themes.theme import advanced_css
 
-    if (file_name is not None) and (file_name != "") and (not file_name.endswith('.html')): file_name += '.html'
-    else: file_name = None
-
     if file_name is None:
         file_name = f_prefix + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
     fp = os.path.join(get_log_folder(get_user(chatbot), plugin_name='chat_history'), file_name)
@@ -72,147 +68,6 @@ def write_chat_to_file_legacy(chatbot, history=None, file_name=None):
     promote_file_to_downloadzone(fp, rename_file=file_name, chatbot=chatbot)
     return '对话历史写入：' + fp
 
-def write_chat_to_file(chatbot, history=None, file_name=None):
-    """
-    将对话记录history以多种格式（HTML、Word、Markdown）写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
-    
-    Args:
-        chatbot: 聊天机器人对象，包含对话内容
-        history: 对话历史记录
-        file_name: 指定的文件名，如果为None则使用时间戳
-        
-    Returns:
-        str: 提示信息，包含文件保存路径
-    """
-    import os
-    import time
-    import asyncio
-    import aiofiles
-    from toolbox import promote_file_to_downloadzone
-    from crazy_functions.doc_fns.conversation_doc.excel_doc import save_chat_tables
-    from crazy_functions.doc_fns.conversation_doc.html_doc import HtmlFormatter
-    from crazy_functions.doc_fns.conversation_doc.markdown_doc import MarkdownFormatter
-    from crazy_functions.doc_fns.conversation_doc.word_doc import WordFormatter
-    from crazy_functions.doc_fns.conversation_doc.txt_doc import TxtFormatter
-    from crazy_functions.doc_fns.conversation_doc.word2pdf import WordToPdfConverter
-
-    async def save_html():
-        try:
-            html_formatter = HtmlFormatter(chatbot, history)
-            html_content = html_formatter.create_document()
-            html_file = os.path.join(save_dir, base_name + '.html')
-            async with aiofiles.open(html_file, 'w', encoding='utf8') as f:
-                await f.write(html_content)
-            return html_file
-        except Exception as e:
-            print(f"保存HTML格式失败: {str(e)}")
-            return None
-
-    async def save_word():
-        try:
-            word_formatter = WordFormatter()
-            doc = word_formatter.create_document(history)
-            docx_file = os.path.join(save_dir, base_name + '.docx')
-            # 由于python-docx不支持异步，使用线程池执行
-            loop = asyncio.get_event_loop()
-            await loop.run_in_executor(None, doc.save, docx_file)
-            return docx_file
-        except Exception as e:
-            print(f"保存Word格式失败: {str(e)}")
-            return None
-    async def save_pdf(docx_file):
-        try:
-            if docx_file:
-                # 获取文件名和保存路径
-                pdf_file = os.path.join(save_dir, base_name + '.pdf')
-                
-                # 在线程池中执行转换
-                loop = asyncio.get_event_loop()
-                pdf_file = await loop.run_in_executor(
-                    None, 
-                    WordToPdfConverter.convert_to_pdf,
-                    docx_file
-                    # save_dir
-                )
-                
-                return pdf_file
-                
-        except Exception as e:
-            print(f"保存PDF格式失败: {str(e)}")
-            return None
-
-    async def save_markdown():
-        try:
-            md_formatter = MarkdownFormatter()
-            md_content = md_formatter.create_document(history)
-            md_file = os.path.join(save_dir, base_name + '.md')
-            async with aiofiles.open(md_file, 'w', encoding='utf8') as f:
-                await f.write(md_content)
-            return md_file
-        except Exception as e:
-            print(f"保存Markdown格式失败: {str(e)}")
-            return None
-
-    async def save_txt():
-        try:
-            txt_formatter = TxtFormatter()
-            txt_content = txt_formatter.create_document(history)
-            txt_file = os.path.join(save_dir, base_name + '.txt')
-            async with aiofiles.open(txt_file, 'w', encoding='utf8') as f:
-                await f.write(txt_content)
-            return txt_file
-        except Exception as e:
-            print(f"保存TXT格式失败: {str(e)}")
-            return None
-
-    async def main():
-        # 并发执行所有保存任务
-        html_task = asyncio.create_task(save_html())
-        word_task = asyncio.create_task(save_word())
-        md_task = asyncio.create_task(save_markdown())
-        txt_task = asyncio.create_task(save_txt())
-        
-        # 等待所有任务完成
-        html_file = await html_task
-        docx_file = await word_task
-        md_file = await md_task
-        txt_file = await txt_task
-        
-        # PDF转换需要等待word文件生成完成
-        pdf_file = await save_pdf(docx_file)
-        # 收集所有成功生成的文件
-        result_files = [f for f in [html_file, docx_file, md_file, txt_file, pdf_file] if f]
-        
-        # 保存Excel表格
-        excel_files = save_chat_tables(history, save_dir, base_name)
-        result_files.extend(excel_files)
-        
-        return result_files
-
-    # 生成时间戳
-    timestamp = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
-    
-    # 获取保存目录
-    save_dir = get_log_folder(get_user(chatbot), plugin_name='chat_history')
-    
-    # 处理文件名
-    base_name = file_name if file_name else f"聊天记录_{timestamp}"
-    
-    # 运行异步任务
-    result_files = asyncio.run(main())
-    
-    # 将生成的文件添加到下载区
-    for file in result_files:
-        promote_file_to_downloadzone(file, rename_file=os.path.basename(file), chatbot=chatbot)
-    
-    # 如果没有成功保存任何文件，返回错误信息
-    if not result_files:
-        return "保存对话记录失败，请检查错误日志"
-    
-    ext_list = [os.path.splitext(f)[1] for f in result_files]
-    # 返回成功信息和文件路径
-    return f"对话历史已保存至以下格式文件：" + "、".join(ext_list)
-
 def gen_file_preview(file_name):
     try:
         with open(file_name, 'r', encoding='utf8') as f:
@@ -264,21 +119,12 @@ def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
     user_request    当前用户的请求信息（IP地址等）
     """
     file_name = plugin_kwargs.get("file_name", None)
+    if (file_name is not None) and (file_name != "") and (not file_name.endswith('.html')): file_name += '.html'
+    else: file_name = None
+
+    chatbot.append((None, f"[Local Message] {write_chat_to_file(chatbot, history, file_name)}，您可以调用下拉菜单中的“载入对话历史存档”还原当下的对话。"))
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
 
-    chatbot.append((None, f"[Local Message] {write_chat_to_file_legacy(chatbot, history, file_name)}，您可以调用下拉菜单中的“载入对话历史存档”还原当下的对话。"))
-    try:
-        chatbot.append((None, f"[Local Message] 正在尝试生成pdf以及word格式的对话存档，请稍等..."))
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求需要一段时间，我们先及时地做一次界面更新
-        lastmsg = f"[Local Message] {write_chat_to_file(chatbot, history, file_name)}。" \
-              f"您可以调用下拉菜单中的“载入对话历史会话”还原当下的对话，请注意，目前只支持html格式载入历史。" \
-              f"当模型回答中存在表格，将提取表格内容存储为Excel的xlsx格式，如果你提供一些数据,然后输入指令要求模型帮你整理为表格" \
-              f"（如“请帮我将下面的数据整理为表格：”），再利用此插件就可以获取到Excel表格。"
-        yield from update_ui_latest_msg(lastmsg, chatbot, history) # 刷新界面 # 由于请求需要一段时间，我们先及时地做一次界面更新
-    except Exception as e:
-        logger.exception(f"已完成对话存档（pdf和word格式的对话存档生成未成功）。{str(e)}")
-        lastmsg = "已完成对话存档（pdf和word格式的对话存档生成未成功）。"
-        yield from update_ui_latest_msg(lastmsg, chatbot, history) # 刷新界面 # 由于请求需要一段时间，我们先及时地做一次界面更新
-    return
 
 class Conversation_To_File_Wrap(GptAcademicPluginTemplate):
     def __init__(self):

crazy_functions/Internet_GPT.py

@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
 from functools import lru_cache
 from itertools import zip_longest
 from check_proxy import check_proxy
-from toolbox import CatchException, update_ui, get_conf, update_ui_latest_msg
+from toolbox import CatchException, update_ui, get_conf
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
 from request_llms.bridge_all import model_info
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -49,7 +49,7 @@ def search_optimizer(
     mutable = ["", time.time(), ""]
     llm_kwargs["temperature"] = 0.8
     try:
-        query_json = predict_no_ui_long_connection(
+        querys_json = predict_no_ui_long_connection(
             inputs=query,
             llm_kwargs=llm_kwargs,
             history=[],
@@ -57,31 +57,31 @@ def search_optimizer(
             observe_window=mutable,
         )
     except Exception:
-        query_json = "null"
+        querys_json = "1234"
     #* 尝试解码优化后的搜索结果
-    query_json = re.sub(r"```json|```", "", query_json)
+    querys_json = re.sub(r"```json|```", "", querys_json)
     try:
-        queries = json.loads(query_json)
+        querys = json.loads(querys_json)
     except Exception:
         #* 如果解码失败,降低温度再试一次
         try:
             llm_kwargs["temperature"] = 0.4
-            query_json = predict_no_ui_long_connection(
+            querys_json = predict_no_ui_long_connection(
                 inputs=query,
                 llm_kwargs=llm_kwargs,
                 history=[],
                 sys_prompt=sys_prompt,
                 observe_window=mutable,
             )
-            query_json = re.sub(r"```json|```", "", query_json)
+            querys_json = re.sub(r"```json|```", "", querys_json)
-            queries = json.loads(query_json)
+            querys = json.loads(querys_json)
         except Exception:
             #* 如果再次失败，直接返回原始问题
-            queries = [query]
+            querys = [query]
     links = []
     success = 0
     Exceptions = ""
-    for q in queries:
+    for q in querys:
         try:
             link = searxng_request(q, proxies, categories, searxng_url, engines=engines)
             if len(link) > 0:
@@ -115,8 +115,7 @@ def get_auth_ip():
 
 def searxng_request(query, proxies, categories='general', searxng_url=None, engines=None):
     if searxng_url is None:
-        urls = get_conf("SEARXNG_URLS")
+        url = get_conf("SEARXNG_URL")
-        url = random.choice(urls)
     else:
         url = searxng_url
 
@@ -175,17 +174,10 @@ def scrape_text(url, proxies) -> str:
     Returns:
         str: The scraped text
     """
-    from loguru import logger
     headers = {
         'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
         'Content-Type': 'text/plain',
     }
-
-    # 首先采用Jina进行文本提取
-    if get_conf("JINA_API_KEY"):
-        try: return jina_scrape_text(url)
-        except: logger.debug("Jina API 请求失败，回到旧方法")
-
     try:
         response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
         if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
@@ -201,56 +193,6 @@ def scrape_text(url, proxies) -> str:
     return text
 
 
-def jina_scrape_text(url) -> str:
-    "jina_39727421c8fa4e4fa9bd698e5211feaaDyGeVFESNrRaepWiLT0wmHYJSh-d"
-    headers = {
-        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
-        'Content-Type': 'text/plain',
-        "X-Retain-Images": "none",
-        "Authorization": f'Bearer {get_conf("JINA_API_KEY")}'
-    }
-    response = requests.get("https://r.jina.ai/" + url, headers=headers, proxies=None, timeout=8)
-    if response.status_code != 200:
-        raise ValueError("Jina API 请求失败，开始尝试旧方法！" + response.text)
-    if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
-    result = response.text
-    result = result.replace("\\[", "[").replace("\\]", "]").replace("\\(", "(").replace("\\)", ")")
-    return response.text
-
-
-def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, chatbot):
-    from toolbox import get_conf
-    proxies = get_conf('proxies')
-    categories = 'general'
-    searxng_url = None  # 使用默认的searxng_url
-    engines = None  # 使用默认的搜索引擎
-    yield from update_ui_latest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
-    urls = searxng_request(prompt, proxies, categories, searxng_url, engines=engines)
-    yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
-    if len(urls) == 0:
-        return None
-    max_search_result = 5   # 最多收纳多少个网页的结果
-    history = []
-    for index, url in enumerate(urls[:max_search_result]):
-        yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
-        res = scrape_text(url['link'], proxies)
-        prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
-        history.extend([prefix, res])
-    i_say = f"从以上搜索结果中抽取信息，然后回答问题：{prompt} {analysis_prompt}"
-    i_say, history = input_clipping( # 裁剪输入，从最长的条目开始裁剪，防止爆token
-        inputs=i_say,
-        history=history,
-        max_token_limit=8192
-    )
-    gpt_say = predict_no_ui_long_connection(
-        inputs=i_say,
-        llm_kwargs=llm_kwargs,
-        history=history,
-        sys_prompt="请从搜索结果中抽取信息，对最相关的两个搜索结果进行总结，然后回答问题。",
-        console_silence=False,
-    )
-    return gpt_say
-
 @CatchException
 def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
     optimizer_history = history[:-8]
@@ -271,52 +213,23 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         urls = search_optimizer(txt, proxies, optimizer_history, llm_kwargs, optimizer, categories, searxng_url, engines)
     history = []
     if len(urls) == 0:
-        chatbot.append((f"结论：{txt}", "[Local Message] 受到限制，无法从searxng获取信息！请尝试更换搜索引擎。"))
+        chatbot.append((f"结论：{txt}",
+                        "[Local Message] 受到限制，无法从searxng获取信息！请尝试更换搜索引擎。"))
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         return
 
     # ------------- < 第2步：依次访问网页 > -------------
-    from concurrent.futures import ThreadPoolExecutor
-    from textwrap import dedent
     max_search_result = 5   # 最多收纳多少个网页的结果
     if optimizer == "开启(增强)":
         max_search_result = 8
-    template = dedent("""
+    chatbot.append(["联网检索中 ...", None])
-        <details>
+    for index, url in enumerate(urls[:max_search_result]):
-        <summary>{TITLE}</summary>
+        res = scrape_text(url['link'], proxies)
-        <div class="search_result">{URL}</div>
+        prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
-        <div class="search_result">{CONTENT}</div>
+        history.extend([prefix, res])
-        </details>
+        res_squeeze = res.replace('\n', '...')
-    """)
+        chatbot[-1] = [prefix + "\n\n" + res_squeeze[:500] + "......", None]
-
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-    buffer = ""
-
-    # 创建线程池
-    with ThreadPoolExecutor(max_workers=5) as executor:
-        # 提交任务到线程池
-        futures = []
-        for index, url in enumerate(urls[:max_search_result]):
-            future = executor.submit(scrape_text, url['link'], proxies)
-            futures.append((index, future, url))
-
-        # 处理完成的任务
-        for index, future, url in futures:
-            # 开始
-            prefix = f"正在加载 第{index+1}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
-            string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT="正在加载，请稍后 ......")
-            yield from update_ui_latest_msg(lastmsg=(buffer + string_structure), chatbot=chatbot, history=history, delay=0.1)  # 刷新界面
-
-            # 获取结果
-            res = future.result()
-
-            # 显示结果
-            prefix = f"第{index+1}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
-            string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT=res[:1000] + "......")
-            buffer += string_structure
-
-            # 更新历史
-            history.extend([prefix, res])
-            yield from update_ui_latest_msg(lastmsg=buffer, chatbot=chatbot, history=history, delay=0.1)  # 刷新界面
 
     # ------------- < 第3步：ChatGPT综合 > -------------
     if (optimizer != "开启(增强)"):

crazy_functions/Internet_GPT_Wrap.py

@@ -1,4 +1,4 @@
-import random
+
 from toolbox import get_conf
 from crazy_functions.Internet_GPT import 连接网络回答问题
 from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
@@ -20,9 +20,6 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
         第三个参数，名称`allow_cache`，参数`type`声明这是一个下拉菜单，下拉菜单上方显示`title`+`description`，下拉菜单的选项为`options`，`default_value`为下拉菜单默认值；
 
         """
-        urls = get_conf("SEARXNG_URLS")
-        url = random.choice(urls)
-
         gui_definition = {
             "main_input":
                 ArgProperty(title="输入问题", description="待通过互联网检索的问题，会自动读取输入框内容", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
@@ -33,17 +30,16 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
             "optimizer":
                 ArgProperty(title="搜索优化", options=["关闭", "开启", "开启(增强)"], default_value="关闭", description="是否使用搜索增强。注意这可能会消耗较多token", type="dropdown").model_dump_json(),
             "searxng_url":
-                ArgProperty(title="Searxng服务地址", description="输入Searxng的地址", default_value=url, type="string").model_dump_json(), # 主输入，自动从输入框同步
+                ArgProperty(title="Searxng服务地址", description="输入Searxng的地址", default_value=get_conf("SEARXNG_URL"), type="string").model_dump_json(), # 主输入，自动从输入框同步
 
         }
         return gui_definition
 
-    def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request):
+    def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
         """
         执行插件
         """
-        if plugin_kwargs.get("categories", None) == "网页": plugin_kwargs["categories"] = "general"
+        if plugin_kwargs["categories"] == "网页": plugin_kwargs["categories"] = "general"
-        elif plugin_kwargs.get("categories", None) == "学术论文": plugin_kwargs["categories"] = "science"
+        if plugin_kwargs["categories"] == "学术论文": plugin_kwargs["categories"] = "science"
-        else: plugin_kwargs["categories"] = "general"
         yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
 

crazy_functions/Latex_Function.py

@@ -1,5 +1,5 @@
 from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone, check_repeat_upload, map_file_to_sha256
-from toolbox import CatchException, report_exception, update_ui_latest_msg, zip_result, gen_time_str
+from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip_result, gen_time_str
 from functools import partial
 from loguru import logger
 
@@ -41,7 +41,7 @@ def switch_prompt(pfg, mode, more_requirement):
     return inputs_array, sys_prompt_array
 
 
-def descend_to_extracted_folder_if_exist(project_folder):
+def desend_to_extracted_folder_if_exist(project_folder):
     """
     Descend into the extracted folder if it exists, otherwise return the original folder.
 
@@ -130,7 +130,7 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
 
     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_}。"
-        yield from update_ui_latest_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
     # <-------------- set format ------------->
     arxiv_id = url_.split('/abs/')[-1]
@@ -156,16 +156,16 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
         return False
 
     if os.path.exists(dst) and allow_cache:
-        yield from update_ui_latest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_lastest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
         success = True
     else:
-        yield from update_ui_latest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_lastest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
         success = fix_url_and_download()
-        yield from update_ui_latest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_lastest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
 
 
     if not success:
-        yield from update_ui_latest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
+        yield from update_ui_lastest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
         raise tarfile.ReadError(f"论文下载失败 {arxiv_id}")
 
     # <-------------- extract file ------------->
@@ -288,7 +288,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
         return
 
     # <-------------- if is a zip/tar file ------------->
-    project_folder = descend_to_extracted_folder_if_exist(project_folder)
+    project_folder = desend_to_extracted_folder_if_exist(project_folder)
 
     # <-------------- move latex project away from temp folder ------------->
     from shared_utils.fastapi_server import validate_path_safety
@@ -365,7 +365,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     try:
         txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
     except tarfile.ReadError as e:
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             "无法自动下载该论文的Latex源码，请前往arxiv打开此论文下载页面，点other Formats，然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。",
             chatbot=chatbot, history=history)
         return
@@ -404,7 +404,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
         return
 
     # <-------------- if is a zip/tar file ------------->
-    project_folder = descend_to_extracted_folder_if_exist(project_folder)
+    project_folder = desend_to_extracted_folder_if_exist(project_folder)
 
     # <-------------- move latex project away from temp folder ------------->
     from shared_utils.fastapi_server import validate_path_safety
@@ -518,7 +518,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     # repeat, project_folder = check_repeat_upload(file_manifest[0], hash_tag)
 
     # if repeat:
-    #     yield from update_ui_latest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)
+    #     yield from update_ui_lastest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)
     #     try:
     #         translate_pdf = [f for f in glob.glob(f'{project_folder}/**/merge_translate_zh.pdf', recursive=True)][0]
     #         promote_file_to_downloadzone(translate_pdf, rename_file=None, chatbot=chatbot)
@@ -531,7 +531,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     #         report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"发现重复上传，但是无法找到相关文件")
     #         yield from update_ui(chatbot=chatbot, history=history)
     # else:
-    #     yield from update_ui_latest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
+    #     yield from update_ui_lastest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
 
     # <-------------- convert pdf into tex ------------->
     chatbot.append([f"解析项目: {txt}", "正在将PDF转换为tex项目，请耐心等待..."])
@@ -543,7 +543,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
         return False
 
     # <-------------- translate latex file into Chinese ------------->
-    yield from update_ui_latest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
+    yield from update_ui_lastest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
     file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
     if len(file_manifest) == 0:
         report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
@@ -551,7 +551,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
         return
 
     # <-------------- if is a zip/tar file ------------->
-    project_folder = descend_to_extracted_folder_if_exist(project_folder)
+    project_folder = desend_to_extracted_folder_if_exist(project_folder)
 
     # <-------------- move latex project away from temp folder ------------->
     from shared_utils.fastapi_server import validate_path_safety
@@ -559,7 +559,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     project_folder = move_project(project_folder)
 
     # <-------------- set a hash tag for repeat-checking ------------->
-    with open(pj(project_folder, hash_tag + '.tag'), 'w', encoding='utf8') as f:
+    with open(pj(project_folder, hash_tag + '.tag'), 'w') as f:
         f.write(hash_tag)
         f.close()
 
@@ -571,7 +571,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
                                     switch_prompt=_switch_prompt_)
 
     # <-------------- compile PDF ------------->
-    yield from update_ui_latest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
+    yield from update_ui_lastest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
     success = yield from 编译Latex(chatbot, history, main_file_original='merge',
                                 main_file_modified='merge_translate_zh', mode='translate_zh',
                                 work_folder_original=project_folder, work_folder_modified=project_folder,

crazy_functions/PDF_Translate.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, check_packages, get_conf
-from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion
+from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion
 from toolbox import trimmed_format_exc_markdown
 from crazy_functions.crazy_utils import get_files_from_everything
 from crazy_functions.pdf_fns.parse_pdf import get_avail_grobid_url
@@ -47,7 +47,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
                 yield from 解析PDF_基于DOC2X(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, DOC2X_API_KEY, user_request)
                 return
             except:
-                chatbot.append([None, f"DOC2X服务不可用，请检查报错详细。{trimmed_format_exc_markdown()}"])
+                chatbot.append([None, f"DOC2X服务不可用，现在将执行效果稍差的旧版代码。{trimmed_format_exc_markdown()}"])
                 yield from update_ui(chatbot=chatbot, history=history)
 
     if method == "GROBID":
@@ -57,9 +57,9 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
             yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
             return
 
-    if method == "Classic":
+    if method == "ClASSIC":
         # ------- 第三种方法，早期代码，效果不理想 -------
-        yield from update_ui_latest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
+        yield from update_ui_lastest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
         yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
         return
 
@@ -77,7 +77,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         if grobid_url is not None:
             yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
             return
-        yield from update_ui_latest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
+        yield from update_ui_lastest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
         yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
         return
 

crazy_functions/PDF_Translate_Wrap.py

@@ -19,7 +19,7 @@ class PDF_Tran(GptAcademicPluginTemplate):
             "additional_prompt":
                 ArgProperty(title="额外提示词", description="例如：对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步
             "pdf_parse_method":
-                ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "Classic"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
+                ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "ClASSIC"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
         }
         return gui_definition
 

crazy_functions/Rag_Interface.py

@@ -1,11 +1,4 @@
-import os,glob
+from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
-from typing import List
-
-from shared_utils.fastapi_server import validate_path_safety
-
-from toolbox import report_exception
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
-from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 
@@ -14,37 +7,6 @@ MAX_HISTORY_ROUND = 5
 MAX_CONTEXT_TOKEN_LIMIT = 4096
 REMEMBER_PREVIEW = 1000
 
-@CatchException
-def handle_document_upload(files: List[str], llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request, rag_worker):
-    """
-    Handles document uploads by extracting text and adding it to the vector store.
-    """
-    from llama_index.core import Document
-    from crazy_functions.rag_fns.rag_file_support import extract_text, supports_format
-    user_name = chatbot.get_user()
-    checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
-
-    for file_path in files:
-        try:
-            validate_path_safety(file_path, user_name)
-            text = extract_text(file_path)
-            if text is None:
-                chatbot.append(
-                    [f"上传文件: {os.path.basename(file_path)}", f"文件解析失败，无法提取文本内容，请更换文件。失败原因可能为：1.文档格式过于复杂；2. 不支持的文件格式，支持的文件格式后缀有:" + ", ".join(supports_format)])
-            else:
-                chatbot.append(
-                    [f"上传文件: {os.path.basename(file_path)}", f"上传文件前50个字符为:{text[:50]}。"])
-                document = Document(text=text, metadata={"source": file_path})
-                rag_worker.add_documents_to_vector_store([document])
-                chatbot.append([f"上传文件: {os.path.basename(file_path)}", "文件已成功添加到知识库。"])
-        except Exception as e:
-            report_exception(chatbot, history, a=f"处理文件: {file_path}", b=str(e))
-
-    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
-
-
-
-# Main Q&A function with document upload support
 @CatchException
 def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
 
@@ -61,45 +23,28 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     # 1. we retrieve rag worker from global context
     user_name = chatbot.get_user()
     checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
-
     if user_name in RAG_WORKER_REGISTER:
         rag_worker = RAG_WORKER_REGISTER[user_name]
     else:
         rag_worker = RAG_WORKER_REGISTER[user_name] = LlamaIndexRagWorker(
-            user_name,
+            user_name, 
-            llm_kwargs,
+            llm_kwargs, 
-            checkpoint_dir=checkpoint_dir,
+            checkpoint_dir=checkpoint_dir, 
-            auto_load_checkpoint=True
+            auto_load_checkpoint=True)
-        )
-
     current_context = f"{VECTOR_STORE_TYPE} @ {checkpoint_dir}"
     tip = "提示：输入“清空向量数据库”可以清空RAG向量数据库"
-
+    if txt == "清空向量数据库":
-    # 2. Handle special commands
-    if os.path.exists(txt) and os.path.isdir(txt):
-        project_folder = txt
-        validate_path_safety(project_folder, chatbot.get_user())
-        # Extract file paths from the user input
-        # Assuming the user inputs file paths separated by commas after the command
-        file_paths =  [f for f in glob.glob(f'{project_folder}/**/*', recursive=True)]
-        chatbot.append([txt, f'正在处理上传的文档 ({current_context}) ...'])
-        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
-
-        yield from handle_document_upload(file_paths, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request, rag_worker)
-        return
-
-    elif txt == "清空向量数据库":
         chatbot.append([txt, f'正在清空 ({current_context}) ...'])
-        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        rag_worker.purge_vector_store()
+        rag_worker.purge()
-        yield from update_ui_latest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0) # 刷新界面
         return
 
-    # 3. Normal Q&A processing
     chatbot.append([txt, f'正在召回知识 ({current_context}) ...'])
-    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
-    # 4. Clip history to reduce token consumption
+    # 2. clip history to reduce token consumption
+    #   2-1. reduce chat round
     txt_origin = txt
 
     if len(history) > MAX_HISTORY_ROUND * 2:
@@ -107,47 +52,41 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     txt_clip, history, flags = input_clipping(txt, history, max_token_limit=MAX_CONTEXT_TOKEN_LIMIT, return_clip_flags=True)
     input_is_clipped_flag = (flags["original_input_len"] != flags["clipped_input_len"])
 
-    # 5. If input is clipped, add input to vector store before retrieve
+    #   2-2. if input is clipped, add input to vector store before retrieve
     if input_is_clipped_flag:
-        yield from update_ui_latest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_lastest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0) # 刷新界面
-        # Save input to vector store
+        # save input to vector store
         rag_worker.add_text_to_vector_store(txt_origin)
-        yield from update_ui_latest_msg('向量化完成 ...', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_lastest_msg('向量化完成 ...', chatbot, history, delay=0) # 刷新界面
-
         if len(txt_origin) > REMEMBER_PREVIEW:
-            HALF = REMEMBER_PREVIEW // 2
+            HALF = REMEMBER_PREVIEW//2
             i_say_to_remember = txt[:HALF] + f" ...\n...(省略{len(txt_origin)-REMEMBER_PREVIEW}字)...\n... " + txt[-HALF:]
             if (flags["original_input_len"] - flags["clipped_input_len"]) > HALF:
-                txt_clip = txt_clip + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... " + txt[-HALF:]
+                txt_clip = txt_clip  + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... " + txt[-HALF:]
+            else:
+                pass
+            i_say = txt_clip
         else:
             i_say_to_remember = i_say = txt_clip
     else:
         i_say_to_remember = i_say = txt_clip
 
-    # 6. Search vector store and build prompts
+    # 3. we search vector store and build prompts
     nodes = rag_worker.retrieve_from_store_with_query(i_say)
     prompt = rag_worker.build_prompt(query=i_say, nodes=nodes)
-    # 7. Query language model
-    if len(chatbot) != 0:
-        chatbot.pop(-1)  # Pop temp chat, because we are going to add them again inside `request_gpt_model_in_new_thread_with_ui_alive`
 
+    # 4. it is time to query llms
+    if len(chatbot) != 0: chatbot.pop(-1) # pop temp chat, because we are going to add them again inside `request_gpt_model_in_new_thread_with_ui_alive`
     model_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=prompt,
+        inputs=prompt, inputs_show_user=i_say,
-        inputs_show_user=i_say,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
-        llm_kwargs=llm_kwargs,
-        chatbot=chatbot,
-        history=history,
         sys_prompt=system_prompt,
         retry_times_at_unknown_error=0
     )
 
-    # 8. Remember Q&A
+    # 5. remember what has been asked / answered
-    yield from update_ui_latest_msg(
+    yield from update_ui_lastest_msg(model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...', chatbot, history, delay=0.5) # 刷新界面
-        model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...',
-        chatbot, history, delay=0.5
-    )
     rag_worker.remember_qa(i_say_to_remember, model_say)
     history.extend([i_say, model_say])
 
-    # 9. Final UI Update
+    yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip) # 刷新界面
-    yield from update_ui_latest_msg(model_say, chatbot, history, delay=0, msg=tip)

crazy_functions/Social_Helper.py

@@ -1,5 +1,5 @@
 import pickle, os, random
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
+from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -9,7 +9,7 @@ from loguru import logger
 from typing import List
 
 
-SOCIAL_NETWORK_WORKER_REGISTER = {}
+SOCIAL_NETWOK_WORKER_REGISTER = {}
 
 class SocialNetwork():
     def __init__(self):
@@ -78,7 +78,7 @@ class SocialNetworkWorker(SaveAndLoad):
             for f in friend.friends_list: 
                 self.add_friend(f)
             msg = f"成功添加{len(friend.friends_list)}个联系人: {str(friend.friends_list)}"
-            yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
+            yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
 
 
     def run(self, txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
@@ -104,12 +104,12 @@ class SocialNetworkWorker(SaveAndLoad):
         }
 
         try:
-            Explanation = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
+            Explaination = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
             class UserSociaIntention(BaseModel):
                 intention_type: str = Field(
                     description=
                         f"The type of user intention. You must choose from {self.tools_to_select.keys()}.\n\n" 
-                        f"Explanation:\n{Explanation}", 
+                        f"Explaination:\n{Explaination}", 
                     default="SocialAdvice"
                 )
             pydantic_cls_instance, err_msg = select_tool(
@@ -118,7 +118,7 @@ class SocialNetworkWorker(SaveAndLoad):
                 pydantic_cls=UserSociaIntention
             )
         except Exception as e:
-            yield from update_ui_latest_msg(
+            yield from update_ui_lastest_msg(
                 lastmsg=f"无法理解用户意图 {err_msg}", 
                 chatbot=chatbot, 
                 history=history, 
@@ -150,10 +150,10 @@ def I人助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt,
     # 1. we retrieve worker from global context
     user_name = chatbot.get_user()
     checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag')
-    if user_name in SOCIAL_NETWORK_WORKER_REGISTER:
+    if user_name in SOCIAL_NETWOK_WORKER_REGISTER:
-        social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name]
+        social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name]
     else:
-        social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
+        social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
             user_name, 
             llm_kwargs, 
             checkpoint_dir=checkpoint_dir, 

crazy_functions/SourceCode_Comment.py

@@ -1,5 +1,5 @@
 import os, copy, time
-from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_latest_msg, get_conf, generate_file_link
+from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_lastest_msg, get_conf, generate_file_link
 from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
@@ -117,7 +117,7 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
                 logger.error(f"文件: {fp} 的注释结果未能成功")
         file_links = generate_file_link(preview_html_list)
 
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             f"当前任务: <br/>{'<br/>'.join(tasks)}.<br/>" + 
             f"剩余源文件数量: {remain}.<br/>" + 
             f"已完成的文件: {sum(worker_done)}.<br/>" + 

crazy_functions/VideoResource_GPT.py

@@ -1,204 +0,0 @@
-import requests
-import random
-import time
-import re
-import json
-from bs4 import BeautifulSoup
-from functools import lru_cache
-from itertools import zip_longest
-from check_proxy import check_proxy
-from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
-from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
-from request_llms.bridge_all import model_info
-from request_llms.bridge_all import predict_no_ui_long_connection
-from crazy_functions.prompts.internet import SearchOptimizerPrompt, SearchAcademicOptimizerPrompt
-from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
-from textwrap import dedent
-from loguru import logger
-from pydantic import BaseModel, Field
-
-class Query(BaseModel):
-    search_keyword: str = Field(description="search query for video resource")
-
-
-class VideoResource(BaseModel):
-    thought: str = Field(description="analysis of the search results based on the user's query")
-    title: str = Field(description="title of the video")
-    author: str = Field(description="author/uploader of the video") 
-    bvid: str = Field(description="unique ID of the video")
-    another_failsafe_bvid: str = Field(description="provide another bvid, the other one is not working")
-
-
-def get_video_resource(search_keyword):
-    from crazy_functions.media_fns.get_media import search_videos
-
-    # Search for videos and return the first result
-    videos = search_videos(
-        search_keyword
-    )
-
-    # Return the first video if results exist, otherwise return None
-    return videos
-
-def download_video(bvid, user_name, chatbot, history):
-    # from experimental_mods.get_bilibili_resource import download_bilibili
-    from crazy_functions.media_fns.get_media import download_video
-    # pause a while
-    tic_time = 8
-    for i in range(tic_time):
-        yield from update_ui_latest_msg(
-            lastmsg=f"即将下载音频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。", 
-            chatbot=chatbot, history=[], delay=1)
-
-    # download audio
-    chatbot.append((None, "下载音频, 请稍等...")); yield from update_ui(chatbot=chatbot, history=history)
-    downloaded_files = yield from download_video(bvid, only_audio=True, user_name=user_name, chatbot=chatbot, history=history)
-
-    if len(downloaded_files) == 0:
-        # failed to download audio
-        return []
-
-    # preview
-    preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files]
-    file_links = generate_file_link(preview_list)
-    yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
-    chatbot.append((None, f"即将下载视频。"))
-
-    # pause a while
-    tic_time = 16
-    for i in range(tic_time):
-        yield from update_ui_latest_msg(
-            lastmsg=f"即将下载视频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。", 
-            chatbot=chatbot, history=[], delay=1)
-
-    # download video
-    chatbot.append((None, "下载视频, 请稍等...")); yield from update_ui(chatbot=chatbot, history=history)
-    downloaded_files_part2 = yield from download_video(bvid, only_audio=False, user_name=user_name, chatbot=chatbot, history=history)
-
-    # preview
-    preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files_part2]
-    file_links = generate_file_link(preview_list)
-    yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
-
-    # return
-    return downloaded_files + downloaded_files_part2
-
-
-class Strategy(BaseModel):
-    thought: str = Field(description="analysis of the user's wish, for example, can you recall the name of the resource?")
-    which_methods: str = Field(description="Which method to use to find the necessary information? choose from 'method_1' and 'method_2'.")
-    method_1_search_keywords: str = Field(description="Generate keywords to search the internet if you choose method 1, otherwise empty.")
-    method_2_generate_keywords: str = Field(description="Generate keywords for video download engine if you choose method 2, otherwise empty.")
-
-
-@CatchException
-def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
-    user_wish: str = txt
-    # query demos: 
-    #   - "我想找一首歌，里面有句歌词是“turn your face towards the sun”"
-    #   - "一首歌，第一句是红豆生南国"
-    #   - "一首音乐，中国航天任务专用的那首"
-    #   - "戴森球计划在熔岩星球的音乐"
-    #   - "hanser的百变什么精"
-    #   - "打大圣残躯时的bgm"
-    #   - "渊下宫战斗音乐"
-
-    # 搜索
-    chatbot.append((txt, "检索中, 请稍等..."))
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-    if "跳过联网搜索" not in user_wish:
-        # 结构化生成
-        internet_search_keyword = user_wish
-
-        yield from update_ui_latest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
-        from crazy_functions.Internet_GPT import internet_search_with_analysis_prompt
-        result = yield from internet_search_with_analysis_prompt(
-            prompt=internet_search_keyword,
-            analysis_prompt="请根据搜索结果分析，获取用户需要找的资源的名称、作者、出处等信息。",
-            llm_kwargs=llm_kwargs,
-            chatbot=chatbot
-        )
-
-        yield from update_ui_latest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
-        rf_req = dedent(f"""
-        The user wish to get the following resource:
-            {user_wish}
-        Meanwhile, you can access another expert's opinion on the user's wish:
-            {result}
-        Generate search keywords (less than 5 keywords) for video download engine accordingly.
-        """)
-    else:
-        user_wish = user_wish.replace("跳过联网搜索", "").strip()
-        rf_req = dedent(f"""
-        The user wish to get the following resource:
-            {user_wish}
-        Generate research keywords (less than 5 keywords) accordingly.
-        """)
-    gpt_json_io = GptJsonIO(Query)
-    inputs = rf_req + gpt_json_io.format_instructions
-    run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
-    analyze_res = run_gpt_fn(inputs, "")
-    logger.info(analyze_res)
-    query: Query = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
-    video_engine_keywords = query.search_keyword
-    # 关键词展示
-    chatbot.append((None, f"检索关键词已确认: {video_engine_keywords}。筛选中, 请稍等..."))
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
-    # 获取候选资源
-    candidate_dictionary: dict =  get_video_resource(video_engine_keywords)
-    candidate_dictionary_as_str = json.dumps(candidate_dictionary, ensure_ascii=False, indent=4)
-
-    # 展示候选资源
-    candidate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candidate_dictionary)])
-    chatbot.append((None, f"候选:\n\n{candidate_display}"))
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
-    # 结构化生成
-    rf_req_2 = dedent(f"""
-    The user wish to get the following resource:
-        {user_wish}
-
-    Select the most relevant and suitable video resource from the following search results:
-        {candidate_dictionary_as_str}
-
-    Note:
-        1. The first several search video results are more likely to satisfy the user's wish.
-        2. The time duration of the video should be less than 10 minutes.
-        3. You should analyze the search results first, before giving your answer.
-        4. Use Chinese if possible.
-        5. Beside the primary video selection, give a backup video resource `bvid`.
-    """)
-    gpt_json_io = GptJsonIO(VideoResource)
-    inputs = rf_req_2 + gpt_json_io.format_instructions
-    run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
-    analyze_res = run_gpt_fn(inputs, "")
-    logger.info(analyze_res)
-    video_resource: VideoResource = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
-
-    # Display
-    chatbot.append(
-        (None, 
-            f"分析：{video_resource.thought}" "<br/>"
-            f"选择: `{video_resource.title}`。" "<br/>" 
-            f"作者：{video_resource.author}"
-        )
-    )
-    chatbot.append((None, f"下载中, 请稍等..."))
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
-    if video_resource and video_resource.bvid:
-        logger.info(video_resource)
-        downloaded = yield from download_video(video_resource.bvid, chatbot.get_user(), chatbot, history)
-        if not downloaded:
-            chatbot.append((None, f"下载失败, 尝试备选 ..."))
-            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-            downloaded = yield from download_video(video_resource.another_failsafe_bvid, chatbot.get_user(), chatbot, history)
-
-
-
-
-        
-@CatchException
-def debug(bvid, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
-    yield from download_video(bvid, chatbot.get_user(), chatbot, history)

crazy_functions/agent_fns/auto_agent.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
-from toolbox import report_exception, get_log_folder, update_ui_latest_msg, Singleton
+from toolbox import report_exception, get_log_folder, update_ui_lastest_msg, Singleton
 from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
 from crazy_functions.agent_fns.general import AutoGenGeneral
 

crazy_functions/agent_fns/echo_agent.py

@@ -8,7 +8,7 @@ class EchoDemo(PluginMultiprocessManager):
         while True:
             msg = self.child_conn.recv() # PipeCom
             if msg.cmd == "user_input":
-                # wait father user input
+                # wait futher user input
                 self.child_conn.send(PipeCom("show", msg.content))
                 wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
                 if not wait_success:

crazy_functions/agent_fns/general.py

@@ -27,7 +27,7 @@ def gpt_academic_generate_oai_reply(
         llm_kwargs=llm_config,
         history=history,
         sys_prompt=self._oai_system_message[0]['content'],
-        console_silence=True
+        console_slience=True
     )
     assumed_done = reply.endswith('\nTERMINATE')
     return True, reply

crazy_functions/agent_fns/python_comment_agent.py

@@ -10,7 +10,7 @@ from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_
 # TODO: 解决缩进问题
 
 find_function_end_prompt = '''
-Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to separate functions, class functions etc.
+Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to sperate functions, class functions etc.
 - Provide the line number where the first visible function ends.
 - Provide the line number where the next visible function begins.
 - If there are no other functions in this page, you should simply return the line number of the last line.
@@ -59,7 +59,7 @@ OUTPUT:
 
 
 
-revise_function_prompt = '''
+revise_funtion_prompt = '''
 You need to read the following code, and revise the source code ({FILE_BASENAME}) according to following instructions:
 1. You should analyze the purpose of the functions (if there are any).
 2. You need to add docstring for the provided functions (if there are any).
@@ -117,7 +117,7 @@ def zip_result(folder):
 '''
 
 
-revise_function_prompt_chinese = '''
+revise_funtion_prompt_chinese = '''
 您需要阅读以下代码，并根据以下说明修订源代码({FILE_BASENAME}):
 1. 如果源代码中包含函数的话, 你应该分析给定函数实现了什么功能
 2. 如果源代码中包含函数的话, 你需要为函数添加docstring, docstring必须使用中文
@@ -188,9 +188,9 @@ class PythonCodeComment():
         self.language = language
         self.observe_window_update = observe_window_update
         if self.language == "chinese":
-            self.core_prompt = revise_function_prompt_chinese
+            self.core_prompt = revise_funtion_prompt_chinese
         else:
-            self.core_prompt = revise_function_prompt
+            self.core_prompt = revise_funtion_prompt
         self.path = None
         self.file_basename = None
         self.file_brief = ""
@@ -222,7 +222,7 @@ class PythonCodeComment():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_silence=True
+            console_slience=True
         )
 
         def extract_number(text):
@@ -316,7 +316,7 @@ class PythonCodeComment():
     def tag_code(self, fn, hint):
         code = fn
         _, n_indent = self.dedent(code)
-        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preserve them in the OUTPUT.)"
+        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preseve them in the OUTPUT.)"
         brief_reminder = "" if self.file_brief == "" else f"({self.file_basename} abstract: {self.file_brief})"
         hint_reminder = "" if hint is None else f"(Reminder: do not ignore or modify code such as `{hint}`, provide complete code in the OUTPUT.)"
         self.llm_kwargs['temperature'] = 0
@@ -333,7 +333,7 @@ class PythonCodeComment():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_silence=True
+            console_slience=True
         )
 
         def get_code_block(reply):
@@ -400,7 +400,7 @@ class PythonCodeComment():
         return revised
 
     def begin_comment_source_code(self, chatbot=None, history=None):
-        # from toolbox import update_ui_latest_msg
+        # from toolbox import update_ui_lastest_msg
         assert self.path is not None
         assert '.py' in self.path   # must be python source code
         # write_target = self.path + '.revised.py'
@@ -409,10 +409,10 @@ class PythonCodeComment():
         # with open(self.path + '.revised.py', 'w+', encoding='utf8') as f:
         while True:
             try:
-                # yield from update_ui_latest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
+                # yield from update_ui_lastest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
                 next_batch, line_no_start, line_no_end = self.get_next_batch()
                 self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
-                # yield from update_ui_latest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
+                # yield from update_ui_lastest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
                 
                 hint = None
                 MAX_ATTEMPT = 2

crazy_functions/chatglm微调工具.py

@@ -0,0 +1,141 @@
+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

crazy_functions/crazy_utils.py

@@ -1,7 +1,7 @@
 import os
 import threading
 from loguru import logger
-from shared_utils.char_visual_effect import scrolling_visual_effect
+from shared_utils.char_visual_effect import scolling_visual_effect
 from toolbox import update_ui, get_conf, trimmed_format_exc, get_max_token, Singleton
 
 def input_clipping(inputs, history, max_token_limit, return_clip_flags=False):
@@ -169,7 +169,6 @@ def can_multi_process(llm) -> bool:
     def default_condition(llm) -> bool:
         # legacy condition
         if llm.startswith('gpt-'): return True
-        if llm.startswith('chatgpt-'): return True
         if llm.startswith('api2d-'): return True
         if llm.startswith('azure-'): return True
         if llm.startswith('spark'): return True
@@ -256,7 +255,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                 # 【第一种情况】：顺利完成
                 gpt_say = predict_no_ui_long_connection(
                     inputs=inputs, llm_kwargs=llm_kwargs, history=history,
-                    sys_prompt=sys_prompt, observe_window=mutable[index], console_silence=True
+                    sys_prompt=sys_prompt, observe_window=mutable[index], console_slience=True
                 )
                 mutable[index][2] = "已成功"
                 return gpt_say
@@ -326,7 +325,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
             mutable[thread_index][1] = time.time()
         # 在前端打印些好玩的东西
         for thread_index, _ in enumerate(worker_done):
-            print_something_really_funny = f"[ ...`{scrolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
+            print_something_really_funny = f"[ ...`{scolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
             observe_win.append(print_something_really_funny)
         # 在前端打印些好玩的东西
         stat_str = ''.join([f'`{mutable[thread_index][2]}`: {obs}\n\n'
@@ -389,11 +388,11 @@ def read_and_clean_pdf_text(fp):
         """
         提取文本块主字体
         """
-        fsize_statistics = {}
+        fsize_statiscs = {}
         for wtf in l['spans']:
-            if wtf['size'] not in fsize_statistics: fsize_statistics[wtf['size']] = 0
+            if wtf['size'] not in fsize_statiscs: fsize_statiscs[wtf['size']] = 0
-            fsize_statistics[wtf['size']] += len(wtf['text'])
+            fsize_statiscs[wtf['size']] += len(wtf['text'])
-        return max(fsize_statistics, key=fsize_statistics.get)
+        return max(fsize_statiscs, key=fsize_statiscs.get)
 
     def ffsize_same(a,b):
         """
@@ -433,11 +432,11 @@ def read_and_clean_pdf_text(fp):
 
         ############################## <第 2 步，获取正文主字体> ##################################
         try:
-            fsize_statistics = {}
+            fsize_statiscs = {}
             for span in meta_span:
-                if span[1] not in fsize_statistics: fsize_statistics[span[1]] = 0
+                if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
-                fsize_statistics[span[1]] += span[2]
+                fsize_statiscs[span[1]] += span[2]
-            main_fsize = max(fsize_statistics, key=fsize_statistics.get)
+            main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
             if REMOVE_FOOT_NOTE:
                 give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
         except:
@@ -610,9 +609,9 @@ class nougat_interface():
 
 
     def NOUGAT_parse_pdf(self, fp, chatbot, history):
-        from toolbox import update_ui_latest_msg
+        from toolbox import update_ui_lastest_msg
 
-        yield from update_ui_latest_msg("正在解析论文, 请稍候。进度：正在排队, 等待线程锁...",
+        yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度：正在排队, 等待线程锁...",
                                          chatbot=chatbot, history=history, delay=0)
         self.threadLock.acquire()
         import glob, threading, os
@@ -620,7 +619,7 @@ class nougat_interface():
         dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
         os.makedirs(dst)
 
-        yield from update_ui_latest_msg("正在解析论文, 请稍候。进度：正在加载NOUGAT... （提示：首次运行需要花费较长时间下载NOUGAT参数）",
+        yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度：正在加载NOUGAT... （提示：首次运行需要花费较长时间下载NOUGAT参数）",
                                          chatbot=chatbot, history=history, delay=0)
         command = ['nougat', '--out', os.path.abspath(dst), os.path.abspath(fp)]
         self.nougat_with_timeout(command, cwd=os.getcwd(), timeout=3600)

crazy_functions/doc_fns/AI_review_doc.py

@@ -1,812 +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
-import markdown
-from crazy_functions.doc_fns.conversation_doc.word_doc import convert_markdown_to_word
-
-
-
-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日'))
-            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，使用convert_markdown_to_word处理文本"""
-        # 使用convert_markdown_to_word处理markdown文本
-        processed_text = convert_markdown_to_word(text)
-        paragraph = self.doc.add_paragraph(processed_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并处理markdown文本
-        """
-        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)
-                # 使用convert_markdown_to_word处理文件内容
-                self._add_content(convert_markdown_to_word(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)
-                # 使用convert_markdown_to_word处理文件内容
-                self._add_content(convert_markdown_to_word(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，使用convert_markdown_to_word处理
-        self._add_heading("总体摘要", 1)
-        self._add_content(convert_markdown_to_word(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
-
-    def save_as_pdf(self, word_path, pdf_path=None):
-        """将生成的Word文档转换为PDF
-        
-        参数:
-            word_path: Word文档的路径
-            pdf_path: 可选，PDF文件的输出路径。如果未指定，将使用与Word文档相同的名称和位置
-            
-        返回:
-            生成的PDF文件路径，如果转换失败则返回None
-        """
-        from crazy_functions.doc_fns.conversation_doc.word2pdf import WordToPdfConverter
-        try:
-            pdf_path = WordToPdfConverter.convert_to_pdf(word_path, pdf_path)
-            return pdf_path
-        except Exception as e:
-            print(f"PDF转换失败: {str(e)}")
-            return None
-
-
-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 - 优化版"""
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.md = markdown.Markdown(extensions=['extra','codehilite', 'tables','nl2br'])
-        self.css_styles = """
-        @keyframes fadeIn {
-            from { opacity: 0; transform: translateY(20px); }
-            to { opacity: 1; transform: translateY(0); }
-        }
-
-        @keyframes slideIn {
-            from { transform: translateX(-20px); opacity: 0; }
-            to { transform: translateX(0); opacity: 1; }
-        }
-
-        @keyframes pulse {
-            0% { transform: scale(1); }
-            50% { transform: scale(1.05); }
-            100% { transform: scale(1); }
-        }
-
-        :root {
-            /* Enhanced color palette */
-            --primary-color: #2563eb;
-            --primary-light: #eff6ff;
-            --secondary-color: #1e293b;
-            --background-color: #f8fafc;
-            --text-color: #334155;
-            --text-light: #64748b;
-            --border-color: #e2e8f0;
-            --error-color: #ef4444;
-            --error-light: #fef2f2;
-            --success-color: #22c55e;
-            --warning-color: #f59e0b;
-            --card-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
-            --hover-shadow: 0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1);
-            
-            /* Typography */
-            --heading-font: "Plus Jakarta Sans", system-ui, sans-serif;
-            --body-font: "Inter", system-ui, sans-serif;
-        }
-
-        body {
-            font-family: var(--body-font);
-            line-height: 1.8;
-            max-width: 1200px;
-            margin: 0 auto;
-            padding: 2rem;
-            color: var(--text-color);
-            background-color: var(--background-color);
-            font-size: 16px;
-            -webkit-font-smoothing: antialiased;
-        }
-
-        .container {
-            background: white;
-            padding: 3rem;
-            border-radius: 24px;
-            box-shadow: var(--card-shadow);
-            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
-            animation: fadeIn 0.6s ease-out;
-            border: 1px solid var(--border-color);
-        }
-
-        .container:hover {
-            box-shadow: var(--hover-shadow);
-            transform: translateY(-2px);
-        }
-
-        h1, h2, h3 {
-            font-family: var(--heading-font);
-            font-weight: 600;
-        }
-
-        h1 {
-            color: var(--primary-color);
-            font-size: 2.8em;
-            text-align: center;
-            margin: 2rem 0 3rem;
-            padding-bottom: 1.5rem;
-            border-bottom: 3px solid var(--primary-color);
-            letter-spacing: -0.03em;
-            position: relative;
-            display: flex;
-            align-items: center;
-            justify-content: center;
-            gap: 1rem;
-        }
-
-        h1::after {
-            content: '';
-            position: absolute;
-            bottom: -3px;
-            left: 50%;
-            transform: translateX(-50%);
-            width: 120px;
-            height: 3px;
-            background: linear-gradient(90deg, var(--primary-color), var(--primary-light));
-            border-radius: 3px;
-            transition: width 0.3s ease;
-        }
-
-        h1:hover::after {
-            width: 180px;
-        }
-
-        h2 {
-            color: var(--secondary-color);
-            font-size: 1.9em;
-            margin: 2.5rem 0 1.5rem;
-            padding-left: 1.2rem;
-            border-left: 4px solid var(--primary-color);
-            letter-spacing: -0.02em;
-            display: flex;
-            align-items: center;
-            gap: 1rem;
-            transition: all 0.3s ease;
-        }
-
-        h2:hover {
-            color: var(--primary-color);
-            transform: translateX(5px);
-        }
-
-        h3 {
-            color: var(--text-color);
-            font-size: 1.5em;
-            margin: 2rem 0 1rem;
-            padding-bottom: 0.8rem;
-            border-bottom: 2px solid var(--border-color);
-            transition: all 0.3s ease;
-            display: flex;
-            align-items: center;
-            gap: 0.8rem;
-        }
-
-        h3:hover {
-            color: var(--primary-color);
-            border-bottom-color: var(--primary-color);
-        }
-
-        .summary {
-            background: var(--primary-light);
-            padding: 2.5rem;
-            border-radius: 16px;
-            margin: 2.5rem 0;
-            box-shadow: 0 4px 6px -1px rgba(37, 99, 235, 0.1);
-            position: relative;
-            overflow: hidden;
-            transition: transform 0.3s ease, box-shadow 0.3s ease;
-            animation: slideIn 0.5s ease-out;
-        }
-
-        .summary:hover {
-            transform: translateY(-3px);
-            box-shadow: 0 8px 12px -2px rgba(37, 99, 235, 0.15);
-        }
-
-        .summary::before {
-            content: '';
-            position: absolute;
-            top: 0;
-            left: 0;
-            width: 4px;
-            height: 100%;
-            background: linear-gradient(to bottom, var(--primary-color), rgba(37, 99, 235, 0.6));
-        }
-
-        .summary p {
-            margin: 1.2rem 0;
-            line-height: 1.9;
-            color: var(--text-color);
-            transition: color 0.3s ease;
-        }
-
-        .summary:hover p {
-            color: var(--secondary-color);
-        }
-
-        .details {
-            margin-top: 3.5rem;
-            padding-top: 2.5rem;
-            border-top: 2px dashed var(--border-color);
-            animation: fadeIn 0.8s ease-out;
-        }
-
-        .failed-files {
-            background: var(--error-light);
-            padding: 2rem;
-            border-radius: 16px;
-            margin: 3rem 0;
-            border-left: 4px solid var(--error-color);
-            position: relative;
-            transition: all 0.3s ease;
-            animation: slideIn 0.5s ease-out;
-        }
-
-        .failed-files:hover {
-            transform: translateX(5px);
-            box-shadow: 0 8px 15px -3px rgba(239, 68, 68, 0.1);
-        }
-
-        .failed-files h2 {
-            color: var(--error-color);
-            border-left: none;
-            padding-left: 0;
-        }
-
-        .failed-files ul {
-            margin: 1.8rem 0;
-            padding-left: 1.2rem;
-            list-style-type: none;
-        }
-
-        .failed-files li {
-            margin: 1.2rem 0;
-            padding: 1.2rem 1.8rem;
-            background: rgba(239, 68, 68, 0.08);
-            border-radius: 12px;
-            transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
-        }
-
-        .failed-files li:hover {
-            transform: translateX(8px);
-            background: rgba(239, 68, 68, 0.12);
-        }
-
-        .directory-section {
-            margin: 3.5rem 0;
-            padding: 2rem;
-            background: var(--background-color);
-            border-radius: 16px;
-            position: relative;
-            transition: all 0.3s ease;
-            animation: fadeIn 0.6s ease-out;
-        }
-
-        .directory-section:hover {
-            background: white;
-            box-shadow: var(--card-shadow);
-        }
-
-        .file-summary {
-            background: white;
-            padding: 2rem;
-            margin: 1.8rem 0;
-            border-radius: 16px;
-            box-shadow: var(--card-shadow);
-            border-left: 4px solid var(--border-color);
-            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
-            position: relative;
-            overflow: hidden;
-        }
-
-        .file-summary:hover {
-            border-left-color: var(--primary-color);
-            transform: translateX(8px) translateY(-2px);
-            box-shadow: var(--hover-shadow);
-        }
-
-        .file-summary {
-            background: white;
-            padding: 2rem;
-            margin: 1.8rem 0;
-            border-radius: 16px;
-            box-shadow: var(--card-shadow);
-            border-left: 4px solid var(--border-color);
-            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
-            position: relative;
-        }
-
-        .file-summary:hover {
-            border-left-color: var(--primary-color);
-            transform: translateX(8px) translateY(-2px);
-            box-shadow: var(--hover-shadow);
-        }
-
-        .icon {
-            display: inline-flex;
-            align-items: center;
-            justify-content: center;
-            width: 32px;
-            height: 32px;
-            border-radius: 8px;
-            background: var(--primary-light);
-            color: var(--primary-color);
-            font-size: 1.2em;
-            transition: all 0.3s ease;
-        }
-
-        .file-summary:hover .icon,
-        .directory-section:hover .icon {
-            transform: scale(1.1);
-            background: var(--primary-color);
-            color: white;
-        }
-
-        /* Smooth scrolling */
-        html {
-            scroll-behavior: smooth;
-        }
-
-        /* Selection style */
-        ::selection {
-            background: var(--primary-light);
-            color: var(--primary-color);
-        }
-
-        /* Print styles */
-        @media print {
-            body {
-                background: white;
-            }
-            .container {
-                box-shadow: none;
-                padding: 0;
-            }
-            .file-summary, .failed-files {
-                break-inside: avoid;
-                box-shadow: none;
-            }
-            .icon {
-                display: none;
-            }
-        }
-
-        /* Responsive design */
-        @media (max-width: 768px) {
-            body {
-                padding: 1rem;
-                font-size: 15px;
-            }
-            
-            .container {
-                padding: 1.5rem;
-            }
-
-            h1 {
-                font-size: 2.2em;
-                margin: 1.5rem 0 2rem;
-            }
-
-            h2 {
-                font-size: 1.7em;
-            }
-
-            h3 {
-                font-size: 1.4em;
-            }
-
-            .summary, .failed-files, .directory-section {
-                padding: 1.5rem;
-            }
-
-            .file-summary {
-                padding: 1.2rem;
-            }
-
-            .icon {
-                width: 28px;
-                height: 28px;
-            }
-        }
-
-        /* Dark mode support */
-        @media (prefers-color-scheme: dark) {
-            :root {
-                --primary-light: rgba(37, 99, 235, 0.15);
-                --background-color: #0f172a;
-                --text-color: #e2e8f0;
-                --text-light: #94a3b8;
-                --border-color: #1e293b;
-                --error-light: rgba(239, 68, 68, 0.15);
-            }
-
-            .container, .file-summary {
-                background: #1e293b;
-            }
-
-            .directory-section {
-                background: #0f172a;
-            }
-
-            .directory-section:hover {
-                background: #1e293b;
-            }
-        }
-        """
-
-    def format_failed_files(self) -> str:
-        if not self.failed_files:
-            return ""
-
-        failed_files_html = ['<div class="failed-files">']
-        failed_files_html.append('<h2><span class="icon">⚠️</span> 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><br><span style="color: var(--text-light)">{reason}</span></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('<div class="directory-section">')
-                    formatted_html.append(f'<h2><span class="icon">📁</span> {dir_path}</h2>')
-                    formatted_html.append('</div>')
-                current_dir = dir_path
-
-            file_name = os.path.basename(path)
-            formatted_html.append('<div class="file-summary">')
-            formatted_html.append(f'<h3><span class="icon">📄</span> {file_name}</h3>')
-            formatted_html.append(self.md.convert(self.file_summaries_map[path]))
-            formatted_html.append('</div>')
-
-        return "\n".join(formatted_html)
-
-    def create_document(self) -> str:
-        """生成HTML文档
-        Returns:
-            str: 完整的HTML文档字符串
-        """
-        return f"""
-        <!DOCTYPE html>
-        <html lang="zh-CN">
-        <head>
-            <meta charset="utf-8">
-            <meta name="viewport" content="width=device-width, initial-scale=1">
-            <title>文档总结报告</title>
-            <link href="https://cdnjs.cloudflare.com/ajax/libs/inter/3.19.3/inter.css" rel="stylesheet">
-            <link href="https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@400;600&display=swap" rel="stylesheet">
-            <style>{self.css_styles}</style>
-        </head>
-        <body>
-            <div class="container">
-                <h1><span class="icon">📑</span> 文档总结报告</h1>
-                <div class="summary">
-                    <h2><span class="icon">📋</span> 总体摘要</h2>
-                    <p>{self.md.convert(self.final_summary)}</p>
-                </div>
-                {self.format_failed_files()}
-                <div class="details">
-                    <h2><span class="icon">📚</span> 各文件详细总结</h2>
-                    {self.format_file_summaries()}
-                </div>
-            </div>
-
-        </body>
-        </html>
-        """

crazy_functions/doc_fns/batch_file_query_doc.py

@@ -9,9 +9,6 @@ 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
-import markdown
-from crazy_functions.doc_fns.conversation_doc.word_doc import  convert_markdown_to_word
-
 
 
 class DocumentFormatter(ABC):
@@ -197,17 +194,26 @@ class WordFormatter(DocumentFormatter):
         return "\n".join(result)
 
     def _add_content(self, text: str, indent: bool = True):
-        """添加正文内容，使用convert_markdown_to_word处理文本"""
+        """添加正文内容"""
-        # 使用convert_markdown_to_word处理markdown文本
+        paragraph = self.doc.add_paragraph(text, style='Normal_Custom')
-        processed_text = convert_markdown_to_word(text)
-        paragraph = self.doc.add_paragraph(processed_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并处理markdown文本
+        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
@@ -227,8 +233,7 @@ class WordFormatter(DocumentFormatter):
                 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)
-                # 使用convert_markdown_to_word处理文件内容
+                self._add_content(self.file_summaries_map[path])
-                self._add_content(convert_markdown_to_word(self.file_summaries_map[path]))
                 self.doc.add_paragraph()
 
         # 处理有目录的文件
@@ -248,8 +253,7 @@ class WordFormatter(DocumentFormatter):
 
                 # 添加文件名作为三级标题
                 self._add_heading(f"📄 {file_name}", 3)
-                # 使用convert_markdown_to_word处理文件内容
+                self._add_content(self.file_summaries_map[path])
-                self._add_content(convert_markdown_to_word(self.file_summaries_map[path]))
                 self.doc.add_paragraph()
 
         return "\n".join(result)
@@ -265,9 +269,9 @@ class WordFormatter(DocumentFormatter):
         self._add_heading("文档总结报告", 0)
         self.doc.add_paragraph()
 
-        # 添加总体摘要，使用convert_markdown_to_word处理
+        # 添加总体摘要
         self._add_heading("总体摘要", 1)
-        self._add_content(convert_markdown_to_word(self.final_summary))
+        self._add_content(self.final_summary)
         self.doc.add_paragraph()
 
         # 添加失败文件列表（如果有）
@@ -280,24 +284,6 @@ class WordFormatter(DocumentFormatter):
 
         return self.doc
 
-    def save_as_pdf(self, word_path, pdf_path=None):
-        """将生成的Word文档转换为PDF
-        
-        参数:
-            word_path: Word文档的路径
-            pdf_path: 可选，PDF文件的输出路径。如果未指定，将使用与Word文档相同的名称和位置
-            
-        返回:
-            生成的PDF文件路径，如果转换失败则返回None
-        """
-        from crazy_functions.doc_fns.conversation_doc.word2pdf import WordToPdfConverter
-        try:
-            pdf_path = WordToPdfConverter.convert_to_pdf(word_path, pdf_path)
-            return pdf_path
-        except Exception as e:
-            print(f"PDF转换失败: {str(e)}")
-            return None
-
 
 class MarkdownFormatter(DocumentFormatter):
     """Markdown格式文档生成器"""
@@ -349,395 +335,61 @@ class MarkdownFormatter(DocumentFormatter):
         return "\n".join(document)
 
 
-
 class HtmlFormatter(DocumentFormatter):
-    """HTML格式文档生成器 - 优化版"""
+    """HTML格式文档生成器"""
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self.md = markdown.Markdown(extensions=['extra','codehilite', 'tables','nl2br'])
         self.css_styles = """
-        @keyframes fadeIn {
-            from { opacity: 0; transform: translateY(20px); }
-            to { opacity: 1; transform: translateY(0); }
-        }
-
-        @keyframes slideIn {
-            from { transform: translateX(-20px); opacity: 0; }
-            to { transform: translateX(0); opacity: 1; }
-        }
-
-        @keyframes pulse {
-            0% { transform: scale(1); }
-            50% { transform: scale(1.05); }
-            100% { transform: scale(1); }
-        }
-
-        :root {
-            /* Enhanced color palette */
-            --primary-color: #2563eb;
-            --primary-light: #eff6ff;
-            --secondary-color: #1e293b;
-            --background-color: #f8fafc;
-            --text-color: #334155;
-            --text-light: #64748b;
-            --border-color: #e2e8f0;
-            --error-color: #ef4444;
-            --error-light: #fef2f2;
-            --success-color: #22c55e;
-            --warning-color: #f59e0b;
-            --card-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
-            --hover-shadow: 0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1);
-            
-            /* Typography */
-            --heading-font: "Plus Jakarta Sans", system-ui, sans-serif;
-            --body-font: "Inter", system-ui, sans-serif;
-        }
-
         body {
-            font-family: var(--body-font);
+            font-family: "Microsoft YaHei", Arial, sans-serif;
-            line-height: 1.8;
+            line-height: 1.6;
-            max-width: 1200px;
+            max-width: 1000px;
             margin: 0 auto;
-            padding: 2rem;
+            padding: 20px;
-            color: var(--text-color);
+            color: #333;
-            background-color: var(--background-color);
-            font-size: 16px;
-            -webkit-font-smoothing: antialiased;
         }
-
-        .container {
-            background: white;
-            padding: 3rem;
-            border-radius: 24px;
-            box-shadow: var(--card-shadow);
-            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
-            animation: fadeIn 0.6s ease-out;
-            border: 1px solid var(--border-color);
-        }
-
-        .container:hover {
-            box-shadow: var(--hover-shadow);
-            transform: translateY(-2px);
-        }
-
-        h1, h2, h3 {
-            font-family: var(--heading-font);
-            font-weight: 600;
-        }
-
         h1 {
-            color: var(--primary-color);
+            color: #2c3e50;
-            font-size: 2.8em;
+            border-bottom: 2px solid #eee;
+            padding-bottom: 10px;
+            font-size: 24px;
             text-align: center;
-            margin: 2rem 0 3rem;
-            padding-bottom: 1.5rem;
-            border-bottom: 3px solid var(--primary-color);
-            letter-spacing: -0.03em;
-            position: relative;
-            display: flex;
-            align-items: center;
-            justify-content: center;
-            gap: 1rem;
         }
-
-        h1::after {
-            content: '';
-            position: absolute;
-            bottom: -3px;
-            left: 50%;
-            transform: translateX(-50%);
-            width: 120px;
-            height: 3px;
-            background: linear-gradient(90deg, var(--primary-color), var(--primary-light));
-            border-radius: 3px;
-            transition: width 0.3s ease;
-        }
-
-        h1:hover::after {
-            width: 180px;
-        }
-
         h2 {
-            color: var(--secondary-color);
+            color: #34495e;
-            font-size: 1.9em;
+            margin-top: 30px;
-            margin: 2.5rem 0 1.5rem;
+            font-size: 20px;
-            padding-left: 1.2rem;
+            border-left: 4px solid #3498db;
-            border-left: 4px solid var(--primary-color);
+            padding-left: 10px;
-            letter-spacing: -0.02em;
-            display: flex;
-            align-items: center;
-            gap: 1rem;
-            transition: all 0.3s ease;
         }
-
-        h2:hover {
-            color: var(--primary-color);
-            transform: translateX(5px);
-        }
-
         h3 {
-            color: var(--text-color);
+            color: #2c3e50;
-            font-size: 1.5em;
+            font-size: 18px;
-            margin: 2rem 0 1rem;
+            margin-top: 20px;
-            padding-bottom: 0.8rem;
-            border-bottom: 2px solid var(--border-color);
-            transition: all 0.3s ease;
-            display: flex;
-            align-items: center;
-            gap: 0.8rem;
         }
-
-        h3:hover {
-            color: var(--primary-color);
-            border-bottom-color: var(--primary-color);
-        }
-
         .summary {
-            background: var(--primary-light);
+            background-color: #f8f9fa;
-            padding: 2.5rem;
+            padding: 20px;
-            border-radius: 16px;
+            border-radius: 5px;
-            margin: 2.5rem 0;
+            margin: 20px 0;
-            box-shadow: 0 4px 6px -1px rgba(37, 99, 235, 0.1);
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-            position: relative;
-            overflow: hidden;
-            transition: transform 0.3s ease, box-shadow 0.3s ease;
-            animation: slideIn 0.5s ease-out;
         }
-
-        .summary:hover {
-            transform: translateY(-3px);
-            box-shadow: 0 8px 12px -2px rgba(37, 99, 235, 0.15);
-        }
-
-        .summary::before {
-            content: '';
-            position: absolute;
-            top: 0;
-            left: 0;
-            width: 4px;
-            height: 100%;
-            background: linear-gradient(to bottom, var(--primary-color), rgba(37, 99, 235, 0.6));
-        }
-
-        .summary p {
-            margin: 1.2rem 0;
-            line-height: 1.9;
-            color: var(--text-color);
-            transition: color 0.3s ease;
-        }
-
-        .summary:hover p {
-            color: var(--secondary-color);
-        }
-
         .details {
-            margin-top: 3.5rem;
+            margin-top: 40px;
-            padding-top: 2.5rem;
-            border-top: 2px dashed var(--border-color);
-            animation: fadeIn 0.8s ease-out;
         }
-
         .failed-files {
-            background: var(--error-light);
+            background-color: #fff3f3;
-            padding: 2rem;
+            padding: 15px;
-            border-radius: 16px;
+            border-left: 4px solid #e74c3c;
-            margin: 3rem 0;
+            margin: 20px 0;
-            border-left: 4px solid var(--error-color);
-            position: relative;
-            transition: all 0.3s ease;
-            animation: slideIn 0.5s ease-out;
         }
-
-        .failed-files:hover {
-            transform: translateX(5px);
-            box-shadow: 0 8px 15px -3px rgba(239, 68, 68, 0.1);
-        }
-
-        .failed-files h2 {
-            color: var(--error-color);
-            border-left: none;
-            padding-left: 0;
-        }
-
-        .failed-files ul {
-            margin: 1.8rem 0;
-            padding-left: 1.2rem;
-            list-style-type: none;
-        }
-
-        .failed-files li {
-            margin: 1.2rem 0;
-            padding: 1.2rem 1.8rem;
-            background: rgba(239, 68, 68, 0.08);
-            border-radius: 12px;
-            transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
-        }
-
-        .failed-files li:hover {
-            transform: translateX(8px);
-            background: rgba(239, 68, 68, 0.12);
-        }
-
-        .directory-section {
-            margin: 3.5rem 0;
-            padding: 2rem;
-            background: var(--background-color);
-            border-radius: 16px;
-            position: relative;
-            transition: all 0.3s ease;
-            animation: fadeIn 0.6s ease-out;
-        }
-
-        .directory-section:hover {
-            background: white;
-            box-shadow: var(--card-shadow);
-        }
-
         .file-summary {
-            background: white;
+            background-color: #fff;
-            padding: 2rem;
+            padding: 15px;
-            margin: 1.8rem 0;
+            margin: 15px 0;
-            border-radius: 16px;
+            border-radius: 4px;
-            box-shadow: var(--card-shadow);
+            box-shadow: 0 1px 3px rgba(0,0,0,0.1);
-            border-left: 4px solid var(--border-color);
-            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
-            position: relative;
-            overflow: hidden;
-        }
-
-        .file-summary:hover {
-            border-left-color: var(--primary-color);
-            transform: translateX(8px) translateY(-2px);
-            box-shadow: var(--hover-shadow);
-        }
-
-        .file-summary {
-            background: white;
-            padding: 2rem;
-            margin: 1.8rem 0;
-            border-radius: 16px;
-            box-shadow: var(--card-shadow);
-            border-left: 4px solid var(--border-color);
-            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
-            position: relative;
-        }
-
-        .file-summary:hover {
-            border-left-color: var(--primary-color);
-            transform: translateX(8px) translateY(-2px);
-            box-shadow: var(--hover-shadow);
-        }
-
-        .icon {
-            display: inline-flex;
-            align-items: center;
-            justify-content: center;
-            width: 32px;
-            height: 32px;
-            border-radius: 8px;
-            background: var(--primary-light);
-            color: var(--primary-color);
-            font-size: 1.2em;
-            transition: all 0.3s ease;
-        }
-
-        .file-summary:hover .icon,
-        .directory-section:hover .icon {
-            transform: scale(1.1);
-            background: var(--primary-color);
-            color: white;
-        }
-
-        /* Smooth scrolling */
-        html {
-            scroll-behavior: smooth;
-        }
-
-        /* Selection style */
-        ::selection {
-            background: var(--primary-light);
-            color: var(--primary-color);
-        }
-
-        /* Print styles */
-        @media print {
-            body {
-                background: white;
-            }
-            .container {
-                box-shadow: none;
-                padding: 0;
-            }
-            .file-summary, .failed-files {
-                break-inside: avoid;
-                box-shadow: none;
-            }
-            .icon {
-                display: none;
-            }
-        }
-
-        /* Responsive design */
-        @media (max-width: 768px) {
-            body {
-                padding: 1rem;
-                font-size: 15px;
-            }
-            
-            .container {
-                padding: 1.5rem;
-            }
-
-            h1 {
-                font-size: 2.2em;
-                margin: 1.5rem 0 2rem;
-            }
-
-            h2 {
-                font-size: 1.7em;
-            }
-
-            h3 {
-                font-size: 1.4em;
-            }
-
-            .summary, .failed-files, .directory-section {
-                padding: 1.5rem;
-            }
-
-            .file-summary {
-                padding: 1.2rem;
-            }
-
-            .icon {
-                width: 28px;
-                height: 28px;
-            }
-        }
-
-        /* Dark mode support */
-        @media (prefers-color-scheme: dark) {
-            :root {
-                --primary-light: rgba(37, 99, 235, 0.15);
-                --background-color: #0f172a;
-                --text-color: #e2e8f0;
-                --text-light: #94a3b8;
-                --border-color: #1e293b;
-                --error-light: rgba(239, 68, 68, 0.15);
-            }
-
-            .container, .file-summary {
-                background: #1e293b;
-            }
-
-            .directory-section {
-                background: #0f172a;
-            }
-
-            .directory-section:hover {
-                background: #1e293b;
-            }
         }
         """
 
@@ -746,12 +398,10 @@ class HtmlFormatter(DocumentFormatter):
             return ""
 
         failed_files_html = ['<div class="failed-files">']
-        failed_files_html.append('<h2><span class="icon">⚠️</span> 处理失败的文件</h2>')
+        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(
+            failed_files_html.append(f"<li><strong>{os.path.basename(fp)}:</strong> {reason}</li>")
-                f'<li><strong>📄 {os.path.basename(fp)}</strong><br><span style="color: var(--text-light)">{reason}</span></li>'
-            )
         failed_files_html.append("</ul></div>")
         return "\n".join(failed_files_html)
 
@@ -764,49 +414,37 @@ class HtmlFormatter(DocumentFormatter):
             dir_path = os.path.dirname(path)
             if dir_path != current_dir:
                 if dir_path:
-                    formatted_html.append('<div class="directory-section">')
+                    formatted_html.append(f'<h2>📁 {dir_path}</h2>')
-                    formatted_html.append(f'<h2><span class="icon">📁</span> {dir_path}</h2>')
-                    formatted_html.append('</div>')
                 current_dir = dir_path
 
             file_name = os.path.basename(path)
             formatted_html.append('<div class="file-summary">')
-            formatted_html.append(f'<h3><span class="icon">📄</span> {file_name}</h3>')
+            formatted_html.append(f'<h3>📄 {file_name}</h3>')
-            formatted_html.append(self.md.convert(self.file_summaries_map[path]))
+            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:
-        """生成HTML文档
-        Returns:
-            str: 完整的HTML文档字符串
-        """
         return f"""
         <!DOCTYPE html>
-        <html lang="zh-CN">
+        <html>
         <head>
-            <meta charset="utf-8">
+            <meta charset='utf-8'>
-            <meta name="viewport" content="width=device-width, initial-scale=1">
             <title>文档总结报告</title>
-            <link href="https://cdnjs.cloudflare.com/ajax/libs/inter/3.19.3/inter.css" rel="stylesheet">
-            <link href="https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@400;600&display=swap" rel="stylesheet">
             <style>{self.css_styles}</style>
         </head>
         <body>
-            <div class="container">
+            <h1>📑 文档总结报告</h1>
-                <h1><span class="icon">📑</span> 文档总结报告</h1>
+            <h2>总体摘要</h2>
-                <div class="summary">
+            <div class="summary">{self.final_summary}</div>
-                    <h2><span class="icon">📋</span> 总体摘要</h2>
+            {self.format_failed_files()}
-                    <p>{self.md.convert(self.final_summary)}</p>
+            <div class="details">
-                </div>
+                <h2>📚 各文件详细总结</h2>
-                {self.format_failed_files()}
+                {self.format_file_summaries()}
-                <div class="details">
-                    <h2><span class="icon">📚</span> 各文件详细总结</h2>
-                    {self.format_file_summaries()}
-                </div>
             </div>
-
         </body>
         </html>
-        """
+        """
+
+

crazy_functions/doc_fns/content_folder.py

@@ -1,237 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Any, Dict, Optional, Type, TypeVar, Generic, Union
-
-from dataclasses import dataclass
-from enum import Enum, auto
-import logging
-from datetime import datetime
-
-# 设置日志
-logger = logging.getLogger(__name__)
-
-
-# 自定义异常类定义
-class FoldingError(Exception):
-    """折叠相关的自定义异常基类"""
-    pass
-
-
-class FormattingError(FoldingError):
-    """格式化过程中的错误"""
-    pass
-
-
-class MetadataError(FoldingError):
-    """元数据相关的错误"""
-    pass
-
-
-class ValidationError(FoldingError):
-    """验证错误"""
-    pass
-
-
-class FoldingStyle(Enum):
-    """折叠样式枚举"""
-    SIMPLE = auto()  # 简单折叠
-    DETAILED = auto()  # 详细折叠（带有额外信息）
-    NESTED = auto()  # 嵌套折叠
-
-
-@dataclass
-class FoldingOptions:
-    """折叠选项配置"""
-    style: FoldingStyle = FoldingStyle.DETAILED
-    code_language: Optional[str] = None  # 代码块的语言
-    show_timestamp: bool = False  # 是否显示时间戳
-    indent_level: int = 0  # 缩进级别
-    custom_css: Optional[str] = None  # 自定义CSS类
-
-
-T = TypeVar('T')  # 用于泛型类型
-
-
-class BaseMetadata(ABC):
-    """元数据基类"""
-
-    @abstractmethod
-    def validate(self) -> bool:
-        """验证元数据的有效性"""
-        pass
-
-    def _validate_non_empty_str(self, value: Optional[str]) -> bool:
-        """验证字符串非空"""
-        return bool(value and value.strip())
-
-
-@dataclass
-class FileMetadata(BaseMetadata):
-    """文件元数据"""
-    rel_path: str
-    size: float
-    last_modified: Optional[datetime] = None
-    mime_type: Optional[str] = None
-    encoding: str = 'utf-8'
-
-    def validate(self) -> bool:
-        """验证文件元数据的有效性"""
-        try:
-            if not self._validate_non_empty_str(self.rel_path):
-                return False
-            if self.size < 0:
-                return False
-            return True
-        except Exception as e:
-            logger.error(f"File metadata validation error: {str(e)}")
-            return False
-
-
-
-
-class ContentFormatter(ABC, Generic[T]):
-    """内容格式化抽象基类
-
-    支持泛型类型参数，可以指定具体的元数据类型。
-    """
-
-    @abstractmethod
-    def format(self,
-               content: str,
-               metadata: T,
-               options: Optional[FoldingOptions] = None) -> str:
-        """格式化内容
-
-        Args:
-            content: 需要格式化的内容
-            metadata: 类型化的元数据
-            options: 折叠选项
-
-        Returns:
-            str: 格式化后的内容
-
-        Raises:
-            FormattingError: 格式化过程中的错误
-        """
-        pass
-
-    def _create_summary(self, metadata: T) -> str:
-        """创建折叠摘要，可被子类重写"""
-        return str(metadata)
-
-    def _format_content_block(self,
-                              content: str,
-                              options: Optional[FoldingOptions]) -> str:
-        """格式化内容块，处理代码块等特殊格式"""
-        if not options:
-            return content
-
-        if options.code_language:
-            return f"```{options.code_language}\n{content}\n```"
-        return content
-
-    def _add_indent(self, text: str, level: int) -> str:
-        """添加缩进"""
-        if level <= 0:
-            return text
-        indent = "  " * level
-        return "\n".join(indent + line for line in text.splitlines())
-
-
-class FileContentFormatter(ContentFormatter[FileMetadata]):
-    """文件内容格式化器"""
-
-    def format(self,
-               content: str,
-               metadata: FileMetadata,
-               options: Optional[FoldingOptions] = None) -> str:
-        """格式化文件内容"""
-        if not metadata.validate():
-            raise MetadataError("Invalid file metadata")
-
-        try:
-            options = options or FoldingOptions()
-
-            # 构建摘要信息
-            summary_parts = [
-                f"{metadata.rel_path} ({metadata.size:.2f}MB)",
-                f"Type: {metadata.mime_type}" if metadata.mime_type else None,
-                (f"Modified: {metadata.last_modified.strftime('%Y-%m-%d %H:%M:%S')}"
-                 if metadata.last_modified and options.show_timestamp else None)
-            ]
-            summary = " | ".join(filter(None, summary_parts))
-
-            # 构建HTML类
-            css_class = f' class="{options.custom_css}"' if options.custom_css else ''
-
-            # 格式化内容
-            formatted_content = self._format_content_block(content, options)
-
-            # 组装最终结果
-            result = (
-                f'<details{css_class}><summary>{summary}</summary>\n\n'
-                f'{formatted_content}\n\n'
-                f'</details>\n\n'
-            )
-
-            return self._add_indent(result, options.indent_level)
-
-        except Exception as e:
-            logger.error(f"Error formatting file content: {str(e)}")
-            raise FormattingError(f"Failed to format file content: {str(e)}")
-
-
-class ContentFoldingManager:
-    """内容折叠管理器"""
-
-    def __init__(self):
-        """初始化折叠管理器"""
-        self._formatters: Dict[str, ContentFormatter] = {}
-        self._register_default_formatters()
-
-    def _register_default_formatters(self) -> None:
-        """注册默认的格式化器"""
-        self.register_formatter('file', FileContentFormatter())
-
-    def register_formatter(self, name: str, formatter: ContentFormatter) -> None:
-        """注册新的格式化器"""
-        if not isinstance(formatter, ContentFormatter):
-            raise TypeError("Formatter must implement ContentFormatter interface")
-        self._formatters[name] = formatter
-
-    def _guess_language(self, extension: str) -> Optional[str]:
-        """根据文件扩展名猜测编程语言"""
-        extension = extension.lower().lstrip('.')
-        language_map = {
-            'py': 'python',
-            'js': 'javascript',
-            'java': 'java',
-            'cpp': 'cpp',
-            'cs': 'csharp',
-            'html': 'html',
-            'css': 'css',
-            'md': 'markdown',
-            'json': 'json',
-            'xml': 'xml',
-            'sql': 'sql',
-            'sh': 'bash',
-            'yaml': 'yaml',
-            'yml': 'yaml',
-            'txt': None  # 纯文本不需要语言标识
-        }
-        return language_map.get(extension)
-
-    def format_content(self,
-                       content: str,
-                       formatter_type: str,
-                       metadata: Union[FileMetadata],
-                       options: Optional[FoldingOptions] = None) -> str:
-        """格式化内容"""
-        formatter = self._formatters.get(formatter_type)
-        if not formatter:
-            raise KeyError(f"No formatter registered for type: {formatter_type}")
-
-        if not isinstance(metadata, FileMetadata):
-            raise TypeError("Invalid metadata type")
-
-        return formatter.format(content, metadata, options)
-

crazy_functions/doc_fns/conversation_doc/excel_doc.py

@@ -1,211 +0,0 @@
-import re
-import os
-import pandas as pd
-from datetime import datetime
-from openpyxl import Workbook
-
-
-class ExcelTableFormatter:
-    """聊天记录中Markdown表格转Excel生成器"""
-
-    def __init__(self):
-        """初始化Excel文档对象"""
-        self.workbook = Workbook()
-        self._table_count = 0
-        self._current_sheet = None
-
-    def _normalize_table_row(self, row):
-        """标准化表格行，处理不同的分隔符情况"""
-        row = row.strip()
-        if row.startswith('|'):
-            row = row[1:]
-        if row.endswith('|'):
-            row = row[:-1]
-        return [cell.strip() for cell in row.split('|')]
-
-    def _is_separator_row(self, row):
-        """检查是否是分隔行（由 - 或 : 组成）"""
-        clean_row = re.sub(r'[\s|]', '', row)
-        return bool(re.match(r'^[-:]+$', clean_row))
-
-    def _extract_tables_from_text(self, text):
-        """从文本中提取所有表格内容"""
-        if not isinstance(text, str):
-            return []
-
-        tables = []
-        current_table = []
-        is_in_table = False
-
-        for line in text.split('\n'):
-            line = line.strip()
-            if not line:
-                if is_in_table and current_table:
-                    if len(current_table) >= 2:
-                        tables.append(current_table)
-                    current_table = []
-                    is_in_table = False
-                continue
-
-            if '|' in line:
-                if not is_in_table:
-                    is_in_table = True
-                current_table.append(line)
-            else:
-                if is_in_table and current_table:
-                    if len(current_table) >= 2:
-                        tables.append(current_table)
-                    current_table = []
-                    is_in_table = False
-
-        if is_in_table and current_table and len(current_table) >= 2:
-            tables.append(current_table)
-
-        return tables
-
-    def _parse_table(self, table_lines):
-        """解析表格内容为结构化数据"""
-        try:
-            headers = self._normalize_table_row(table_lines[0])
-
-            separator_index = next(
-                (i for i, line in enumerate(table_lines) if self._is_separator_row(line)),
-                1
-            )
-
-            data_rows = []
-            for line in table_lines[separator_index + 1:]:
-                cells = self._normalize_table_row(line)
-                # 确保单元格数量与表头一致
-                while len(cells) < len(headers):
-                    cells.append('')
-                cells = cells[:len(headers)]
-                data_rows.append(cells)
-
-            if headers and data_rows:
-                return {
-                    'headers': headers,
-                    'data': data_rows
-                }
-        except Exception as e:
-            print(f"解析表格时发生错误: {str(e)}")
-
-        return None
-
-    def _create_sheet(self, question_num, table_num):
-        """创建新的工作表"""
-        sheet_name = f'Q{question_num}_T{table_num}'
-        if len(sheet_name) > 31:
-            sheet_name = f'Table{self._table_count}'
-
-        if sheet_name in self.workbook.sheetnames:
-            sheet_name = f'{sheet_name}_{datetime.now().strftime("%H%M%S")}'
-
-        return self.workbook.create_sheet(title=sheet_name)
-
-    def create_document(self, history):
-        """
-        处理聊天历史中的所有表格并创建Excel文档
-
-        Args:
-            history: 聊天历史列表
-
-        Returns:
-            Workbook: 处理完成的Excel工作簿对象，如果没有表格则返回None
-        """
-        has_tables = False
-
-        # 删除默认创建的工作表
-        default_sheet = self.workbook['Sheet']
-        self.workbook.remove(default_sheet)
-
-        # 遍历所有回答
-        for i in range(1, len(history), 2):
-            answer = history[i]
-            tables = self._extract_tables_from_text(answer)
-
-            for table_lines in tables:
-                parsed_table = self._parse_table(table_lines)
-                if parsed_table:
-                    self._table_count += 1
-                    sheet = self._create_sheet(i // 2 + 1, self._table_count)
-
-                    # 写入表头
-                    for col, header in enumerate(parsed_table['headers'], 1):
-                        sheet.cell(row=1, column=col, value=header)
-
-                    # 写入数据
-                    for row_idx, row_data in enumerate(parsed_table['data'], 2):
-                        for col_idx, value in enumerate(row_data, 1):
-                            sheet.cell(row=row_idx, column=col_idx, value=value)
-
-                    has_tables = True
-
-        return self.workbook if has_tables else None
-
-
-def save_chat_tables(history, save_dir, base_name):
-    """
-    保存聊天历史中的表格到Excel文件
-
-    Args:
-        history: 聊天历史列表
-        save_dir: 保存目录
-        base_name: 基础文件名
-
-    Returns:
-        list: 保存的文件路径列表
-    """
-    result_files = []
-
-    try:
-        # 创建Excel格式
-        excel_formatter = ExcelTableFormatter()
-        workbook = excel_formatter.create_document(history)
-
-        if workbook is not None:
-            # 确保保存目录存在
-            os.makedirs(save_dir, exist_ok=True)
-
-            # 生成Excel文件路径
-            excel_file = os.path.join(save_dir, base_name + '.xlsx')
-
-            # 保存Excel文件
-            workbook.save(excel_file)
-            result_files.append(excel_file)
-            print(f"已保存表格到Excel文件: {excel_file}")
-    except Exception as e:
-        print(f"保存Excel格式失败: {str(e)}")
-
-    return result_files
-
-
-# 使用示例
-if __name__ == "__main__":
-    # 示例聊天历史
-    history = [
-        "问题1",
-        """这是第一个表格：
-        | A | B | C |
-        |---|---|---|
-        | 1 | 2 | 3 |""",
-
-        "问题2",
-        "这是没有表格的回答",
-
-        "问题3",
-        """回答包含多个表格：
-        | Name | Age |
-        |------|-----|
-        | Tom  | 20  |
-
-        第二个表格：
-        | X | Y |
-        |---|---|
-        | 1 | 2 |"""
-    ]
-
-    # 保存表格
-    save_dir = "output"
-    base_name = "chat_tables"
-    saved_files = save_chat_tables(history, save_dir, base_name)

crazy_functions/doc_fns/conversation_doc/html_doc.py

@@ -1,190 +0,0 @@
-
-
-class HtmlFormatter:
-    """聊天记录HTML格式生成器"""
-    
-    def __init__(self, chatbot, history):
-        self.chatbot = chatbot
-        self.history = history
-        self.css_styles = """
-        :root {
-            --primary-color: #2563eb;
-            --primary-light: #eff6ff;
-            --secondary-color: #1e293b;
-            --background-color: #f8fafc;
-            --text-color: #334155;
-            --border-color: #e2e8f0;
-            --card-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
-        }
-
-        body {
-            font-family: system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
-            line-height: 1.8;
-            margin: 0;
-            padding: 2rem;
-            color: var(--text-color);
-            background-color: var(--background-color);
-        }
-
-        .container {
-            max-width: 1200px;
-            margin: 0 auto;
-            background: white;
-            padding: 2rem;
-            border-radius: 16px;
-            box-shadow: var(--card-shadow);
-        }
-        ::selection {
-            background: var(--primary-light);
-            color: var(--primary-color);
-        }
-        @keyframes fadeIn {
-            from { opacity: 0; transform: translateY(20px); }
-            to { opacity: 1; transform: translateY(0); }
-        }
-        
-        @keyframes slideIn {
-            from { transform: translateX(-20px); opacity: 0; }
-            to { transform: translateX(0); opacity: 1; }
-        }
-        
-        .container {
-            animation: fadeIn 0.6s ease-out;
-        }
-        
-        .QaBox {
-            animation: slideIn 0.5s ease-out;
-            transition: all 0.3s ease;
-        }
-        
-        .QaBox:hover {
-            transform: translateX(5px);
-        }
-        .Question, .Answer, .historyBox {
-            transition: all 0.3s ease;
-        }
-        .chat-title {
-            color: var(--primary-color);
-            font-size: 2em;
-            text-align: center;
-            margin: 1rem 0 2rem;
-            padding-bottom: 1rem;
-            border-bottom: 2px solid var(--primary-color);
-        }
-
-        .chat-body {
-            display: flex;
-            flex-direction: column;
-            gap: 1.5rem;
-            margin: 2rem 0;
-        }
-
-        .QaBox {
-            background: white;
-            padding: 1.5rem;
-            border-radius: 8px;
-            border-left: 4px solid var(--primary-color);
-            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
-            margin-bottom: 1.5rem;
-        }
-
-        .Question {
-            color: var(--secondary-color);
-            font-weight: 500;
-            margin-bottom: 1rem;
-        }
-
-        .Answer {
-            color: var(--text-color);
-            background: var(--primary-light);
-            padding: 1rem;
-            border-radius: 6px;
-        }
-
-        .history-section {
-            margin-top: 3rem;
-            padding-top: 2rem;
-            border-top: 2px solid var(--border-color);
-        }
-
-        .history-title {
-            color: var(--secondary-color);
-            font-size: 1.5em;
-            margin-bottom: 1.5rem;
-            text-align: center;
-        }
-
-        .historyBox {
-            background: white;
-            padding: 1rem;
-            margin: 0.5rem 0;
-            border-radius: 6px;
-            border: 1px solid var(--border-color);
-        }
-
-        @media (prefers-color-scheme: dark) {
-            :root {
-                --background-color: #0f172a;
-                --text-color: #e2e8f0;
-                --border-color: #1e293b;
-            }
-            
-            .container, .QaBox {
-                background: #1e293b;
-            }
-        }
-        """
-
-    def format_chat_content(self) -> str:
-        """格式化聊天内容"""
-        chat_content = []
-        for q, a in self.chatbot:
-            question = str(q) if q is not None else ""
-            answer = str(a) if a is not None else ""
-            chat_content.append(f'''
-            <div class="QaBox">
-                <div class="Question">{question}</div>
-                <div class="Answer">{answer}</div>
-            </div>
-            ''')
-        return "\n".join(chat_content)
-
-    def format_history_content(self) -> str:
-        """格式化历史记录内容"""
-        if not self.history:
-            return ""
-            
-        history_content = []
-        for entry in self.history:
-            history_content.append(f'''
-            <div class="historyBox">
-                <div class="entry">{entry}</div>
-            </div>
-            ''')
-        return "\n".join(history_content)
-
-    def create_document(self) -> str:
-        """生成完整的HTML文档
-        
-        Returns:
-            str: 完整的HTML文档字符串
-        """
-        return f"""
-        <!DOCTYPE html>
-        <html lang="zh-CN">
-        <head>
-            <meta charset="utf-8">
-            <meta name="viewport" content="width=device-width, initial-scale=1">
-            <title>对话存档</title>
-            <style>{self.css_styles}</style>
-        </head>
-        <body>
-            <div class="container">
-                <h1 class="chat-title">对话存档</h1>
-                <div class="chat-body">
-                    {self.format_chat_content()}
-                </div>
-            </div>
-        </body>
-        </html>
-        """

crazy_functions/doc_fns/conversation_doc/markdown_doc.py

@@ -1,39 +0,0 @@
-
-class MarkdownFormatter:
-    """Markdown格式文档生成器 - 用于生成对话记录的markdown文档"""
-
-    def __init__(self):
-        self.content = []
-
-    def _add_content(self, text: str):
-        """添加正文内容"""
-        if text:
-            self.content.append(f"\n{text}\n")
-
-    def create_document(self, history: list) -> str:
-        """
-        创建完整的Markdown文档
-        Args:
-            history: 历史记录列表，偶数位置为问题，奇数位置为答案
-        Returns:
-            str: 生成的Markdown文本
-        """
-        self.content = []
-        
-        # 处理问答对
-        for i in range(0, len(history), 2):
-            question = history[i]
-            answer = history[i + 1]
-            
-            # 添加问题
-            self.content.append(f"\n### 问题 {i//2 + 1}")
-            self._add_content(question)
-            
-            # 添加回答
-            self.content.append(f"\n### 回答 {i//2 + 1}")
-            self._add_content(answer)
-            
-            # 添加分隔线
-            self.content.append("\n---\n")
-
-        return "\n".join(self.content)

crazy_functions/doc_fns/conversation_doc/pdf_doc.py

@@ -1,172 +0,0 @@
-from datetime import datetime
-import os
-import re
-from reportlab.pdfbase import pdfmetrics
-from reportlab.pdfbase.ttfonts import TTFont
-
-def convert_markdown_to_pdf(markdown_text):
-    """将Markdown文本转换为PDF格式的纯文本"""
-    if not markdown_text:
-        return ""
-
-    # 标准化换行符
-    markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
-
-    # 处理标题、粗体、斜体
-    markdown_text = re.sub(r'^#\s+(.+)$', r'\1', markdown_text, flags=re.MULTILINE)
-    markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)
-    markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)
-
-    # 处理列表
-    markdown_text = re.sub(r'^\s*[-*+]\s+(.+?)(?=\n|$)', r'• \1', markdown_text, flags=re.MULTILINE)
-    markdown_text = re.sub(r'^\s*\d+\.\s+(.+?)(?=\n|$)', r'\1', markdown_text, flags=re.MULTILINE)
-
-    # 处理链接
-    markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+)\)', r'\1', markdown_text)
-
-    # 处理段落
-    markdown_text = re.sub(r'\n{2,}', '\n', markdown_text)
-    markdown_text = re.sub(r'(?<!\n)(?<!^)(?<!•\s)(?<!\d\.\s)\n(?![\s•\d])', '\n\n', markdown_text, flags=re.MULTILINE)
-
-    # 清理空白
-    markdown_text = re.sub(r' +', ' ', markdown_text)
-    markdown_text = re.sub(r'(?m)^\s+|\s+$', '', markdown_text)
-
-    return markdown_text.strip()
-
-class PDFFormatter:
-    """聊天记录PDF文档生成器 - 使用 Noto Sans CJK 字体"""
-
-    def __init__(self):
-        self._init_reportlab()
-        self._register_fonts()
-        self.styles = self._get_reportlab_lib()['getSampleStyleSheet']()
-        self._create_styles()
-
-    def _init_reportlab(self):
-        """初始化 ReportLab 相关组件"""
-        from reportlab.lib.pagesizes import A4
-        from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
-        from reportlab.lib.units import cm
-        from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
-        
-        self._lib = {
-            'A4': A4,
-            'getSampleStyleSheet': getSampleStyleSheet,
-            'ParagraphStyle': ParagraphStyle,
-            'cm': cm
-        }
-        
-        self._platypus = {
-            'SimpleDocTemplate': SimpleDocTemplate,
-            'Paragraph': Paragraph,
-            'Spacer': Spacer
-        }
-
-    def _get_reportlab_lib(self):
-        return self._lib
-
-    def _get_reportlab_platypus(self):
-        return self._platypus
-
-    def _register_fonts(self):
-        """注册 Noto Sans CJK 字体"""
-        possible_font_paths = [
-            '/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc',
-            '/usr/share/fonts/noto-cjk/NotoSansCJK-Regular.ttc',
-            '/usr/share/fonts/noto/NotoSansCJK-Regular.ttc'
-        ]
-
-        font_registered = False
-        for path in possible_font_paths:
-            if os.path.exists(path):
-                try:
-                    pdfmetrics.registerFont(TTFont('NotoSansCJK', path))
-                    font_registered = True
-                    break
-                except:
-                    continue
-
-        if not font_registered:
-            print("Warning: Could not find Noto Sans CJK font. Using fallback font.")
-            self.font_name = 'Helvetica'
-        else:
-            self.font_name = 'NotoSansCJK'
-
-    def _create_styles(self):
-        """创建文档样式"""
-        ParagraphStyle = self._lib['ParagraphStyle']
-
-        # 标题样式
-        self.styles.add(ParagraphStyle(
-            name='Title_Custom',
-            fontName=self.font_name,
-            fontSize=24,
-            leading=38,
-            alignment=1,
-            spaceAfter=32
-        ))
-
-        # 日期样式
-        self.styles.add(ParagraphStyle(
-            name='Date_Style',
-            fontName=self.font_name,
-            fontSize=16,
-            leading=20,
-            alignment=1,
-            spaceAfter=20
-        ))
-
-        # 问题样式
-        self.styles.add(ParagraphStyle(
-            name='Question_Style',
-            fontName=self.font_name,
-            fontSize=12,
-            leading=18,
-            leftIndent=28,
-            spaceAfter=6
-        ))
-
-        # 回答样式
-        self.styles.add(ParagraphStyle(
-            name='Answer_Style',
-            fontName=self.font_name,
-            fontSize=12,
-            leading=18,
-            leftIndent=28,
-            spaceAfter=12
-        ))
-
-    def create_document(self, history, output_path):
-        """生成PDF文档"""
-        # 创建PDF文档
-        doc = self._platypus['SimpleDocTemplate'](
-            output_path,
-            pagesize=self._lib['A4'],
-            rightMargin=2.6 * self._lib['cm'],
-            leftMargin=2.8 * self._lib['cm'],
-            topMargin=3.7 * self._lib['cm'],
-            bottomMargin=3.5 * self._lib['cm']
-        )
-
-        # 构建内容
-        story = []
-        Paragraph = self._platypus['Paragraph']
-
-        # 添加对话内容
-        for i in range(0, len(history), 2):
-            question = history[i]
-            answer = convert_markdown_to_pdf(history[i + 1]) if i + 1 < len(history) else ""
-
-            if question:
-                q_text = f'问题 {i // 2 + 1}：{str(question)}'
-                story.append(Paragraph(q_text, self.styles['Question_Style']))
-
-            if answer:
-                a_text = f'回答 {i // 2 + 1}：{str(answer)}'
-                story.append(Paragraph(a_text, self.styles['Answer_Style']))
-
-        # 构建PDF
-        doc.build(story)
-
-        return doc

crazy_functions/doc_fns/conversation_doc/txt_doc.py

@@ -1,79 +0,0 @@
-
-import re
-
-
-def convert_markdown_to_txt(markdown_text):
-    """Convert markdown text to plain text while preserving formatting"""
-    # Standardize line endings
-    markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
-
-    # 1. Handle headers but keep their formatting instead of removing them
-    markdown_text = re.sub(r'^#\s+(.+)$', r'# \1', markdown_text, flags=re.MULTILINE)
-    markdown_text = re.sub(r'^##\s+(.+)$', r'## \1', markdown_text, flags=re.MULTILINE)
-    markdown_text = re.sub(r'^###\s+(.+)$', r'### \1', markdown_text, flags=re.MULTILINE)
-
-    # 2. Handle bold and italic - simply remove markers
-    markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)
-    markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)
-
-    # 3. Handle lists but preserve formatting
-    markdown_text = re.sub(r'^\s*[-*+]\s+(.+?)(?=\n|$)', r'• \1', markdown_text, flags=re.MULTILINE)
-
-    # 4. Handle links - keep only the text
-    markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+)\)', r'\1 (\2)', markdown_text)
-
-    # 5. Handle HTML links - convert to user-friendly format
-    markdown_text = re.sub(r'<a href=[\'"]([^\'"]+)[\'"](?:\s+target=[\'"][^\'"]+[\'"])?>([^<]+)</a>', r'\2 (\1)',
-                           markdown_text)
-
-    # 6. Preserve paragraph breaks
-    markdown_text = re.sub(r'\n{3,}', '\n\n', markdown_text)  # normalize multiple newlines to double newlines
-
-    # 7. Clean up extra spaces but maintain indentation
-    markdown_text = re.sub(r' +', ' ', markdown_text)
-
-    return markdown_text.strip()
-
-
-class TxtFormatter:
-    """Chat history TXT document generator"""
-
-    def __init__(self):
-        self.content = []
-        self._setup_document()
-
-    def _setup_document(self):
-        """Initialize document with header"""
-        self.content.append("=" * 50)
-        self.content.append("GPT-Academic对话记录".center(48))
-        self.content.append("=" * 50)
-
-    def _format_header(self):
-        """Create document header with current date"""
-        from datetime import datetime
-        date_str = datetime.now().strftime('%Y年%m月%d日')
-        return [
-            date_str.center(48),
-            "\n"  # Add blank line after date
-        ]
-
-    def create_document(self, history):
-        """Generate document from chat history"""
-        # Add header with date
-        self.content.extend(self._format_header())
-
-        # Add conversation content
-        for i in range(0, len(history), 2):
-            question = history[i]
-            answer = convert_markdown_to_txt(history[i + 1]) if i + 1 < len(history) else ""
-
-            if question:
-                self.content.append(f"问题 {i // 2 + 1}：{str(question)}")
-                self.content.append("")  # Add blank line
-
-            if answer:
-                self.content.append(f"回答 {i // 2 + 1}：{str(answer)}")
-                self.content.append("")  # Add blank line
-
-        # Join all content with newlines
-        return "\n".join(self.content)

crazy_functions/doc_fns/conversation_doc/word2pdf.py

@@ -1,155 +0,0 @@
-from docx2pdf import convert
-import os
-import platform
-import subprocess
-from typing import Union
-from pathlib import Path
-from datetime import datetime
-
-class WordToPdfConverter:
-    """Word文档转PDF转换器"""
-    
-    @staticmethod
-    def convert_to_pdf(word_path: Union[str, Path], pdf_path: Union[str, Path] = None) -> str:
-        """
-        将Word文档转换为PDF
-        
-        参数:
-            word_path: Word文档的路径
-            pdf_path: 可选，PDF文件的输出路径。如果未指定，将使用与Word文档相同的名称和位置
-            
-        返回:
-            生成的PDF文件路径
-        
-        异常:
-            如果转换失败，将抛出相应异常
-        """
-        try:
-            # 确保输入路径是Path对象
-            word_path = Path(word_path)
-            
-            # 如果未指定pdf_path，则使用与word文档相同的名称
-            if pdf_path is None:
-                pdf_path = word_path.with_suffix('.pdf')
-            else:
-                pdf_path = Path(pdf_path)
-            
-            # 检查操作系统
-            if platform.system() == 'Linux':
-                # Linux系统需要安装libreoffice
-                which_result = subprocess.run(['which', 'libreoffice'], capture_output=True, text=True)
-                if which_result.returncode != 0:
-                    raise RuntimeError("请先安装LibreOffice: sudo apt-get install libreoffice")
-                
-                print(f"开始转换Word文档: {word_path} 到 PDF")
-                
-                # 使用subprocess代替os.system
-                result = subprocess.run(
-                    ['libreoffice', '--headless', '--convert-to', 'pdf:writer_pdf_Export', 
-                     str(word_path), '--outdir', str(pdf_path.parent)],
-                    capture_output=True, text=True
-                )
-                
-                if result.returncode != 0:
-                    error_msg = result.stderr or "未知错误"
-                    print(f"LibreOffice转换失败，错误信息: {error_msg}")
-                    raise RuntimeError(f"LibreOffice转换失败: {error_msg}")
-                
-                print(f"LibreOffice转换输出: {result.stdout}")
-                
-                # 如果输出路径与默认生成的不同，则重命名
-                default_pdf = word_path.with_suffix('.pdf')
-                if default_pdf != pdf_path and default_pdf.exists():
-                    os.rename(default_pdf, pdf_path)
-                    print(f"已将PDF从 {default_pdf} 重命名为 {pdf_path}")
-                
-                # 验证PDF是否成功生成
-                if not pdf_path.exists() or pdf_path.stat().st_size == 0:
-                    raise RuntimeError("PDF生成失败或文件为空")
-                
-                print(f"PDF转换成功，文件大小: {pdf_path.stat().st_size} 字节")
-            else:
-                # Windows和MacOS使用docx2pdf
-                print(f"使用docx2pdf转换 {word_path} 到 {pdf_path}")
-                convert(word_path, pdf_path)
-                
-                # 验证PDF是否成功生成
-                if not pdf_path.exists() or pdf_path.stat().st_size == 0:
-                    raise RuntimeError("PDF生成失败或文件为空")
-                    
-                print(f"PDF转换成功，文件大小: {pdf_path.stat().st_size} 字节")
-            
-            return str(pdf_path)
-            
-        except Exception as e:
-            print(f"PDF转换异常: {str(e)}")
-            raise Exception(f"转换PDF失败: {str(e)}")
-
-    @staticmethod
-    def batch_convert(word_dir: Union[str, Path], pdf_dir: Union[str, Path] = None) -> list:
-        """
-        批量转换目录下的所有Word文档
-        
-        参数:
-            word_dir: 包含Word文档的目录路径
-            pdf_dir: 可选，PDF文件的输出目录。如果未指定，将使用与Word文档相同的目录
-            
-        返回:
-            生成的PDF文件路径列表
-        """
-        word_dir = Path(word_dir)
-        if pdf_dir:
-            pdf_dir = Path(pdf_dir)
-            pdf_dir.mkdir(parents=True, exist_ok=True)
-            
-        converted_files = []
-        
-        for word_file in word_dir.glob("*.docx"):
-            try:
-                if pdf_dir:
-                    pdf_path = pdf_dir / word_file.with_suffix('.pdf').name
-                else:
-                    pdf_path = word_file.with_suffix('.pdf')
-                    
-                pdf_file = WordToPdfConverter.convert_to_pdf(word_file, pdf_path)
-                converted_files.append(pdf_file)
-                
-            except Exception as e:
-                print(f"转换 {word_file} 失败: {str(e)}")
-                
-        return converted_files
-
-    @staticmethod
-    def convert_doc_to_pdf(doc, output_dir: Union[str, Path] = None) -> str:
-        """
-        将docx对象直接转换为PDF
-        
-        参数:
-            doc: python-docx的Document对象
-            output_dir: 可选，输出目录。如果未指定，将使用当前目录
-            
-        返回:
-            生成的PDF文件路径
-        """
-        try:
-            # 设置临时文件路径和输出路径
-            output_dir = Path(output_dir) if output_dir else Path.cwd()
-            output_dir.mkdir(parents=True, exist_ok=True)
-            
-            # 生成临时word文件
-            temp_docx = output_dir / f"temp_{datetime.now().strftime('%Y%m%d_%H%M%S')}.docx"
-            doc.save(temp_docx)
-            
-            # 转换为PDF
-            pdf_path = temp_docx.with_suffix('.pdf')
-            WordToPdfConverter.convert_to_pdf(temp_docx, pdf_path)
-            
-            # 删除临时word文件
-            temp_docx.unlink()
-            
-            return str(pdf_path)
-            
-        except Exception as e:
-            if temp_docx.exists():
-                temp_docx.unlink()
-            raise Exception(f"转换PDF失败: {str(e)}") 

crazy_functions/doc_fns/conversation_doc/word_doc.py

@@ -1,177 +0,0 @@
-import re
-from docx import Document
-from docx.shared import Cm, Pt
-from docx.enum.text import WD_PARAGRAPH_ALIGNMENT, WD_LINE_SPACING
-from docx.enum.style import WD_STYLE_TYPE
-from docx.oxml.ns import qn
-from datetime import datetime
-
-
-def convert_markdown_to_word(markdown_text):
-    # 0. 首先标准化所有换行符为\n
-    markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
-
-    # 1. 处理标题 - 支持更多级别的标题，使用更精确的正则
-    # 保留标题标记，以便后续处理时还能识别出标题级别
-    markdown_text = re.sub(r'^(#{1,6})\s+(.+?)(?:\s+#+)?$', r'\1 \2', markdown_text, flags=re.MULTILINE)
-
-    # 2. 处理粗体、斜体和加粗斜体
-    markdown_text = re.sub(r'\*\*\*(.+?)\*\*\*', r'\1', markdown_text)  # 加粗斜体
-    markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)  # 加粗
-    markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)  # 斜体
-    markdown_text = re.sub(r'_(.+?)_', r'\1', markdown_text)  # 下划线斜体
-    markdown_text = re.sub(r'__(.+?)__', r'\1', markdown_text)  # 下划线加粗
-
-    # 3. 处理代码块 - 不移除，而是简化格式
-    # 多行代码块
-    markdown_text = re.sub(r'```(?:\w+)?\n([\s\S]*?)```', r'[代码块]\n\1[/代码块]', markdown_text)
-    # 单行代码
-    markdown_text = re.sub(r'`([^`]+)`', r'[代码]\1[/代码]', markdown_text)
-
-    # 4. 处理列表 - 保留列表结构
-    # 匹配无序列表
-    markdown_text = re.sub(r'^(\s*)[-*+]\s+(.+?)$', r'\1• \2', markdown_text, flags=re.MULTILINE)
-
-    # 5. 处理Markdown链接
-    markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+?)\s*(?:"[^"]*")?\)', r'\1 (\2)', markdown_text)
-
-    # 6. 处理HTML链接
-    markdown_text = re.sub(r'<a href=[\'"]([^\'"]+)[\'"](?:\s+target=[\'"][^\'"]+[\'"])?>([^<]+)</a>', r'\2 (\1)',
-                           markdown_text)
-
-    # 7. 处理图片
-    markdown_text = re.sub(r'!\[([^\]]*)\]\([^)]+\)', r'[图片：\1]', markdown_text)
-
-    return markdown_text
-
-
-class WordFormatter:
-    """聊天记录Word文档生成器 - 符合中国政府公文格式规范(GB/T 9704-2012)"""
-
-    def __init__(self):
-        self.doc = Document()
-        self._setup_document()
-        self._create_styles()
-
-    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("GPT-Academic对话记录")
-            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(12)  # 调整为12磅
-        style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
-        style.paragraph_format.space_after = Pt(0)
-
-        # 创建问题样式
-        question_style = self.doc.styles.add_style('Question_Style', WD_STYLE_TYPE.PARAGRAPH)
-        question_style.font.name = '黑体'
-        question_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
-        question_style.font.size = Pt(14)  # 调整为14磅
-        question_style.font.bold = True
-        question_style.paragraph_format.space_before = Pt(12)  # 减小段前距
-        question_style.paragraph_format.space_after = Pt(6)
-        question_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
-        question_style.paragraph_format.left_indent = Pt(0)  # 移除左缩进
-
-        # 创建回答样式
-        answer_style = self.doc.styles.add_style('Answer_Style', WD_STYLE_TYPE.PARAGRAPH)
-        answer_style.font.name = '仿宋'
-        answer_style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
-        answer_style.font.size = Pt(12)  # 调整为12磅
-        answer_style.paragraph_format.space_before = Pt(6)
-        answer_style.paragraph_format.space_after = Pt(12)
-        answer_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
-        answer_style.paragraph_format.left_indent = Pt(0)  # 移除左缩进
-
-        # 创建标题样式
-        title_style = self.doc.styles.add_style('Title_Custom', WD_STYLE_TYPE.PARAGRAPH)
-        title_style.font.name = '黑体'  # 改用黑体
-        title_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
-        title_style.font.size = Pt(22)  # 调整为22磅
-        title_style.font.bold = True
-        title_style.paragraph_format.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
-        title_style.paragraph_format.space_before = Pt(0)
-        title_style.paragraph_format.space_after = Pt(24)
-        title_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
-
-        # 添加参考文献样式
-        ref_style = self.doc.styles.add_style('Reference_Style', WD_STYLE_TYPE.PARAGRAPH)
-        ref_style.font.name = '宋体'
-        ref_style._element.rPr.rFonts.set(qn('w:eastAsia'), '宋体')
-        ref_style.font.size = Pt(10.5)  # 参考文献使用小号字体
-        ref_style.paragraph_format.space_before = Pt(3)
-        ref_style.paragraph_format.space_after = Pt(3)
-        ref_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.SINGLE
-        ref_style.paragraph_format.left_indent = Pt(21)
-        ref_style.paragraph_format.first_line_indent = Pt(-21)
-
-        # 添加参考文献标题样式
-        ref_title_style = self.doc.styles.add_style('Reference_Title_Style', WD_STYLE_TYPE.PARAGRAPH)
-        ref_title_style.font.name = '黑体'
-        ref_title_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
-        ref_title_style.font.size = Pt(16)
-        ref_title_style.font.bold = True
-        ref_title_style.paragraph_format.space_before = Pt(24)
-        ref_title_style.paragraph_format.space_after = Pt(12)
-        ref_title_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
-
-    def create_document(self,  history):
-        """写入聊天历史"""
-        # 添加标题
-        title_para = self.doc.add_paragraph(style='Title_Custom')
-        title_run = title_para.add_run('GPT-Academic 对话记录')
-
-        # 添加日期
-        date_para = self.doc.add_paragraph()
-        date_para.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
-        date_run = date_para.add_run(datetime.now().strftime('%Y年%m月%d日'))
-        date_run.font.name = '仿宋'
-        date_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
-        date_run.font.size = Pt(16)
-
-        self.doc.add_paragraph()  # 添加空行
-
-        # 添加对话内容
-        for i in range(0, len(history), 2):
-            question = history[i]
-            answer = convert_markdown_to_word(history[i + 1])
-
-            if question:
-                q_para = self.doc.add_paragraph(style='Question_Style')
-                q_para.add_run(f'问题 {i//2 + 1}：').bold = True
-                q_para.add_run(str(question))
-
-            if answer:
-                a_para = self.doc.add_paragraph(style='Answer_Style')
-                a_para.add_run(f'回答 {i//2 + 1}：').bold = True
-                a_para.add_run(str(answer))
-
-
-        return self.doc
-

crazy_functions/doc_fns/read_fns/docx_reader.py

@@ -1,6 +0,0 @@
-import nltk
-nltk.data.path.append('~/nltk_data')
-nltk.download('averaged_perceptron_tagger', download_dir='~/nltk_data',
-             )
-nltk.download('punkt', download_dir='~/nltk_data',
-               )

crazy_functions/doc_fns/read_fns/excel_reader.py

@@ -1,286 +0,0 @@
-from __future__ import annotations
-
-import pandas as pd
-import numpy as np
-from pathlib import Path
-from typing import Optional, List, Set, Dict, Union, Iterator, Tuple
-from dataclasses import dataclass, field
-import logging
-from concurrent.futures import ThreadPoolExecutor, as_completed
-import chardet
-from functools import lru_cache
-import os
-
-
-@dataclass
-class ExtractorConfig:
-    """提取器配置类"""
-    encoding: str = 'auto'
-    na_filter: bool = True
-    skip_blank_lines: bool = True
-    chunk_size: int = 10000
-    max_workers: int = 4
-    preserve_format: bool = True
-    read_all_sheets: bool = True  # 新增：是否读取所有工作表
-    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
-        'remove_extra_spaces': True,
-        'normalize_whitespace': False,
-        'remove_special_chars': False,
-        'lowercase': False
-    })
-
-
-class ExcelTextExtractor:
-    """增强的Excel格式文件文本内容提取器"""
-
-    SUPPORTED_EXTENSIONS: Set[str] = {
-        '.xlsx', '.xls', '.csv', '.tsv', '.xlsm', '.xltx', '.xltm', '.ods'
-    }
-
-    def __init__(self, config: Optional[ExtractorConfig] = None):
-        self.config = config or ExtractorConfig()
-        self._setup_logging()
-        self._detect_encoding = lru_cache(maxsize=128)(self._detect_encoding)
-
-    def _setup_logging(self) -> None:
-        """配置日志记录器"""
-        logging.basicConfig(
-            level=logging.INFO,
-            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-        )
-        self.logger = logging.getLogger(__name__)
-        fh = logging.FileHandler('excel_extractor.log')
-        fh.setLevel(logging.ERROR)
-        self.logger.addHandler(fh)
-
-    def _detect_encoding(self, file_path: Path) -> str:
-        if self.config.encoding != 'auto':
-            return self.config.encoding
-
-        try:
-            with open(file_path, 'rb') as f:
-                raw_data = f.read(10000)
-                result = chardet.detect(raw_data)
-                return result['encoding'] or 'utf-8'
-        except Exception as e:
-            self.logger.warning(f"Encoding detection failed: {e}. Using utf-8")
-            return 'utf-8'
-
-    def _validate_file(self, file_path: Union[str, Path]) -> Path:
-        path = Path(file_path).resolve()
-
-        if not path.exists():
-            raise ValueError(f"File not found: {path}")
-
-        if not path.is_file():
-            raise ValueError(f"Not a file: {path}")
-
-        if not os.access(path, os.R_OK):
-            raise PermissionError(f"No read permission: {path}")
-
-        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
-            raise ValueError(
-                f"Unsupported format: {path.suffix}. "
-                f"Supported: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
-            )
-
-        return path
-
-    def _format_value(self, value: Any) -> str:
-        if pd.isna(value) or value is None:
-            return ''
-        if isinstance(value, (int, float)):
-            return str(value)
-        return str(value).strip()
-
-    def _process_chunk(self, chunk: pd.DataFrame, columns: Optional[List[str]] = None, sheet_name: str = '') -> str:
-        """处理数据块，新增sheet_name参数"""
-        try:
-            if columns:
-                chunk = chunk[columns]
-
-            if self.config.preserve_format:
-                formatted_chunk = chunk.applymap(self._format_value)
-                rows = []
-
-                # 添加工作表名称作为标题
-                if sheet_name:
-                    rows.append(f"[Sheet: {sheet_name}]")
-
-                # 添加表头
-                headers = [str(col) for col in formatted_chunk.columns]
-                rows.append('\t'.join(headers))
-
-                # 添加数据行
-                for _, row in formatted_chunk.iterrows():
-                    rows.append('\t'.join(row.values))
-
-                return '\n'.join(rows)
-            else:
-                flat_values = (
-                    chunk.astype(str)
-                    .replace({'nan': '', 'None': '', 'NaN': ''})
-                    .values.flatten()
-                )
-                return ' '.join(v for v in flat_values if v)
-
-        except Exception as e:
-            self.logger.error(f"Error processing chunk: {e}")
-            raise
-
-    def _read_file(self, file_path: Path) -> Union[pd.DataFrame, Iterator[pd.DataFrame], Dict[str, pd.DataFrame]]:
-        """读取文件，支持多工作表"""
-        try:
-            encoding = self._detect_encoding(file_path)
-
-            if file_path.suffix.lower() in {'.csv', '.tsv'}:
-                sep = '\t' if file_path.suffix.lower() == '.tsv' else ','
-
-                # 对大文件使用分块读取
-                if file_path.stat().st_size > self.config.chunk_size * 1024:
-                    return pd.read_csv(
-                        file_path,
-                        encoding=encoding,
-                        na_filter=self.config.na_filter,
-                        skip_blank_lines=self.config.skip_blank_lines,
-                        sep=sep,
-                        chunksize=self.config.chunk_size,
-                        on_bad_lines='warn'
-                    )
-                else:
-                    return pd.read_csv(
-                        file_path,
-                        encoding=encoding,
-                        na_filter=self.config.na_filter,
-                        skip_blank_lines=self.config.skip_blank_lines,
-                        sep=sep
-                    )
-            else:
-                # Excel文件处理，支持多工作表
-                if self.config.read_all_sheets:
-                    # 读取所有工作表
-                    return pd.read_excel(
-                        file_path,
-                        na_filter=self.config.na_filter,
-                        keep_default_na=self.config.na_filter,
-                        engine='openpyxl',
-                        sheet_name=None  # None表示读取所有工作表
-                    )
-                else:
-                    # 只读取第一个工作表
-                    return pd.read_excel(
-                        file_path,
-                        na_filter=self.config.na_filter,
-                        keep_default_na=self.config.na_filter,
-                        engine='openpyxl',
-                        sheet_name=0  # 读取第一个工作表
-                    )
-
-        except Exception as e:
-            self.logger.error(f"Error reading file {file_path}: {e}")
-            raise
-
-    def extract_text(
-            self,
-            file_path: Union[str, Path],
-            columns: Optional[List[str]] = None,
-            separator: str = '\n'
-    ) -> str:
-        """提取文本，支持多工作表"""
-        try:
-            path = self._validate_file(file_path)
-            self.logger.info(f"Processing: {path}")
-
-            reader = self._read_file(path)
-            texts = []
-
-            # 处理Excel多工作表
-            if isinstance(reader, dict):
-                for sheet_name, df in reader.items():
-                    sheet_text = self._process_chunk(df, columns, sheet_name)
-                    if sheet_text:
-                        texts.append(sheet_text)
-                return separator.join(texts)
-
-            # 处理单个DataFrame
-            elif isinstance(reader, pd.DataFrame):
-                return self._process_chunk(reader, columns)
-
-            # 处理DataFrame迭代器
-            else:
-                with ThreadPoolExecutor(max_workers=self.config.max_workers) as executor:
-                    futures = {
-                        executor.submit(self._process_chunk, chunk, columns): i
-                        for i, chunk in enumerate(reader)
-                    }
-
-                    chunk_texts = []
-                    for future in as_completed(futures):
-                        try:
-                            text = future.result()
-                            if text:
-                                chunk_texts.append((futures[future], text))
-                        except Exception as e:
-                            self.logger.error(f"Error in chunk {futures[future]}: {e}")
-
-                    # 按块的顺序排序
-                    chunk_texts.sort(key=lambda x: x[0])
-                    texts = [text for _, text in chunk_texts]
-
-                # 合并文本，保留格式
-                if texts and self.config.preserve_format:
-                    result = texts[0]  # 第一块包含表头
-                    if len(texts) > 1:
-                        # 跳过后续块的表头行
-                        for text in texts[1:]:
-                            result += '\n' + '\n'.join(text.split('\n')[1:])
-                    return result
-                else:
-                    return separator.join(texts)
-
-        except Exception as e:
-            self.logger.error(f"Extraction failed: {e}")
-            raise
-
-    @staticmethod
-    def get_supported_formats() -> List[str]:
-        """获取支持的文件格式列表"""
-        return sorted(ExcelTextExtractor.SUPPORTED_EXTENSIONS)
-
-
-def main():
-    """主函数：演示用法"""
-    config = ExtractorConfig(
-        encoding='auto',
-        preserve_format=True,
-        read_all_sheets=True,  # 启用多工作表读取
-        text_cleanup={
-            'remove_extra_spaces': True,
-            'normalize_whitespace': False,
-            'remove_special_chars': False,
-            'lowercase': False
-        }
-    )
-
-    extractor = ExcelTextExtractor(config)
-
-    try:
-        sample_file = 'example.xlsx'
-        if Path(sample_file).exists():
-            text = extractor.extract_text(
-                sample_file,
-                columns=['title', 'content']
-            )
-            print("提取的文本:")
-            print(text)
-        else:
-            print(f"示例文件 {sample_file} 不存在")
-
-        print("\n支持的格式:", extractor.get_supported_formats())
-
-    except Exception as e:
-        print(f"错误: {e}")
-
-
-if __name__ == "__main__":
-    main()

crazy_functions/doc_fns/read_fns/markitdown/markdown_reader.py

@@ -1,359 +0,0 @@
-from __future__ import annotations
-
-from pathlib import Path
-from typing import Optional, Set, Dict, Union, List
-from dataclasses import dataclass, field
-import logging
-import os
-import re
-import subprocess
-import tempfile
-import shutil
-
-@dataclass
-class MarkdownConverterConfig:
-    """PDF 到 Markdown 转换器配置类
-
-    Attributes:
-        extract_images: 是否提取图片
-        extract_tables: 是否尝试保留表格结构
-        extract_code_blocks: 是否识别代码块
-        extract_math: 是否转换数学公式
-        output_dir: 输出目录路径
-        image_dir: 图片保存目录路径
-        paragraph_separator: 段落之间的分隔符
-        text_cleanup: 文本清理选项字典
-        docintel_endpoint: Document Intelligence端点URL (可选)
-        enable_plugins: 是否启用插件
-        llm_client: LLM客户端对象 (例如OpenAI client)
-        llm_model: 要使用的LLM模型名称
-    """
-    extract_images: bool = True
-    extract_tables: bool = True
-    extract_code_blocks: bool = True
-    extract_math: bool = True
-    output_dir: str = ""
-    image_dir: str = "images"
-    paragraph_separator: str = '\n\n'
-    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
-        'remove_extra_spaces': True,
-        'normalize_whitespace': True,
-        'remove_special_chars': False,
-        'lowercase': False
-    })
-    docintel_endpoint: str = ""
-    enable_plugins: bool = False
-    llm_client: Optional[object] = None
-    llm_model: str = ""
-
-
-class MarkdownConverter:
-    """PDF 到 Markdown 转换器
-
-    使用 markitdown 库实现 PDF 到 Markdown 的转换，支持多种配置选项。
-    """
-
-    SUPPORTED_EXTENSIONS: Set[str] = {
-        '.pdf',
-    }
-
-    def __init__(self, config: Optional[MarkdownConverterConfig] = None):
-        """初始化转换器
-
-        Args:
-            config: 转换器配置对象，如果为None则使用默认配置
-        """
-        self.config = config or MarkdownConverterConfig()
-        self._setup_logging()
-        
-        # 检查是否安装了 markitdown
-        self._check_markitdown_installation()
-
-    def _setup_logging(self) -> None:
-        """配置日志记录器"""
-        logging.basicConfig(
-            level=logging.INFO,
-            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-        )
-        self.logger = logging.getLogger(__name__)
-
-        # 添加文件处理器
-        fh = logging.FileHandler('markdown_converter.log')
-        fh.setLevel(logging.ERROR)
-        self.logger.addHandler(fh)
-    
-    def _check_markitdown_installation(self) -> None:
-        """检查是否安装了 markitdown"""
-        try:
-            # 尝试导入 markitdown 库
-            from markitdown import MarkItDown
-            self.logger.info("markitdown 库已安装")
-        except ImportError:
-            self.logger.warning("markitdown 库未安装，尝试安装...")
-            try:
-                subprocess.check_call(["pip", "install", "markitdown"])
-                self.logger.info("markitdown 库安装成功")
-                from markitdown import MarkItDown
-            except (subprocess.SubprocessError, ImportError):
-                self.logger.error("无法安装 markitdown 库，请手动安装")
-                self.markitdown_available = False
-                return
-        
-        self.markitdown_available = True
-
-    def _validate_file(self, file_path: Union[str, Path], max_size_mb: int = 100) -> Path:
-        """验证文件
-
-        Args:
-            file_path: 文件路径
-            max_size_mb: 允许的最大文件大小(MB)
-
-        Returns:
-            Path: 验证后的Path对象
-
-        Raises:
-            ValueError: 文件不存在、格式不支持或大小超限
-            PermissionError: 没有读取权限
-        """
-        path = Path(file_path).resolve()
-
-        if not path.exists():
-            raise ValueError(f"文件不存在: {path}")
-
-        if not path.is_file():
-            raise ValueError(f"不是一个文件: {path}")
-
-        if not os.access(path, os.R_OK):
-            raise PermissionError(f"没有读取权限: {path}")
-
-        file_size_mb = path.stat().st_size / (1024 * 1024)
-        if file_size_mb > max_size_mb:
-            raise ValueError(
-                f"文件大小 ({file_size_mb:.1f}MB) 超过限制 {max_size_mb}MB"
-            )
-
-        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
-            raise ValueError(
-                f"不支持的格式: {path.suffix}. "
-                f"支持的格式: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
-            )
-
-        return path
-
-    def _cleanup_text(self, text: str) -> str:
-        """清理文本
-
-        Args:
-            text: 原始文本
-
-        Returns:
-            str: 清理后的文本
-        """
-        if self.config.text_cleanup['remove_extra_spaces']:
-            text = ' '.join(text.split())
-
-        if self.config.text_cleanup['normalize_whitespace']:
-            text = text.replace('\t', ' ').replace('\r', '\n')
-
-        if self.config.text_cleanup['lowercase']:
-            text = text.lower()
-
-        return text.strip()
-
-    @staticmethod
-    def get_supported_formats() -> List[str]:
-        """获取支持的文件格式列表"""
-        return sorted(MarkdownConverter.SUPPORTED_EXTENSIONS)
-
-    def convert_to_markdown(
-            self,
-            file_path: Union[str, Path],
-            output_path: Optional[Union[str, Path]] = None
-    ) -> str:
-        """将 PDF 转换为 Markdown
-
-        Args:
-            file_path: PDF 文件路径
-            output_path: 输出 Markdown 文件路径，如果为 None 则返回内容而不保存
-
-        Returns:
-            str: 转换后的 Markdown 内容
-
-        Raises:
-            Exception: 转换过程中的错误
-        """
-        try:
-            path = self._validate_file(file_path)
-            self.logger.info(f"处理: {path}")
-
-            if not self.markitdown_available:
-                raise ImportError("markitdown 库未安装，无法进行转换")
-
-            # 导入 markitdown 库
-            from markitdown import MarkItDown
-
-            # 准备输出目录
-            if output_path:
-                output_path = Path(output_path)
-                output_dir = output_path.parent
-                output_dir.mkdir(parents=True, exist_ok=True)
-            else:
-                # 创建临时目录作为输出目录
-                temp_dir = tempfile.mkdtemp()
-                output_dir = Path(temp_dir)
-                output_path = output_dir / f"{path.stem}.md"
-
-            # 图片目录
-            image_dir = output_dir / self.config.image_dir
-            image_dir.mkdir(parents=True, exist_ok=True)
-
-            # 创建 MarkItDown 实例并进行转换
-            if self.config.docintel_endpoint:
-                md = MarkItDown(docintel_endpoint=self.config.docintel_endpoint)
-            elif self.config.llm_client and self.config.llm_model:
-                md = MarkItDown(
-                    enable_plugins=self.config.enable_plugins,
-                    llm_client=self.config.llm_client,
-                    llm_model=self.config.llm_model
-                )
-            else:
-                md = MarkItDown(enable_plugins=self.config.enable_plugins)
-            
-            # 执行转换
-            result = md.convert(str(path))
-            markdown_content = result.text_content
-            
-            # 清理文本
-            markdown_content = self._cleanup_text(markdown_content)
-            
-            # 如果需要保存到文件
-            if output_path:
-                with open(output_path, 'w', encoding='utf-8') as f:
-                    f.write(markdown_content)
-                self.logger.info(f"转换成功，输出到: {output_path}")
-            
-            return markdown_content
-
-        except Exception as e:
-            self.logger.error(f"转换失败: {e}")
-            raise
-        finally:
-            # 如果使用了临时目录且没有指定输出路径，则清理临时目录
-            if 'temp_dir' in locals() and not output_path:
-                shutil.rmtree(temp_dir, ignore_errors=True)
-
-    def convert_to_markdown_and_save(
-            self,
-            file_path: Union[str, Path],
-            output_path: Union[str, Path]
-    ) -> Path:
-        """将 PDF 转换为 Markdown 并保存到指定路径
-
-        Args:
-            file_path: PDF 文件路径
-            output_path: 输出 Markdown 文件路径
-
-        Returns:
-            Path: 输出文件的 Path 对象
-
-        Raises:
-            Exception: 转换过程中的错误
-        """
-        self.convert_to_markdown(file_path, output_path)
-        return Path(output_path)
-    
-    def batch_convert(
-            self, 
-            file_paths: List[Union[str, Path]], 
-            output_dir: Union[str, Path]
-    ) -> List[Path]:
-        """批量转换多个 PDF 文件为 Markdown
-
-        Args:
-            file_paths: PDF 文件路径列表
-            output_dir: 输出目录路径
-
-        Returns:
-            List[Path]: 输出文件路径列表
-
-        Raises:
-            Exception: 转换过程中的错误
-        """
-        output_dir = Path(output_dir)
-        output_dir.mkdir(parents=True, exist_ok=True)
-        
-        output_paths = []
-        for file_path in file_paths:
-            path = Path(file_path)
-            output_path = output_dir / f"{path.stem}.md"
-            
-            try:
-                self.convert_to_markdown(file_path, output_path)
-                output_paths.append(output_path)
-                self.logger.info(f"成功转换: {path} -> {output_path}")
-            except Exception as e:
-                self.logger.error(f"转换失败 {path}: {e}")
-        
-        return output_paths
-
-
-def main():
-    """主函数：演示用法"""
-    # 配置
-    config = MarkdownConverterConfig(
-        extract_images=True,
-        extract_tables=True,
-        extract_code_blocks=True,
-        extract_math=True,
-        enable_plugins=False,
-        text_cleanup={
-            'remove_extra_spaces': True,
-            'normalize_whitespace': True,
-            'remove_special_chars': False,
-            'lowercase': False
-        }
-    )
-
-    # 创建转换器
-    converter = MarkdownConverter(config)
-
-    # 使用示例
-    try:
-        # 替换为实际的文件路径
-        sample_file = './crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf'
-        if Path(sample_file).exists():
-            # 转换为 Markdown 并打印内容
-            markdown_content = converter.convert_to_markdown(sample_file)
-            print("转换后的 Markdown 内容:")
-            print(markdown_content[:500] + "...")  # 只打印前500个字符
-            
-            # 转换并保存到文件
-            output_file = f"./output_{Path(sample_file).stem}.md"
-            output_path = converter.convert_to_markdown_and_save(sample_file, output_file)
-            print(f"\n已保存到: {output_path}")
-            
-            # 使用LLM增强的示例 (需要添加相应的导入和配置)
-            # try:
-            #     from openai import OpenAI
-            #     client = OpenAI()
-            #     llm_config = MarkdownConverterConfig(
-            #         llm_client=client,
-            #         llm_model="gpt-4o"
-            #     )
-            #     llm_converter = MarkdownConverter(llm_config)
-            #     llm_result = llm_converter.convert_to_markdown("example.jpg")
-            #     print("LLM增强的结果:")
-            #     print(llm_result[:500] + "...")
-            # except ImportError:
-            #     print("未安装OpenAI库，跳过LLM示例")
-        else:
-            print(f"示例文件 {sample_file} 不存在")
-
-        print("\n支持的格式:", converter.get_supported_formats())
-
-    except Exception as e:
-        print(f"错误: {e}")
-
-
-if __name__ == "__main__":
-    main() 

crazy_functions/doc_fns/read_fns/unstructured_all/paper_metadata_extractor.py

@@ -1,493 +0,0 @@
-from __future__ import annotations
-
-from pathlib import Path
-from typing import Optional, Set, Dict, Union, List
-from dataclasses import dataclass, field
-import logging
-import os
-import re
-
-from unstructured.partition.auto import partition
-from unstructured.documents.elements import (
-    Text, Title, NarrativeText, ListItem, Table,
-    Footer, Header, PageBreak, Image, Address
-)
-
-
-@dataclass
-class PaperMetadata:
-    """论文元数据类"""
-    title: str = ""
-    authors: List[str] = field(default_factory=list)
-    affiliations: List[str] = field(default_factory=list)
-    journal: str = ""
-    volume: str = ""
-    issue: str = ""
-    year: str = ""
-    doi: str = ""
-    date: str = ""
-    publisher: str = ""
-    conference: str = ""
-    abstract: str = ""
-    keywords: List[str] = field(default_factory=list)
-
-
-@dataclass
-class ExtractorConfig:
-    """元数据提取器配置类"""
-    paragraph_separator: str = '\n\n'
-    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
-        'remove_extra_spaces': True,
-        'normalize_whitespace': True,
-        'remove_special_chars': False,
-        'lowercase': False
-    })
-
-
-class PaperMetadataExtractor:
-    """论文元数据提取器
-    
-    使用unstructured库从多种文档格式中提取论文的标题、作者、摘要等元数据信息。
-    """
-
-    SUPPORTED_EXTENSIONS: Set[str] = {
-        '.pdf', '.docx', '.doc', '.txt', '.ppt', '.pptx',
-        '.xlsx', '.xls', '.md', '.org', '.odt', '.rst',
-        '.rtf', '.epub', '.html', '.xml', '.json'
-    }
-
-    # 定义论文各部分的关键词模式
-    SECTION_PATTERNS = {
-        'abstract': r'\b(摘要|abstract|summary|概要|résumé|zusammenfassung|аннотация)\b',
-        'keywords': r'\b(关键词|keywords|key\s+words|关键字|mots[- ]clés|schlüsselwörter|ключевые слова)\b',
-    }
-
-    def __init__(self, config: Optional[ExtractorConfig] = None):
-        """初始化提取器
-        
-        Args:
-            config: 提取器配置对象，如果为None则使用默认配置
-        """
-        self.config = config or ExtractorConfig()
-        self._setup_logging()
-
-    def _setup_logging(self) -> None:
-        """配置日志记录器"""
-        logging.basicConfig(
-            level=logging.INFO,
-            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-        )
-        self.logger = logging.getLogger(__name__)
-
-        # 添加文件处理器
-        fh = logging.FileHandler('paper_metadata_extractor.log')
-        fh.setLevel(logging.ERROR)
-        self.logger.addHandler(fh)
-
-    def _validate_file(self, file_path: Union[str, Path], max_size_mb: int = 100) -> Path:
-        """验证文件
-        
-        Args:
-            file_path: 文件路径
-            max_size_mb: 允许的最大文件大小(MB)
-            
-        Returns:
-            Path: 验证后的Path对象
-            
-        Raises:
-            ValueError: 文件不存在、格式不支持或大小超限
-            PermissionError: 没有读取权限
-        """
-        path = Path(file_path).resolve()
-
-        if not path.exists():
-            raise ValueError(f"文件不存在: {path}")
-
-        if not path.is_file():
-            raise ValueError(f"不是文件: {path}")
-
-        if not os.access(path, os.R_OK):
-            raise PermissionError(f"没有读取权限: {path}")
-
-        file_size_mb = path.stat().st_size / (1024 * 1024)
-        if file_size_mb > max_size_mb:
-            raise ValueError(
-                f"文件大小 ({file_size_mb:.1f}MB) 超过限制 {max_size_mb}MB"
-            )
-
-        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
-            raise ValueError(
-                f"不支持的文件格式: {path.suffix}. "
-                f"支持的格式: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
-            )
-
-        return path
-
-    def _cleanup_text(self, text: str) -> str:
-        """清理文本
-        
-        Args:
-            text: 原始文本
-            
-        Returns:
-            str: 清理后的文本
-        """
-        if self.config.text_cleanup['remove_extra_spaces']:
-            text = ' '.join(text.split())
-
-        if self.config.text_cleanup['normalize_whitespace']:
-            text = text.replace('\t', ' ').replace('\r', '\n')
-
-        if self.config.text_cleanup['lowercase']:
-            text = text.lower()
-
-        return text.strip()
-
-    @staticmethod
-    def get_supported_formats() -> List[str]:
-        """获取支持的文件格式列表"""
-        return sorted(PaperMetadataExtractor.SUPPORTED_EXTENSIONS)
-
-    def extract_metadata(self, file_path: Union[str, Path], strategy: str = "fast") -> PaperMetadata:
-        """提取论文元数据
-        
-        Args:
-            file_path: 文件路径
-            strategy: 提取策略 ("fast" 或 "accurate")
-            
-        Returns:
-            PaperMetadata: 提取的论文元数据
-            
-        Raises:
-            Exception: 提取过程中的错误
-        """
-        try:
-            path = self._validate_file(file_path)
-            self.logger.info(f"正在处理: {path}")
-
-            # 使用unstructured库分解文档
-            elements = partition(
-                str(path),
-                strategy=strategy,
-                include_metadata=True,
-                nlp=False,
-            )
-
-            # 提取元数据
-            metadata = PaperMetadata()
-            
-            # 提取标题和作者
-            self._extract_title_and_authors(elements, metadata)
-            
-            # 提取摘要和关键词
-            self._extract_abstract_and_keywords(elements, metadata)
-            
-            # 提取其他元数据
-            self._extract_additional_metadata(elements, metadata)
-            
-            return metadata
-
-        except Exception as e:
-            self.logger.error(f"元数据提取失败: {e}")
-            raise
-
-    def _extract_title_and_authors(self, elements, metadata: PaperMetadata) -> None:
-        """从文档中提取标题和作者信息 - 改进版"""
-        # 收集所有潜在的标题候选
-        title_candidates = []
-        all_text = []
-        raw_text = []
-        
-        # 首先收集文档前30个元素的文本，用于辅助判断
-        for i, element in enumerate(elements[:30]):
-            if isinstance(element, (Text, Title, NarrativeText)):
-                text = str(element).strip()
-                if text:
-                    all_text.append(text)
-                    raw_text.append(text)
-        
-        # 打印出原始文本，用于调试
-        print("原始文本前10行:")
-        for i, text in enumerate(raw_text[:10]):
-            print(f"{i}: {text}")
-        
-        # 1. 尝试查找连续的标题片段并合并它们
-        i = 0
-        while i < len(all_text) - 1:
-            current = all_text[i]
-            next_text = all_text[i + 1]
-            
-            # 检查是否存在标题分割情况：一行以冒号结尾，下一行像是标题的延续
-            if current.endswith(':') and len(current) < 50 and len(next_text) > 5 and next_text[0].isupper():
-                # 合并这两行文本
-                combined_title = f"{current} {next_text}"
-                # 查找合并前的文本并替换
-                all_text[i] = combined_title
-                all_text.pop(i + 1)
-                # 给合并后的标题很高的分数
-                title_candidates.append((combined_title, 15, i))
-            else:
-                i += 1
-        
-        # 2. 首先尝试从标题元素中查找
-        for i, element in enumerate(elements[:15]):  # 只检查前15个元素
-            if isinstance(element, Title):
-                title_text = str(element).strip()
-                # 排除常见的非标题内容
-                if title_text.lower() not in ['abstract', '摘要', 'introduction', '引言']:
-                    # 计算标题分数（越高越可能是真正的标题）
-                    score = self._evaluate_title_candidate(title_text, i, element)
-                    title_candidates.append((title_text, score, i))
-        
-        # 3. 特别处理常见的论文标题格式
-        for i, text in enumerate(all_text[:15]):
-            # 特别检查"KIMI K1.5:"类型的前缀标题
-            if re.match(r'^[A-Z][A-Z0-9\s\.]+(\s+K\d+(\.\d+)?)?:', text):
-                score = 12  # 给予很高的分数
-                title_candidates.append((text, score, i))
-                
-                # 如果下一行也是全大写，很可能是标题的延续
-                if i+1 < len(all_text) and all_text[i+1].isupper() and len(all_text[i+1]) > 10:
-                    combined_title = f"{text} {all_text[i+1]}"
-                    title_candidates.append((combined_title, 15, i))  # 给合并标题更高分数
-            
-            # 匹配全大写的标题行
-            elif text.isupper() and len(text) > 10 and len(text) < 100:
-                score = 10 - i * 0.5  # 越靠前越可能是标题
-                title_candidates.append((text, score, i))
-        
-        # 对标题候选按分数排序并选取最佳候选
-        if title_candidates:
-            title_candidates.sort(key=lambda x: x[1], reverse=True)
-            metadata.title = title_candidates[0][0]
-            title_position = title_candidates[0][2]
-            print(f"所有标题候选: {title_candidates[:3]}")
-        else:
-            # 如果没有找到合适的标题，使用一个备选策略
-            for text in all_text[:10]:
-                if text.isupper() and len(text) > 10 and len(text) < 200:  # 大写且适当长度的文本
-                    metadata.title = text
-                    break
-            title_position = 0
-        
-        # 提取作者信息 - 改进后的作者提取逻辑
-        author_candidates = []
-        
-        # 1. 特别处理"TECHNICAL REPORT OF"之后的行，通常是作者或团队
-        for i, text in enumerate(all_text):
-            if "TECHNICAL REPORT" in text.upper() and i+1 < len(all_text):
-                team_text = all_text[i+1].strip()
-                if re.search(r'\b(team|group|lab)\b', team_text, re.IGNORECASE):
-                    author_candidates.append((team_text, 15))
-        
-        # 2. 查找包含Team的文本
-        for text in all_text[:20]:
-            if "Team" in text and len(text) < 30:
-                # 这很可能是团队名
-                author_candidates.append((text, 12))
-        
-        # 添加作者到元数据
-        if author_candidates:
-            # 按分数排序
-            author_candidates.sort(key=lambda x: x[1], reverse=True)
-            
-            # 去重
-            seen_authors = set()
-            for author, _ in author_candidates:
-                if author.lower() not in seen_authors and not author.isdigit():
-                    seen_authors.add(author.lower())
-                    metadata.authors.append(author)
-        
-        # 如果没有找到作者，尝试查找隶属机构信息中的团队名称
-        if not metadata.authors:
-            for text in all_text[:20]:
-                if re.search(r'\b(team|group|lab|laboratory|研究组|团队)\b', text, re.IGNORECASE):
-                    if len(text) < 50:  # 避免太长的文本
-                        metadata.authors.append(text.strip())
-                        break
-        
-        # 提取隶属机构信息
-        for i, element in enumerate(elements[:30]):
-            element_text = str(element).strip()
-            if re.search(r'(university|institute|department|school|laboratory|college|center|centre|\d{5,}|^[a-zA-Z]+@|学院|大学|研究所|研究院)', element_text, re.IGNORECASE):
-                # 可能是隶属机构
-                if element_text not in metadata.affiliations and len(element_text) > 10:
-                    metadata.affiliations.append(element_text)
-
-    def _evaluate_title_candidate(self, text, position, element):
-        """评估标题候选项的可能性分数"""
-        score = 0
-        
-        # 位置因素：越靠前越可能是标题
-        score += max(0, 10 - position) * 0.5
-        
-        # 长度因素：标题通常不会太短也不会太长
-        if 10 <= len(text) <= 150:
-            score += 3
-        elif len(text) < 10:
-            score -= 2
-        elif len(text) > 150:
-            score -= 3
-        
-        # 格式因素
-        if text.isupper():  # 全大写可能是标题
-            score += 2
-        if re.match(r'^[A-Z]', text):  # 首字母大写
-            score += 1
-        if ':' in text:  # 标题常包含冒号
-            score += 1.5
-        
-        # 内容因素
-        if re.search(r'\b(scaling|learning|model|approach|method|system|framework|analysis)\b', text.lower()):
-            score += 2  # 包含常见的学术论文关键词
-            
-        # 避免误判
-        if re.match(r'^\d+$', text):  # 纯数字
-            score -= 10
-        if re.search(r'^(http|www|doi)', text.lower()):  # URL或DOI
-            score -= 5
-        if len(text.split()) <= 2 and len(text) < 15:  # 太短的短语
-            score -= 3
-            
-        # 元数据因素(如果有)
-        if hasattr(element, 'metadata') and element.metadata:
-            # 修复：正确处理ElementMetadata对象
-            try:
-                # 尝试通过getattr安全地获取属性
-                font_size = getattr(element.metadata, 'font_size', None)
-                if font_size is not None and font_size > 14:  # 假设标准字体大小是12
-                    score += 3
-                    
-                font_weight = getattr(element.metadata, 'font_weight', None)
-                if font_weight == 'bold':
-                    score += 2  # 粗体加分
-            except (AttributeError, TypeError):
-                # 如果metadata的访问方式不正确，尝试其他可能的访问方式
-                try:
-                    metadata_dict = element.metadata.__dict__ if hasattr(element.metadata, '__dict__') else {}
-                    if 'font_size' in metadata_dict and metadata_dict['font_size'] > 14:
-                        score += 3
-                    if 'font_weight' in metadata_dict and metadata_dict['font_weight'] == 'bold':
-                        score += 2
-                except Exception:
-                    # 如果所有尝试都失败，忽略元数据处理
-                    pass
-        
-        return score
-
-    def _extract_abstract_and_keywords(self, elements, metadata: PaperMetadata) -> None:
-        """从文档中提取摘要和关键词"""
-        abstract_found = False
-        keywords_found = False
-        abstract_text = []
-        
-        for i, element in enumerate(elements):
-            element_text = str(element).strip().lower()
-            
-            # 寻找摘要部分
-            if not abstract_found and (
-                isinstance(element, Title) and 
-                re.search(self.SECTION_PATTERNS['abstract'], element_text, re.IGNORECASE)
-            ):
-                abstract_found = True
-                continue
-            
-            # 如果找到摘要部分，收集内容直到遇到关键词部分或新章节
-            if abstract_found and not keywords_found:
-                # 检查是否遇到关键词部分或新章节
-                if (
-                    isinstance(element, Title) or 
-                    re.search(self.SECTION_PATTERNS['keywords'], element_text, re.IGNORECASE) or
-                    re.match(r'\b(introduction|引言|method|方法)\b', element_text, re.IGNORECASE)
-                ):
-                    keywords_found = re.search(self.SECTION_PATTERNS['keywords'], element_text, re.IGNORECASE)
-                    abstract_found = False  # 停止收集摘要
-                else:
-                    # 收集摘要文本
-                    if isinstance(element, (Text, NarrativeText)) and element_text:
-                        abstract_text.append(element_text)
-            
-            # 如果找到关键词部分，提取关键词
-            if keywords_found and not abstract_found and not metadata.keywords:
-                if isinstance(element, (Text, NarrativeText)):
-                    # 清除可能的"关键词:"/"Keywords:"前缀
-                    cleaned_text = re.sub(r'^\s*(关键词|keywords|key\s+words)\s*[：:]\s*', '', element_text, flags=re.IGNORECASE)
-                    
-                    # 尝试按不同分隔符分割
-                    for separator in [';', '；', ',', '，']:
-                        if separator in cleaned_text:
-                            metadata.keywords = [k.strip() for k in cleaned_text.split(separator) if k.strip()]
-                            break
-                    
-                    # 如果未能分割，将整个文本作为一个关键词
-                    if not metadata.keywords and cleaned_text:
-                        metadata.keywords = [cleaned_text]
-                    
-                    keywords_found = False  # 已提取关键词，停止处理
-        
-        # 设置摘要文本
-        if abstract_text:
-            metadata.abstract = self.config.paragraph_separator.join(abstract_text)
-
-    def _extract_additional_metadata(self, elements, metadata: PaperMetadata) -> None:
-        """提取其他元数据信息"""
-        for element in elements[:30]:  # 只检查文档前部分
-            element_text = str(element).strip()
-            
-            # 尝试匹配DOI
-            doi_match = re.search(r'(doi|DOI):\s*(10\.\d{4,}\/[a-zA-Z0-9.-]+)', element_text)
-            if doi_match and not metadata.doi:
-                metadata.doi = doi_match.group(2)
-            
-            # 尝试匹配日期
-            date_match = re.search(r'(published|received|accepted|submitted):\s*(\d{1,2}\s+[a-zA-Z]+\s+\d{4}|\d{4}[-/]\d{1,2}[-/]\d{1,2})', element_text, re.IGNORECASE)
-            if date_match and not metadata.date:
-                metadata.date = date_match.group(2)
-                
-            # 尝试匹配年份
-            year_match = re.search(r'\b(19|20)\d{2}\b', element_text)
-            if year_match and not metadata.year:
-                metadata.year = year_match.group(0)
-                
-            # 尝试匹配期刊/会议名称
-            journal_match = re.search(r'(journal|conference):\s*([^,;.]+)', element_text, re.IGNORECASE)
-            if journal_match:
-                if "journal" in journal_match.group(1).lower() and not metadata.journal:
-                    metadata.journal = journal_match.group(2).strip()
-                elif not metadata.conference:
-                    metadata.conference = journal_match.group(2).strip()
-
-
-def main():
-    """主函数：演示用法"""
-    # 创建提取器
-    extractor = PaperMetadataExtractor()
-
-    # 使用示例
-    try:
-        # 替换为实际的文件路径
-        sample_file = '/Users/boyin.liu/Documents/示例文档/论文/3.pdf'
-        if Path(sample_file).exists():
-            metadata = extractor.extract_metadata(sample_file)
-            print("提取的元数据:")
-            print(f"标题: {metadata.title}")
-            print(f"作者: {', '.join(metadata.authors)}")
-            print(f"机构: {', '.join(metadata.affiliations)}")
-            print(f"摘要: {metadata.abstract[:200]}...")
-            print(f"关键词: {', '.join(metadata.keywords)}")
-            print(f"DOI: {metadata.doi}")
-            print(f"日期: {metadata.date}")
-            print(f"年份: {metadata.year}")
-            print(f"期刊: {metadata.journal}")
-            print(f"会议: {metadata.conference}")
-        else:
-            print(f"示例文件 {sample_file} 不存在")
-
-        print("\n支持的格式:", extractor.get_supported_formats())
-
-    except Exception as e:
-        print(f"错误: {e}")
-
-
-if __name__ == "__main__":
-    main() 

crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_md.py

@@ -1,86 +0,0 @@
-from pathlib import Path
-from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import PaperStructureExtractor
-
-def extract_and_save_as_markdown(paper_path, output_path=None):
-    """
-    提取论文结构并保存为Markdown格式
-    
-    参数:
-        paper_path: 论文文件路径
-        output_path: 输出的Markdown文件路径，如果不指定，将使用与输入相同的文件名但扩展名为.md
-    
-    返回:
-        保存的Markdown文件路径
-    """
-    # 创建提取器
-    extractor = PaperStructureExtractor()
-    
-    # 解析文件路径
-    paper_path = Path(paper_path)
-    
-    # 如果未指定输出路径，使用相同文件名但扩展名为.md
-    if output_path is None:
-        output_path = paper_path.with_suffix('.md')
-    else:
-        output_path = Path(output_path)
-    
-    # 确保输出目录存在
-    output_path.parent.mkdir(parents=True, exist_ok=True)
-    
-    print(f"正在处理论文: {paper_path}")
-    
-    try:
-        # 提取论文结构
-        paper = extractor.extract_paper_structure(paper_path)
-        
-        # 生成Markdown内容
-        markdown_content = extractor.generate_markdown(paper)
-        
-        # 保存到文件
-        with open(output_path, 'w', encoding='utf-8') as f:
-            f.write(markdown_content)
-        
-        print(f"已成功保存Markdown文件: {output_path}")
-        
-        # 打印摘要信息
-        print("\n论文摘要信息:")
-        print(f"标题: {paper.metadata.title}")
-        print(f"作者: {', '.join(paper.metadata.authors)}")
-        print(f"关键词: {', '.join(paper.keywords)}")
-        print(f"章节数: {len(paper.sections)}")
-        print(f"图表数: {len(paper.figures)}")
-        print(f"表格数: {len(paper.tables)}")
-        print(f"公式数: {len(paper.formulas)}")
-        print(f"参考文献数: {len(paper.references)}")
-        
-        return output_path
-    
-    except Exception as e:
-        print(f"处理论文时出错: {e}")
-        import traceback
-        traceback.print_exc()
-        return None
-
-# 使用示例
-if __name__ == "__main__":
-    # 替换为实际的论文文件路径
-    sample_paper = "crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf"
-    
-    # 可以指定输出路径，也可以使用默认路径
-    # output_file = "/path/to/output/paper_structure.md"
-    # extract_and_save_as_markdown(sample_paper, output_file)
-    
-    # 使用默认输出路径（与输入文件同名但扩展名为.md）
-    extract_and_save_as_markdown(sample_paper)
-    
-    # # 批量处理多个论文的示例
-    # paper_dir = Path("/path/to/papers/folder")
-    # output_dir = Path("/path/to/output/folder")
-    #
-    # # 确保输出目录存在
-    # output_dir.mkdir(parents=True, exist_ok=True)
-    #
-    # # 处理目录中的所有PDF文件
-    # for paper_file in paper_dir.glob("*.pdf"):
-    #     output_file = output_dir / f"{paper_file.stem}.md"
-    #     extract_and_save_as_markdown(paper_file, output_file)

crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_reader.py

@@ -1,275 +0,0 @@
-from __future__ import annotations
-
-from pathlib import Path
-from typing import Optional, Set, Dict, Union, List
-from dataclasses import dataclass, field
-import logging
-import os
-
-from unstructured.partition.auto import partition
-from unstructured.documents.elements import (
-    Text, Title, NarrativeText, ListItem, Table,
-    Footer, Header, PageBreak, Image, Address
-)
-
-
-@dataclass
-class TextExtractorConfig:
-    """通用文档提取器配置类
-
-    Attributes:
-        extract_headers_footers: 是否提取页眉页脚
-        extract_tables: 是否提取表格内容
-        extract_lists: 是否提取列表内容
-        extract_titles: 是否提取标题
-        paragraph_separator: 段落之间的分隔符
-        text_cleanup: 文本清理选项字典
-    """
-    extract_headers_footers: bool = False
-    extract_tables: bool = True
-    extract_lists: bool = True
-    extract_titles: bool = True
-    paragraph_separator: str = '\n\n'
-    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
-        'remove_extra_spaces': True,
-        'normalize_whitespace': True,
-        'remove_special_chars': False,
-        'lowercase': False
-    })
-
-
-class UnstructuredTextExtractor:
-    """通用文档文本内容提取器
-
-    使用 unstructured 库支持多种文档格式的文本提取，提供统一的接口和配置选项。
-    """
-
-    SUPPORTED_EXTENSIONS: Set[str] = {
-        # 文档格式
-        '.pdf', '.docx', '.doc', '.txt',
-        # 演示文稿
-        '.ppt', '.pptx',
-        # 电子表格
-        '.xlsx', '.xls', '.csv',
-        # 图片
-        '.png', '.jpg', '.jpeg', '.tiff',
-        # 邮件
-        '.eml', '.msg', '.p7s',
-        # Markdown
-        ".md",
-        # Org Mode
-        ".org",
-        # Open Office
-        ".odt",
-        # reStructured Text
-        ".rst",
-        # Rich Text
-        ".rtf",
-        # TSV
-        ".tsv",
-        # EPUB
-        '.epub',
-        # 其他格式
-        '.html', '.xml',  '.json',
-    }
-
-    def __init__(self, config: Optional[TextExtractorConfig] = None):
-        """初始化提取器
-
-        Args:
-            config: 提取器配置对象，如果为None则使用默认配置
-        """
-        self.config = config or TextExtractorConfig()
-        self._setup_logging()
-
-    def _setup_logging(self) -> None:
-        """配置日志记录器"""
-        logging.basicConfig(
-            level=logging.INFO,
-            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-        )
-        self.logger = logging.getLogger(__name__)
-
-        # 添加文件处理器
-        fh = logging.FileHandler('text_extractor.log')
-        fh.setLevel(logging.ERROR)
-        self.logger.addHandler(fh)
-
-    def _validate_file(self, file_path: Union[str, Path], max_size_mb: int = 100) -> Path:
-        """验证文件
-
-        Args:
-            file_path: 文件路径
-            max_size_mb: 允许的最大文件大小(MB)
-
-        Returns:
-            Path: 验证后的Path对象
-
-        Raises:
-            ValueError: 文件不存在、格式不支持或大小超限
-            PermissionError: 没有读取权限
-        """
-        path = Path(file_path).resolve()
-
-        if not path.exists():
-            raise ValueError(f"File not found: {path}")
-
-        if not path.is_file():
-            raise ValueError(f"Not a file: {path}")
-
-        if not os.access(path, os.R_OK):
-            raise PermissionError(f"No read permission: {path}")
-
-        file_size_mb = path.stat().st_size / (1024 * 1024)
-        if file_size_mb > max_size_mb:
-            raise ValueError(
-                f"File size ({file_size_mb:.1f}MB) exceeds limit of {max_size_mb}MB"
-            )
-
-        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
-            raise ValueError(
-                f"Unsupported format: {path.suffix}. "
-                f"Supported: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
-            )
-
-        return path
-
-    def _cleanup_text(self, text: str) -> str:
-        """清理文本
-
-        Args:
-            text: 原始文本
-
-        Returns:
-            str: 清理后的文本
-        """
-        if self.config.text_cleanup['remove_extra_spaces']:
-            text = ' '.join(text.split())
-
-        if self.config.text_cleanup['normalize_whitespace']:
-            text = text.replace('\t', ' ').replace('\r', '\n')
-
-        if self.config.text_cleanup['lowercase']:
-            text = text.lower()
-
-        return text.strip()
-
-    def _should_extract_element(self, element) -> bool:
-        """判断是否应该提取某个元素
-
-        Args:
-            element: 文档元素
-
-        Returns:
-            bool: 是否应该提取
-        """
-        if isinstance(element, (Text, NarrativeText)):
-            return True
-
-        if isinstance(element, Title) and self.config.extract_titles:
-            return True
-
-        if isinstance(element, ListItem) and self.config.extract_lists:
-            return True
-
-        if isinstance(element, Table) and self.config.extract_tables:
-            return True
-
-        if isinstance(element, (Header, Footer)) and self.config.extract_headers_footers:
-            return True
-
-        return False
-
-    @staticmethod
-    def get_supported_formats() -> List[str]:
-        """获取支持的文件格式列表"""
-        return sorted(UnstructuredTextExtractor.SUPPORTED_EXTENSIONS)
-
-    def extract_text(
-            self,
-            file_path: Union[str, Path],
-            strategy: str = "fast"
-    ) -> str:
-        """提取文本
-
-        Args:
-            file_path: 文件路径
-            strategy: 提取策略 ("fast" 或 "accurate")
-
-        Returns:
-            str: 提取的文本内容
-
-        Raises:
-            Exception: 提取过程中的错误
-        """
-        try:
-            path = self._validate_file(file_path)
-            self.logger.info(f"Processing: {path}")
-
-            # 修改这里：添加 nlp=False 参数来禁用 NLTK
-            elements = partition(
-                str(path),
-                strategy=strategy,
-                include_metadata=True,
-                nlp=True,
-            )
-
-            # 其余代码保持不变
-            text_parts = []
-            for element in elements:
-                if self._should_extract_element(element):
-                    text = str(element)
-                    cleaned_text = self._cleanup_text(text)
-                    if cleaned_text:
-                        if isinstance(element, (Header, Footer)):
-                            prefix = "[Header] " if isinstance(element, Header) else "[Footer] "
-                            text_parts.append(f"{prefix}{cleaned_text}")
-                        else:
-                            text_parts.append(cleaned_text)
-
-            return self.config.paragraph_separator.join(text_parts)
-
-        except Exception as e:
-            self.logger.error(f"Extraction failed: {e}")
-            raise
-
-
-
-def main():
-    """主函数：演示用法"""
-    # 配置
-    config = TextExtractorConfig(
-        extract_headers_footers=True,
-        extract_tables=True,
-        extract_lists=True,
-        extract_titles=True,
-        text_cleanup={
-            'remove_extra_spaces': True,
-            'normalize_whitespace': True,
-            'remove_special_chars': False,
-            'lowercase': False
-        }
-    )
-
-    # 创建提取器
-    extractor = UnstructuredTextExtractor(config)
-
-    # 使用示例
-    try:
-        # 替换为实际的文件路径
-        sample_file = './crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf'
-        if Path(sample_file).exists() or True:
-            text = extractor.extract_text(sample_file)
-            print("提取的文本:")
-            print(text)
-        else:
-            print(f"示例文件 {sample_file} 不存在")
-
-        print("\n支持的格式:", extractor.get_supported_formats())
-
-    except Exception as e:
-        print(f"错误: {e}")
-
-
-if __name__ == "__main__":
-    main()

crazy_functions/doc_fns/read_fns/web_reader.py

@@ -1,219 +0,0 @@
-from __future__ import annotations
-
-from dataclasses import dataclass, field
-from typing import Dict, Optional, Union
-from urllib.parse import urlparse
-import logging
-import trafilatura
-import requests
-from pathlib import Path
-
-
-@dataclass
-class WebExtractorConfig:
-    """网页内容提取器配置类
-
-    Attributes:
-        extract_comments: 是否提取评论
-        extract_tables: 是否提取表格
-        extract_links: 是否保留链接信息
-        paragraph_separator: 段落分隔符
-        timeout: 网络请求超时时间(秒)
-        max_retries: 最大重试次数
-        user_agent: 自定义User-Agent
-        text_cleanup: 文本清理选项
-    """
-    extract_comments: bool = False
-    extract_tables: bool = True
-    extract_links: bool = False
-    paragraph_separator: str = '\n\n'
-    timeout: int = 10
-    max_retries: int = 3
-    user_agent: str = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
-    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
-        'remove_extra_spaces': True,
-        'normalize_whitespace': True,
-        'remove_special_chars': False,
-        'lowercase': False
-    })
-
-
-class WebTextExtractor:
-    """网页文本内容提取器
-    
-    使用trafilatura库提取网页中的主要文本内容，去除广告、导航等无关内容。
-    """
-
-    def __init__(self, config: Optional[WebExtractorConfig] = None):
-        """初始化提取器
-
-        Args:
-            config: 提取器配置对象，如果为None则使用默认配置
-        """
-        self.config = config or WebExtractorConfig()
-        self._setup_logging()
-
-    def _setup_logging(self) -> None:
-        """配置日志记录器"""
-        logging.basicConfig(
-            level=logging.INFO,
-            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-        )
-        self.logger = logging.getLogger(__name__)
-
-        # 添加文件处理器
-        fh = logging.FileHandler('web_extractor.log')
-        fh.setLevel(logging.ERROR)
-        self.logger.addHandler(fh)
-
-    def _validate_url(self, url: str) -> bool:
-        """验证URL格式是否有效
-
-        Args:
-            url: 网页URL
-
-        Returns:
-            bool: URL是否有效
-        """
-        try:
-            result = urlparse(url)
-            return all([result.scheme, result.netloc])
-        except Exception:
-            return False
-
-    def _download_webpage(self, url: str) -> Optional[str]:
-        """下载网页内容
-
-        Args:
-            url: 网页URL
-
-        Returns:
-            Optional[str]: 网页HTML内容，失败返回None
-
-        Raises:
-            Exception: 下载失败时抛出异常
-        """
-        headers = {'User-Agent': self.config.user_agent}
-        
-        for attempt in range(self.config.max_retries):
-            try:
-                response = requests.get(
-                    url, 
-                    headers=headers,
-                    timeout=self.config.timeout
-                )
-                response.raise_for_status()
-                return response.text
-            except requests.RequestException as e:
-                self.logger.warning(f"Attempt {attempt + 1} failed: {e}")
-                if attempt == self.config.max_retries - 1:
-                    raise Exception(f"Failed to download webpage after {self.config.max_retries} attempts: {e}")
-        return None
-
-    def _cleanup_text(self, text: str) -> str:
-        """清理文本
-
-        Args:
-            text: 原始文本
-
-        Returns:
-            str: 清理后的文本
-        """
-        if not text:
-            return ""
-
-        if self.config.text_cleanup['remove_extra_spaces']:
-            text = ' '.join(text.split())
-
-        if self.config.text_cleanup['normalize_whitespace']:
-            text = text.replace('\t', ' ').replace('\r', '\n')
-
-        if self.config.text_cleanup['lowercase']:
-            text = text.lower()
-
-        return text.strip()
-
-    def extract_text(self, url: str) -> str:
-        """提取网页文本内容
-
-        Args:
-            url: 网页URL
-
-        Returns:
-            str: 提取的文本内容
-
-        Raises:
-            ValueError: URL无效时抛出
-            Exception: 提取失败时抛出
-        """
-        try:
-            if not self._validate_url(url):
-                raise ValueError(f"Invalid URL: {url}")
-
-            self.logger.info(f"Processing URL: {url}")
-            
-            # 下载网页
-            html_content = self._download_webpage(url)
-            if not html_content:
-                raise Exception("Failed to download webpage")
-
-            # 配置trafilatura提取选项
-            extract_config = {
-                'include_comments': self.config.extract_comments,
-                'include_tables': self.config.extract_tables,
-                'include_links': self.config.extract_links,
-                'no_fallback': False,  # 允许使用后备提取器
-            }
-
-            # 提取文本
-            extracted_text = trafilatura.extract(
-                html_content,
-                **extract_config
-            )
-
-            if not extracted_text:
-                raise Exception("No content could be extracted")
-
-            # 清理文本
-            cleaned_text = self._cleanup_text(extracted_text)
-            
-            return cleaned_text
-
-        except Exception as e:
-            self.logger.error(f"Extraction failed: {e}")
-            raise
-
-
-def main():
-    """主函数：演示用法"""
-    # 配置
-    config = WebExtractorConfig(
-        extract_comments=False,
-        extract_tables=True,
-        extract_links=False,
-        timeout=10,
-        text_cleanup={
-            'remove_extra_spaces': True,
-            'normalize_whitespace': True,
-            'remove_special_chars': False,
-            'lowercase': False
-        }
-    )
-
-    # 创建提取器
-    extractor = WebTextExtractor(config)
-
-    # 使用示例
-    try:
-        # 替换为实际的URL
-        sample_url = 'https://arxiv.org/abs/2412.00036'
-        text = extractor.extract_text(sample_url)
-        print("提取的文本:")
-        print(text)
-
-    except Exception as e:
-        print(f"错误: {e}")
-
-
-if __name__ == "__main__":
-    main()

crazy_functions/game_fns/game_ascii_art.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, update_ui_latest_msg
+from toolbox import CatchException, update_ui, update_ui_lastest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -13,7 +13,7 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
         else:
             if prompt.strip() == 'exit':
                 self.delete_game = True
-                yield from update_ui_latest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_lastest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
                 return
             chatbot.append([prompt, ""])
         yield from update_ui(chatbot=chatbot, history=history)
@@ -31,12 +31,12 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
             self.cur_task = 'identify user guess'
             res = get_code_block(raw_res)
             history += ['', f'the answer is {self.obj}', inputs, res]
-            yield from update_ui_latest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
 
         elif self.cur_task == 'identify user guess':
             if is_same_thing(self.obj, prompt, self.llm_kwargs):
                 self.delete_game = True
-                yield from update_ui_latest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_lastest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
             else:
                 self.cur_task = 'identify user guess'
-                yield from update_ui_latest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_lastest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)

crazy_functions/game_fns/game_interactive_story.py

@@ -63,7 +63,7 @@ prompts_terminate = """小说的前文回顾：
 """
 
 
-from toolbox import CatchException, update_ui, update_ui_latest_msg
+from toolbox import CatchException, update_ui, update_ui_lastest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -112,7 +112,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
             if prompt.strip() == 'exit' or prompt.strip() == '结束剧情':
                 # should we terminate game here?
                 self.delete_game = True
-                yield from update_ui_latest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_lastest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
                 return
             if '剧情收尾' in prompt:
                 self.cur_task = 'story_terminate'
@@ -137,8 +137,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
             )
             self.story.append(story_paragraph)
             # # 配图
-            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
 
             # # 构建后续剧情引导
             previously_on_story = ""
@@ -171,8 +171,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
             )
             self.story.append(story_paragraph)
             # # 配图
-            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
 
             # # 构建后续剧情引导
             previously_on_story = ""
@@ -204,8 +204,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
                 chatbot, history_, self.sys_prompt_
             )
             # # 配图
-            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
 
             # terminate game
             self.delete_game = True

crazy_functions/gen_fns/gen_fns_shared.py

@@ -2,7 +2,7 @@ import time
 import importlib
 from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
-from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
+from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
 import multiprocessing
 
 def get_class_name(class_string):

crazy_functions/json_fns/pydantic_io.py

@@ -102,10 +102,10 @@ class GptJsonIO():
                 logging.info(f'Repairing json：{response}')
                 repair_prompt = self.generate_repair_prompt(broken_json = response, error=repr(e))
                 result = self.generate_output(gpt_gen_fn(repair_prompt, self.format_instructions))
-                logging.info('Repair json success.')
+                logging.info('Repaire json success.')
             except Exception as e:
                 # 没辙了，放弃治疗
-                logging.info('Repair json fail.')
+                logging.info('Repaire json fail.')
                 raise JsonStringError('Cannot repair json.', str(e))
         return result
 

crazy_functions/latex_fns/latex_actions.py

@@ -3,7 +3,7 @@ import re
 import shutil
 import numpy as np
 from loguru import logger
-from toolbox import update_ui, update_ui_latest_msg, get_log_folder, gen_time_str
+from toolbox import update_ui, update_ui_lastest_msg, get_log_folder, gen_time_str
 from toolbox import get_conf, promote_file_to_downloadzone
 from crazy_functions.latex_fns.latex_toolbox import PRESERVE, TRANSFORM
 from crazy_functions.latex_fns.latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
@@ -20,7 +20,7 @@ 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
-    be processed by GPT.
+    be proccessed by GPT.
     """
     text = txt
     mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
@@ -85,14 +85,14 @@ class LatexPaperSplit():
     """
     break down latex file to a linked list,
     each node use a preserve flag to indicate whether it should
-    be processed by GPT.
+    be proccessed by GPT.
     """
     def __init__(self) -> None:
         self.nodes = None
         self.msg = "*{\\scriptsize\\textbf{警告：该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成，" + \
             "版权归原文作者所有。翻译内容可靠性无保障，请仔细鉴别并以原文为准。" + \
             "项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
-        # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加README中的QQ联系开发者）
+        # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加REAME中的QQ联系开发者）
         self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\"
         self.title = "unknown"
         self.abstract = "unknown"
@@ -151,7 +151,7 @@ class LatexPaperSplit():
         """
         break down latex file to a linked list,
         each node use a preserve flag to indicate whether it should
-        be processed by GPT.
+        be proccessed by GPT.
         P.S. use multiprocessing to avoid timeout error
         """
         import multiprocessing
@@ -300,8 +300,7 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
     write_html(pfg.sp_file_contents, pfg.sp_file_result, chatbot=chatbot, project_folder=project_folder)
 
     #  <-------- 写出文件 ---------->
-    model_name = llm_kwargs['llm_model'].replace('_', '\\_')  # 替换LLM模型名称中的下划线为转义字符
+    msg = f"当前大语言模型: {llm_kwargs['llm_model']}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
-    msg = f"当前大语言模型: {model_name}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
     final_tex = lps.merge_result(pfg.file_result, mode, msg)
     objdump((lps, pfg.file_result, mode, msg), file=pj(project_folder,'merge_result.pkl'))
 
@@ -351,42 +350,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
     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，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_latest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
+    yield from update_ui_lastest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
-    # 检查是否需要使用xelatex
-    def check_if_need_xelatex(tex_path):
-        try:
-            with open(tex_path, 'r', encoding='utf-8', errors='replace') as f:
-                content = f.read(5000)
-                # 检查是否有使用xelatex的宏包
-                need_xelatex = any(
-                    pkg in content 
-                    for pkg in ['fontspec', 'xeCJK', 'xetex', 'unicode-math', 'xltxtra', 'xunicode']
-                )
-                if need_xelatex:
-                    logger.info(f"检测到宏包需要xelatex编译, 切换至xelatex编译")
-                else:
-                    logger.info(f"未检测到宏包需要xelatex编译, 使用pdflatex编译")
-                return need_xelatex
-        except Exception:
-            return False
-
-    # 根据编译器类型返回编译命令
-    def get_compile_command(compiler, filename):
-        compile_command = f'{compiler} -interaction=batchmode -file-line-error {filename}.tex'
-        logger.info('Latex 编译指令: ' + compile_command)
-        return compile_command
-
-    # 确定使用的编译器
-    compiler = 'pdflatex'
-    if check_if_need_xelatex(pj(work_folder_modified, f'{main_file_modified}.tex')):
-        logger.info("检测到宏包需要xelatex编译，切换至xelatex编译")
-        # Check if xelatex is installed
-        try:
-            import subprocess
-            subprocess.run(['xelatex', '--version'], capture_output=True, check=True)
-            compiler = 'xelatex'
-        except (subprocess.CalledProcessError, FileNotFoundError):
-            raise RuntimeError("检测到需要使用xelatex编译，但系统中未安装xelatex。请先安装texlive或其他提供xelatex的LaTeX发行版。")
 
     while True:
         import os
@@ -396,36 +360,36 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
             shutil.copyfile(may_exist_bbl, target_bbl)
 
         # https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
-        yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
+        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
-        ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
+        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
 
-        yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
+        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
-        ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
+        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
 
         if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
             # 只有第二步成功，才能继续下面的步骤
-            yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
             if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
                 ok = compile_latex_with_timeout(f'bibtex  {main_file_original}.aux', work_folder_original)
             if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
                 ok = compile_latex_with_timeout(f'bibtex  {main_file_modified}.aux', work_folder_modified)
 
-            yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
+            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
-            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
+            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
-            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
+            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
-            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
+            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
-            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
+            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
 
             if mode!='translate_zh':
-                yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
+                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
                 logger.info(    f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
                 ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())
 
-                yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
+                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
-                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
+                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
                 ok = compile_latex_with_timeout(f'bibtex    merge_diff.aux', work_folder)
-                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
+                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
-                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
+                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
 
         # <---------- 检查结果 ----------->
         results_ = ""
@@ -435,13 +399,13 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
         results_ += f"原始PDF编译是否成功: {original_pdf_success};"
         results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
         results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
-        yield from update_ui_latest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
+        yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
 
         if diff_pdf_success:
             result_pdf = pj(work_folder_modified, f'merge_diff.pdf')    # get pdf path
             promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot)  # promote file to web UI
         if modified_pdf_success:
-            yield from update_ui_latest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
             result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf') # get pdf path
             origin_pdf = pj(work_folder_original, f'{main_file_original}.pdf') # get pdf path
             if os.path.exists(pj(work_folder, '..', 'translation')):
@@ -472,7 +436,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 work_folder_modified=work_folder_modified,
                 fixed_line=fixed_line
             )
-            yield from update_ui_latest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history)   # 刷新Gradio前端界面
+            yield from update_ui_lastest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history)   # 刷新Gradio前端界面
             if not can_retry: break
 
     return False # 失败啦

crazy_functions/latex_fns/latex_pickle_io.py

@@ -6,16 +6,12 @@ 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
 
@@ -26,6 +22,8 @@ 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

crazy_functions/latex_fns/latex_toolbox.py

@@ -168,7 +168,7 @@ def set_forbidden_text(text, mask, pattern, flags=0):
 def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
     """
     Move area out of preserve area (make text editable for GPT)
-    count the number of the braces so as to catch complete text area.
+    count the number of the braces so as to catch compelete text area.
     e.g.
     \begin{abstract} blablablablablabla. \end{abstract}
     """
@@ -188,7 +188,7 @@ def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
 def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
     """
     Add a preserve text area in this paper (text become untouchable for GPT).
-    count the number of the braces so as to catch complete text area.
+    count the number of the braces so as to catch compelete text area.
     e.g.
     \caption{blablablablabla\texbf{blablabla}blablabla.}
     """
@@ -214,7 +214,7 @@ def reverse_forbidden_text_careful_brace(
 ):
     """
     Move area out of preserve area (make text editable for GPT)
-    count the number of the braces so as to catch complete text area.
+    count the number of the braces so as to catch compelete text area.
     e.g.
     \caption{blablablablabla\texbf{blablabla}blablabla.}
     """
@@ -287,23 +287,23 @@ def find_main_tex_file(file_manifest, mode):
     在多Tex文档中，寻找主文件，必须包含documentclass，返回找到的第一个。
     P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
     """
-    candidates = []
+    canidates = []
     for texf in file_manifest:
         if os.path.basename(texf).startswith("merge"):
             continue
         with open(texf, "r", encoding="utf8", errors="ignore") as f:
             file_content = f.read()
         if r"\documentclass" in file_content:
-            candidates.append(texf)
+            canidates.append(texf)
         else:
             continue
 
-    if len(candidates) == 0:
+    if len(canidates) == 0:
         raise RuntimeError("无法找到一个主Tex文件（包含documentclass关键字）")
-    elif len(candidates) == 1:
+    elif len(canidates) == 1:
-        return candidates[0]
+        return canidates[0]
-    else:  # if len(candidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
+    else:  # if len(canidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
-        candidates_score = []
+        canidates_score = []
         # 给出一些判定模板文档的词作为扣分项
         unexpected_words = [
             "\\LaTeX",
@@ -316,19 +316,19 @@ def find_main_tex_file(file_manifest, mode):
             "reviewers",
         ]
         expected_words = ["\\input", "\\ref", "\\cite"]
-        for texf in candidates:
+        for texf in canidates:
-            candidates_score.append(0)
+            canidates_score.append(0)
             with open(texf, "r", encoding="utf8", errors="ignore") as f:
                 file_content = f.read()
                 file_content = rm_comments(file_content)
             for uw in unexpected_words:
                 if uw in file_content:
-                    candidates_score[-1] -= 1
+                    canidates_score[-1] -= 1
             for uw in expected_words:
                 if uw in file_content:
-                    candidates_score[-1] += 1
+                    canidates_score[-1] += 1
-        select = np.argmax(candidates_score)  # 取评分最高者返回
+        select = np.argmax(canidates_score)  # 取评分最高者返回
-        return candidates[select]
+        return canidates[select]
 
 
 def rm_comments(main_file):
@@ -374,7 +374,7 @@ def find_tex_file_ignore_case(fp):
 
 def merge_tex_files_(project_foler, main_file, mode):
     """
-    Merge Tex project recursively
+    Merge Tex project recrusively
     """
     main_file = rm_comments(main_file)
     for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
@@ -429,7 +429,7 @@ def find_title_and_abs(main_file):
 
 def merge_tex_files(project_foler, main_file, mode):
     """
-    Merge Tex project recursively
+    Merge Tex project recrusively
     P.S. 顺便把CTEX塞进去以支持中文
     P.S. 顺便把Latex的注释去除
     """

crazy_functions/media_fns/get_media.py

@@ -1,43 +0,0 @@
-from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
-from shared_utils.docker_as_service_api import stream_daas
-from shared_utils.docker_as_service_api import DockerServiceApiComModel
-import random
-
-def download_video(video_id, only_audio, user_name, chatbot, history):
-    from toolbox import get_log_folder
-    chatbot.append([None, "Processing..."])
-    yield from update_ui(chatbot, history)
-    client_command = f'{video_id} --audio-only' if only_audio else video_id
-    server_urls = get_conf('DAAS_SERVER_URLS')
-    server_url = random.choice(server_urls)
-    docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command)
-    save_file_dir = get_log_folder(user_name, plugin_name='media_downloader')
-    for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir):
-        status_buf = ""
-        status_buf += "DaaS message: \n\n"
-        status_buf += output_manifest['server_message'].replace('\n', '<br/>')
-        status_buf += "\n\n"
-        status_buf += "DaaS standard error: \n\n"
-        status_buf += output_manifest['server_std_err'].replace('\n', '<br/>')
-        status_buf += "\n\n"
-        status_buf += "DaaS standard output: \n\n"
-        status_buf += output_manifest['server_std_out'].replace('\n', '<br/>')
-        status_buf += "\n\n"
-        status_buf += "DaaS file attach: \n\n"
-        status_buf += str(output_manifest['server_file_attach'])
-        yield from update_ui_latest_msg(status_buf, chatbot, history)
-
-    return output_manifest['server_file_attach']
-
-
-def search_videos(keywords):
-    from toolbox import get_log_folder
-    client_command = keywords
-    server_urls = get_conf('DAAS_SERVER_URLS')
-    server_url = random.choice(server_urls)
-    server_url = server_url.replace('stream', 'search')
-    docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command)
-    save_file_dir = get_log_folder("default_user", plugin_name='media_downloader')
-    for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir):
-        return output_manifest['server_message']
-

crazy_functions/multi_stage/multi_stage_utils.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_latest_msg, disable_auto_promotion
+from toolbox import update_ui_lastest_msg, disable_auto_promotion
 from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError

crazy_functions/pdf_fns/parse_pdf.py

@@ -113,7 +113,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
             return [txt]
         else:
             # raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
-            # find a smooth token limit to achieve even separation
+            # 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_text_to_satisfy_token_limit(txt, limit=token_limit_smooth, llm_model=llm_kwargs['llm_model'])

crazy_functions/pdf_fns/parse_pdf_grobid.py

@@ -1,6 +1,6 @@
 import os
 from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
-from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
+from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
 from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive
 from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf
 

crazy_functions/pdf_fns/parse_pdf_via_doc2x.py

@@ -6,128 +6,75 @@ from crazy_functions.crazy_utils import get_files_from_everything
 from shared_utils.colorful import *
 from loguru import logger
 import os
-import requests
 import time
 
+def refresh_key(doc2x_api_key):
+    import requests, json
+    url = "https://api.doc2x.noedgeai.com/api/token/refresh"
+    res = requests.post(
+        url,
+        headers={"Authorization": "Bearer " + doc2x_api_key}
+    )
+    res_json = []
+    if res.status_code == 200:
+        decoded = res.content.decode("utf-8")
+        res_json = json.loads(decoded)
+        doc2x_api_key = res_json['data']['token']
+    else:
+        raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
+    return doc2x_api_key
 
-def retry_request(max_retries=3, delay=3):
-    """
-    Decorator for retrying HTTP requests
-    Args:
-        max_retries: Maximum number of retry attempts
-        delay: Delay between retries in seconds
-    """
-
-    def decorator(func):
-        def wrapper(*args, **kwargs):
-            for attempt in range(max_retries):
-                try:
-                    return func(*args, **kwargs)
-                except Exception as e:
-                    if attempt < max_retries - 1:
-                        logger.error(
-                            f"Request failed, retrying... ({attempt + 1}/{max_retries}) Error: {e}"
-                        )
-                        time.sleep(delay)
-                        continue
-                    raise e
-            return None
-
-        return wrapper
-
-    return decorator
-
-
-@retry_request()
-def make_request(method, url, **kwargs):
-    """
-    Make HTTP request with retry mechanism
-    """
-    return requests.request(method, url, **kwargs)
-
-
-def doc2x_api_response_status(response, uid=""):
-    """
-    Check the status of Doc2x API response
-    Args:
-        response_data: Response object from Doc2x API
-    """
-    response_json = response.json()
-    response_data = response_json.get("data", {})
-    code = response_json.get("code", "Unknown")
-    meg = response_data.get("message", response_json)
-    trace_id = response.headers.get("trace-id", "Failed to get trace-id")
-    if response.status_code != 200:
-        raise RuntimeError(
-            f"Doc2x return an error:\nTrace ID: {trace_id} {uid}\n{response.status_code} - {response_json}"
-        )
-    if code in ["parse_page_limit_exceeded", "parse_concurrency_limit"]:
-        raise RuntimeError(
-            f"Reached the limit of Doc2x:\nTrace ID: {trace_id} {uid}\n{code} - {meg}"
-        )
-    if code not in ["ok", "success"]:
-        raise RuntimeError(
-            f"Doc2x return an error:\nTrace ID: {trace_id} {uid}\n{code} - {meg}"
-        )
-    return response_data
 
 
 def 解析PDF_DOC2X_转Latex(pdf_file_path):
-    zip_file_path, unzipped_folder = 解析PDF_DOC2X(pdf_file_path, format="tex")
+    zip_file_path, unzipped_folder = 解析PDF_DOC2X(pdf_file_path, format='tex')
     return unzipped_folder
 
 
-def 解析PDF_DOC2X(pdf_file_path, format="tex"):
+def 解析PDF_DOC2X(pdf_file_path, format='tex'):
     """
-    format: 'tex', 'md', 'docx'
+        format: 'tex', 'md', 'docx'
     """
-
+    import requests, json, os
-    DOC2X_API_KEY = get_conf("DOC2X_API_KEY")
+    DOC2X_API_KEY = get_conf('DOC2X_API_KEY')
     latex_dir = get_log_folder(plugin_name="pdf_ocr_latex")
     markdown_dir = get_log_folder(plugin_name="pdf_ocr")
     doc2x_api_key = DOC2X_API_KEY
 
-    # < ------ 第1步：预上传获取URL，然后上传文件 ------ >
-    logger.info("Doc2x 上传文件：预上传获取URL")
-    res = make_request(
-        "POST",
-        "https://v2.doc2x.noedgeai.com/api/v2/parse/preupload",
-        headers={"Authorization": "Bearer " + doc2x_api_key},
-        timeout=15,
-    )
-    res_data = doc2x_api_response_status(res)
-    upload_url = res_data["url"]
-    uuid = res_data["uid"]
 
-    logger.info("Doc2x 上传文件：上传文件")
+    # < ------ 第1步：上传 ------ >
-    with open(pdf_file_path, "rb") as file:
+    logger.info("Doc2x 第1步：上传")
-        res = make_request("PUT", upload_url, data=file, timeout=60)
+    with open(pdf_file_path, 'rb') as file:
-    res.raise_for_status()
+        res = requests.post(
+            "https://v2.doc2x.noedgeai.com/api/v2/parse/pdf",
+            headers={"Authorization": "Bearer " + doc2x_api_key},
+            data=file
+        )
+    # res_json = []
+    if res.status_code == 200:
+        res_json = res.json()
+    else:
+        raise RuntimeError(f"Doc2x return an error: {res.json()}")
+    uuid = res_json['data']['uid']
 
     # < ------ 第2步：轮询等待 ------ >
-    logger.info("Doc2x 处理文件中：轮询等待")
+    logger.info("Doc2x 第2步：轮询等待")
-    params = {"uid": uuid}
+    params = {'uid': uuid}
-    max_attempts = 60
+    while True:
-    attempt = 0
+        res = requests.get(
-    while attempt < max_attempts:
+            'https://v2.doc2x.noedgeai.com/api/v2/parse/status',
-        res = make_request(
-            "GET",
-            "https://v2.doc2x.noedgeai.com/api/v2/parse/status",
             headers={"Authorization": "Bearer " + doc2x_api_key},
-            params=params,
+            params=params
-            timeout=15,
         )
-        res_data = doc2x_api_response_status(res)
+        res_json = res.json()
-        if res_data["status"] == "success":
+        if res_json['data']['status'] == "success":
             break
-        elif res_data["status"] == "processing":
+        elif res_json['data']['status'] == "processing":
-            time.sleep(5)
+            time.sleep(3)
-            logger.info(f"Doc2x is processing at {res_data['progress']}%")
+            logger.info(f"Doc2x is processing at {res_json['data']['progress']}%")
-            attempt += 1
+        elif res_json['data']['status'] == "failed":
-        else:
+            raise RuntimeError(f"Doc2x return an error: {res_json}")
-            raise RuntimeError(f"Doc2x return an error: {res_data}")
+
-    if attempt >= max_attempts:
-        raise RuntimeError("Doc2x processing timeout after maximum attempts")
 
     # < ------ 第3步：提交转化 ------ >
     logger.info("Doc2x 第3步：提交转化")
@@ -137,44 +84,42 @@ def 解析PDF_DOC2X(pdf_file_path, format="tex"):
         "formula_mode": "dollar",
         "filename": "output"
     }
-    res = make_request(
+    res = requests.post(
-        "POST",
+        'https://v2.doc2x.noedgeai.com/api/v2/convert/parse',
-        "https://v2.doc2x.noedgeai.com/api/v2/convert/parse",
         headers={"Authorization": "Bearer " + doc2x_api_key},
-        json=data,
+        json=data
-        timeout=15,
     )
-    doc2x_api_response_status(res, uid=f"uid: {uuid}")
+    if res.status_code == 200:
+        res_json = res.json()
+    else:
+        raise RuntimeError(f"Doc2x return an error: {res.json()}")
+
 
     # < ------ 第4步：等待结果 ------ >
     logger.info("Doc2x 第4步：等待结果")
-    params = {"uid": uuid}
+    params = {'uid': uuid}
-    max_attempts = 36
+    while True:
-    attempt = 0
+        res = requests.get(
-    while attempt < max_attempts:
+            'https://v2.doc2x.noedgeai.com/api/v2/convert/parse/result',
-        res = make_request(
-            "GET",
-            "https://v2.doc2x.noedgeai.com/api/v2/convert/parse/result",
             headers={"Authorization": "Bearer " + doc2x_api_key},
-            params=params,
+            params=params
-            timeout=15,
         )
-        res_data = doc2x_api_response_status(res, uid=f"uid: {uuid}")
+        res_json = res.json()
-        if res_data["status"] == "success":
+        if res_json['data']['status'] == "success":
             break
-        elif res_data["status"] == "processing":
+        elif res_json['data']['status'] == "processing":
             time.sleep(3)
-            logger.info("Doc2x still processing to convert file")
+            logger.info(f"Doc2x still processing")
-            attempt += 1
+        elif res_json['data']['status'] == "failed":
-    if attempt >= max_attempts:
+            raise RuntimeError(f"Doc2x return an error: {res_json}")
-        raise RuntimeError("Doc2x conversion timeout after maximum attempts")
+
 
     # < ------ 第5步：最后的处理 ------ >
-    logger.info("Doc2x 第5步：下载转换后的文件")
+    logger.info("Doc2x 第5步：最后的处理")
 
-    if format == "tex":
+    if format=='tex':
         target_path = latex_dir
-    if format == "md":
+    if format=='md':
         target_path = markdown_dir
     os.makedirs(target_path, exist_ok=True)
 
@@ -182,18 +127,17 @@ def 解析PDF_DOC2X(pdf_file_path, format="tex"):
     # < ------ 下载 ------ >
     for attempt in range(max_attempt):
         try:
-            result_url = res_data["url"]
+            result_url = res_json['data']['url']
-            res = make_request("GET", result_url, timeout=60)
+            res = requests.get(result_url)
-            zip_path = os.path.join(target_path, gen_time_str() + ".zip")
+            zip_path = os.path.join(target_path, gen_time_str() + '.zip')
             unzip_path = os.path.join(target_path, gen_time_str())
             if res.status_code == 200:
-                with open(zip_path, "wb") as f:
+                with open(zip_path, "wb") as f: f.write(res.content)
-                    f.write(res.content)
             else:
                 raise RuntimeError(f"Doc2x return an error: {res.json()}")
         except Exception as e:
             if attempt < max_attempt - 1:
-                logger.error(f"Failed to download uid = {uuid} file, retrying... {e}")
+                logger.error(f"Failed to download latex file, retrying... {e}")
                 time.sleep(3)
                 continue
             else:
@@ -201,31 +145,22 @@ def 解析PDF_DOC2X(pdf_file_path, format="tex"):
 
     # < ------ 解压 ------ >
     import zipfile
-    with zipfile.ZipFile(zip_path, "r") as zip_ref:
+    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
         zip_ref.extractall(unzip_path)
     return zip_path, unzip_path
 
 
-def 解析PDF_DOC2X_单文件(
+def 解析PDF_DOC2X_单文件(fp, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, DOC2X_API_KEY, user_request):
-    fp,
+
-    project_folder,
-    llm_kwargs,
-    plugin_kwargs,
-    chatbot,
-    history,
-    system_prompt,
-    DOC2X_API_KEY,
-    user_request,
-):
     def pdf2markdown(filepath):
         chatbot.append((None, f"Doc2x 解析中"))
-        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
-        md_zip_path, unzipped_folder = 解析PDF_DOC2X(filepath, format="md")
+        md_zip_path, unzipped_folder = 解析PDF_DOC2X(filepath, format='md')
 
         promote_file_to_downloadzone(md_zip_path, chatbot=chatbot)
         chatbot.append((None, f"完成解析 {md_zip_path} ..."))
-        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 md_zip_path
 
     def deliver_to_markdown_plugin(md_zip_path, user_request):
@@ -239,97 +174,77 @@ def 解析PDF_DOC2X_单文件(
         os.makedirs(target_path_base, exist_ok=True)
         shutil.copyfile(md_zip_path, this_file_path)
         ex_folder = this_file_path + ".extract"
-        extract_archive(file_path=this_file_path, dest_dir=ex_folder)
+        extract_archive(
+            file_path=this_file_path, dest_dir=ex_folder
+        )
 
         # edit markdown files
-        success, file_manifest, project_folder = get_files_from_everything(
+        success, file_manifest, project_folder = get_files_from_everything(ex_folder, type='.md')
-            ex_folder, type=".md"
-        )
         for generated_fp in file_manifest:
             # 修正一些公式问题
-            with open(generated_fp, "r", encoding="utf8") as f:
+            with open(generated_fp, 'r', encoding='utf8') as f:
                 content = f.read()
             # 将公式中的\[ \]替换成$$
-            content = content.replace(r"\[", r"$$").replace(r"\]", r"$$")
+            content = content.replace(r'\[', r'$$').replace(r'\]', r'$$')
             # 将公式中的\( \)替换成$
-            content = content.replace(r"\(", r"$").replace(r"\)", r"$")
+            content = content.replace(r'\(', r'$').replace(r'\)', r'$')
-            content = content.replace("```markdown", "\n").replace("```", "\n")
+            content = content.replace('```markdown', '\n').replace('```', '\n')
-            with open(generated_fp, "w", encoding="utf8") as f:
+            with open(generated_fp, 'w', encoding='utf8') as f:
                 f.write(content)
             promote_file_to_downloadzone(generated_fp, chatbot=chatbot)
-            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
             # 生成在线预览html
-            file_name = "在线预览翻译（原文）" + gen_time_str() + ".html"
+            file_name = '在线预览翻译（原文）' + gen_time_str() + '.html'
             preview_fp = os.path.join(ex_folder, file_name)
-            from shared_utils.advanced_markdown_format import (
+            from shared_utils.advanced_markdown_format import markdown_convertion_for_file
-                markdown_convertion_for_file,
-            )
-
             with open(generated_fp, "r", encoding="utf-8") as f:
                 md = f.read()
             #     # Markdown中使用不标准的表格，需要在表格前加上一个emoji，以便公式渲染
             #     md = re.sub(r'^<table>', r'.<table>', md, flags=re.MULTILINE)
             html = markdown_convertion_for_file(md)
-            with open(preview_fp, "w", encoding="utf-8") as f:
+            with open(preview_fp, "w", encoding="utf-8") as f: f.write(html)
-                f.write(html)
             chatbot.append([None, f"生成在线预览：{generate_file_link([preview_fp])}"])
             promote_file_to_downloadzone(preview_fp, chatbot=chatbot)
 
-        chatbot.append((None, f"调用Markdown插件 {ex_folder} ..."))
-        plugin_kwargs["markdown_expected_output_dir"] = ex_folder
 
-        translated_f_name = "translated_markdown.md"
+
-        generated_fp = plugin_kwargs["markdown_expected_output_path"] = os.path.join(
+        chatbot.append((None, f"调用Markdown插件 {ex_folder} ..."))
-            ex_folder, translated_f_name
+        plugin_kwargs['markdown_expected_output_dir'] = ex_folder
-        )
+
-        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        translated_f_name = 'translated_markdown.md'
-        yield from Markdown英译中(
+        generated_fp = plugin_kwargs['markdown_expected_output_path'] = os.path.join(ex_folder, translated_f_name)
-            ex_folder,
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-            llm_kwargs,
+        yield from Markdown英译中(ex_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
-            plugin_kwargs,
-            chatbot,
-            history,
-            system_prompt,
-            user_request,
-        )
         if os.path.exists(generated_fp):
             # 修正一些公式问题
-            with open(generated_fp, "r", encoding="utf8") as f:
+            with open(generated_fp, 'r', encoding='utf8') as f: content = f.read()
-                content = f.read()
+            content = content.replace('```markdown', '\n').replace('```', '\n')
-            content = content.replace("```markdown", "\n").replace("```", "\n")
             # Markdown中使用不标准的表格，需要在表格前加上一个emoji，以便公式渲染
             # content = re.sub(r'^<table>', r'.<table>', content, flags=re.MULTILINE)
-            with open(generated_fp, "w", encoding="utf8") as f:
+            with open(generated_fp, 'w', encoding='utf8') as f: f.write(content)
-                f.write(content)
             # 生成在线预览html
-            file_name = "在线预览翻译" + gen_time_str() + ".html"
+            file_name = '在线预览翻译' + gen_time_str() + '.html'
             preview_fp = os.path.join(ex_folder, file_name)
-            from shared_utils.advanced_markdown_format import (
+            from shared_utils.advanced_markdown_format import markdown_convertion_for_file
-                markdown_convertion_for_file,
-            )
-
             with open(generated_fp, "r", encoding="utf-8") as f:
                 md = f.read()
             html = markdown_convertion_for_file(md)
-            with open(preview_fp, "w", encoding="utf-8") as f:
+            with open(preview_fp, "w", encoding="utf-8") as f: f.write(html)
-                f.write(html)
             promote_file_to_downloadzone(preview_fp, chatbot=chatbot)
             # 生成包含图片的压缩包
             dest_folder = get_log_folder(chatbot.get_user())
-            zip_name = "翻译后的带图文档.zip"
+            zip_name = '翻译后的带图文档.zip'
-            zip_folder(
+            zip_folder(source_folder=ex_folder, dest_folder=dest_folder, zip_name=zip_name)
-                source_folder=ex_folder, dest_folder=dest_folder, zip_name=zip_name
-            )
             zip_fp = os.path.join(dest_folder, zip_name)
             promote_file_to_downloadzone(zip_fp, chatbot=chatbot)
-            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
     md_zip_path = yield from pdf2markdown(fp)
     yield from deliver_to_markdown_plugin(md_zip_path, user_request)
 
-
 def 解析PDF_基于DOC2X(file_manifest, *args):
     for index, fp in enumerate(file_manifest):
         yield from 解析PDF_DOC2X_单文件(fp, *args)
     return
+
+

crazy_functions/pdf_fns/parse_word.py

@@ -14,17 +14,17 @@ def extract_text_from_files(txt, chatbot, history):
         final_result(list):文本内容
         page_one(list):第一页内容/摘要
         file_manifest(list):文件路径
-        exception(string):需要用户手动处理的信息,如没出错则保持为空
+        excption(string):需要用户手动处理的信息,如没出错则保持为空
     """
 
     final_result = []
     page_one = []
     file_manifest = []
-    exception = ""
+    excption = ""
 
     if txt == "":
         final_result.append(txt)
-        return False, final_result, page_one, file_manifest, exception   #如输入区内容不是文件则直接返回输入区内容
+        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
 
     #查找输入区内容中的文件
     file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
@@ -33,20 +33,20 @@ def extract_text_from_files(txt, chatbot, history):
     file_doc,doc_manifest,folder_doc = get_files_from_everything(txt, '.doc')
 
     if file_doc:
-        exception = "word"
+        excption = "word"
-        return False, final_result, page_one, file_manifest, exception
+        return False, final_result, page_one, file_manifest, excption
 
     file_num = len(pdf_manifest) + len(md_manifest) + len(word_manifest)
     if file_num == 0:
         final_result.append(txt)
-        return False, final_result, page_one, file_manifest, exception   #如输入区内容不是文件则直接返回输入区内容
+        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
 
     if file_pdf:
         try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
             import fitz
         except:
-            exception = "pdf"
+            excption = "pdf"
-            return False, final_result, page_one, file_manifest, exception
+            return False, final_result, page_one, file_manifest, excption
         for index, fp in enumerate(pdf_manifest):
             file_content, pdf_one = read_and_clean_pdf_text(fp) # （尝试）按照章节切割PDF
             file_content = file_content.encode('utf-8', 'ignore').decode()   # avoid reading non-utf8 chars
@@ -72,8 +72,8 @@ def extract_text_from_files(txt, chatbot, history):
         try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
             from docx import Document
         except:
-            exception = "word_pip"
+            excption = "word_pip"
-            return False, final_result, page_one, file_manifest, exception
+            return False, final_result, page_one, file_manifest, excption
         for index, fp in enumerate(word_manifest):
             doc = Document(fp)
             file_content = '\n'.join([p.text for p in doc.paragraphs])
@@ -82,4 +82,4 @@ def extract_text_from_files(txt, chatbot, history):
             final_result.append(file_content)
             file_manifest.append(os.path.relpath(fp, folder_word))
 
-    return True, final_result, page_one, file_manifest, exception
+    return True, final_result, page_one, file_manifest, excption

crazy_functions/rag_fns/rag_file_support.py

@@ -1,22 +1,45 @@
 import os
 from llama_index.core import SimpleDirectoryReader
 
-supports_format = ['.csv', '.docx', '.epub', '.ipynb',  '.mbox', '.md', '.pdf',  '.txt', '.ppt',
+supports_format = ['.csv', '.docx','.doc', '.epub', '.ipynb',  '.mbox', '.md', '.pdf',  '.txt', '.ppt',
-                   '.pptm', '.pptx']
+                   '.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 supports_format:
+    if ext in ['.docx', '.doc']:
-        try:
+        return read_docx_doc(file_path)
-            reader = SimpleDirectoryReader(input_files=[file_path])
+    try:
-            documents = reader.load_data()
+        reader = SimpleDirectoryReader(input_files=[file_path])
-            if len(documents) > 0:
+        documents = reader.load_data()
-                return documents[0].text
+        if len(documents) > 0:
-        except Exception as e:
+            return documents[0].text
-            pass
+    except Exception as e:
+        pass
 
     return None

crazy_functions/vector_fns/vector_database.py

@@ -60,7 +60,7 @@ def similarity_search_with_score_by_vector(
         self, embedding: List[float], k: int = 4
 ) -> List[Tuple[Document, float]]:
 
-    def separate_list(ls: List[int]) -> List[List[int]]:
+    def seperate_list(ls: List[int]) -> List[List[int]]:
         lists = []
         ls1 = [ls[0]]
         for i in range(1, len(ls)):
@@ -82,7 +82,7 @@ def similarity_search_with_score_by_vector(
             continue
         _id = self.index_to_docstore_id[i]
         doc = self.docstore.search(_id)
-        if not self.chunk_content:
+        if not self.chunk_conent:
             if not isinstance(doc, Document):
                 raise ValueError(f"Could not find document for id {_id}, got {doc}")
             doc.metadata["score"] = int(scores[0][j])
@@ -104,12 +104,12 @@ def similarity_search_with_score_by_vector(
                         id_set.add(l)
             if break_flag:
                 break
-    if not self.chunk_content:
+    if not self.chunk_conent:
         return docs
     if len(id_set) == 0 and self.score_threshold > 0:
         return []
     id_list = sorted(list(id_set))
-    id_lists = separate_list(id_list)
+    id_lists = seperate_list(id_list)
     for id_seq in id_lists:
         for id in id_seq:
             if id == id_seq[0]:
@@ -132,7 +132,7 @@ class LocalDocQA:
     embeddings: object = None
     top_k: int = VECTOR_SEARCH_TOP_K
     chunk_size: int = CHUNK_SIZE
-    chunk_content: bool = True
+    chunk_conent: bool = True
     score_threshold: int = VECTOR_SEARCH_SCORE_THRESHOLD
 
     def init_cfg(self,
@@ -209,16 +209,16 @@ class LocalDocQA:
 
     # query      查询内容
     # vs_path    知识库路径
-    # chunk_content   是否启用上下文关联
+    # chunk_conent   是否启用上下文关联
     # score_threshold    搜索匹配score阈值
     # vector_search_top_k   搜索知识库内容条数，默认搜索5条结果
     # chunk_sizes    匹配单段内容的连接上下文长度
-    def get_knowledge_based_content_test(self, query, vs_path, chunk_content,
+    def get_knowledge_based_conent_test(self, query, vs_path, chunk_conent,
                                         score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
                                         vector_search_top_k=VECTOR_SEARCH_TOP_K, chunk_size=CHUNK_SIZE,
                                         text2vec=None):
         self.vector_store = FAISS.load_local(vs_path, text2vec)
-        self.vector_store.chunk_content = chunk_content
+        self.vector_store.chunk_conent = chunk_conent
         self.vector_store.score_threshold = score_threshold
         self.vector_store.chunk_size = chunk_size
 
@@ -241,7 +241,7 @@ class LocalDocQA:
 
 
 
-def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_content, one_content_segmentation, text2vec):
+def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_conent, one_content_segmentation, text2vec):
     for file in files:
         assert os.path.exists(file), "输入文件不存在：" + file
     import nltk
@@ -297,7 +297,7 @@ class knowledge_archive_interface():
             files=file_manifest,
             sentence_size=100,
             history=[],
-            one_content="",
+            one_conent="",
             one_content_segmentation="",
             text2vec = self.get_chinese_text2vec(),
         )
@@ -319,19 +319,19 @@ class knowledge_archive_interface():
                 files=[],
                 sentence_size=100,
                 history=[],
-                one_content="",
+                one_conent="",
                 one_content_segmentation="",
                 text2vec = self.get_chinese_text2vec(),
             )
         VECTOR_SEARCH_SCORE_THRESHOLD = 0
         VECTOR_SEARCH_TOP_K = 4
         CHUNK_SIZE = 512
-        resp, prompt = self.qa_handle.get_knowledge_based_content_test(
+        resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
             query = txt,
             vs_path = self.kai_path,
             score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
             vector_search_top_k=VECTOR_SEARCH_TOP_K,
-            chunk_content=True,
+            chunk_conent=True,
             chunk_size=CHUNK_SIZE,
             text2vec = self.get_chinese_text2vec(),
         )

crazy_functions/vt_fns/vt_call_plugin.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_latest_msg, disable_auto_promotion
+from toolbox import update_ui_lastest_msg, disable_auto_promotion
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
 import copy, json, pickle, os, sys, time
@@ -9,14 +9,14 @@ import copy, json, pickle, os, sys, time
 def read_avail_plugin_enum():
     from crazy_functional import get_crazy_functions
     plugin_arr = get_crazy_functions()
-    # remove plugins with out explanation
+    # remove plugins with out explaination
     plugin_arr = {k:v for k, v in plugin_arr.items() if ('Info' in v) and ('Function' in v)}
     plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
     prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
-    prompt = "\n\nThe definition of PluginEnum:\nPluginEnum=" + prompt
+    prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt
     return prompt, plugin_arr_dict, plugin_arr_dict_parse
 
 def wrap_code(txt):
@@ -55,7 +55,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
         reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
     # ⭐ ⭐ ⭐ 选择插件
-    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
     gpt_json_io = GptJsonIO(Plugin)
     gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n"
     gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n"""
@@ -74,13 +74,13 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         msg += "请求的Prompt为：\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
         msg += "语言模型回复为：\n" + wrap_code(gpt_reply)
         msg += "\n但您可以尝试再试一次\n"
-        yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
     if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
         msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
         msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件：\n" + wrap_code(gpt_reply)
         msg += "\n但您可以尝试再试一次\n"
-        yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
 
     # ⭐ ⭐ ⭐ 确认插件参数
@@ -90,7 +90,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         appendix_info = get_recent_file_prompt_support(chatbot)
 
     plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
-    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
     class PluginExplicit(BaseModel):
         plugin_selection: str = plugin_sel.plugin_selection
         plugin_arg: str = Field(description="The argument of the plugin.", default="")
@@ -109,6 +109,6 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
     fn = plugin['Function']
     fn_name = fn.__name__
     msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。'
-    yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+    yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
     yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
     return

crazy_functions/vt_fns/vt_modify_config.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_latest_msg, get_conf
+from toolbox import update_ui_lastest_msg, get_conf
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO
 import copy, json, pickle, os, sys
@@ -9,7 +9,7 @@ import copy, json, pickle, os, sys
 def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
     ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
     if not ALLOW_RESET_CONFIG:
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
             chatbot=chatbot, history=history, delay=2
         )
@@ -30,7 +30,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         new_option_value: str = Field(description="the new value of the option", default=None)
 
     # ⭐ ⭐ ⭐ 分析用户意图
-    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
     gpt_json_io = GptJsonIO(ModifyConfigurationIntention)
     inputs = "Analyze how to change configuration according to following user input, answer me with json: \n\n" + \
              ">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
@@ -44,11 +44,11 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
 
     ok = (explicit_conf in txt)
     if ok:
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}",
             chatbot=chatbot, history=history, delay=1
         )
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中",
             chatbot=chatbot, history=history, delay=2
         )
@@ -57,25 +57,25 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         from toolbox import set_conf
         set_conf(explicit_conf, user_intention.new_option_value)
 
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n配置修改完成，重新页面即可生效。", chatbot=chatbot, history=history, delay=1
         )
     else:
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"失败，如果需要配置{explicit_conf}，您需要明确说明并在指令中提到它。", chatbot=chatbot, history=history, delay=5
         )
 
 def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
     ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
     if not ALLOW_RESET_CONFIG:
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
             chatbot=chatbot, history=history, delay=2
         )
         return
 
     yield from modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
-    yield from update_ui_latest_msg(
+    yield from update_ui_lastest_msg(
         lastmsg=f"正在执行任务: {txt}\n\n配置修改完成，五秒后即将重启！若出现报错请无视即可。", chatbot=chatbot, history=history, delay=5
     )
     os.execl(sys.executable, sys.executable, *sys.argv)

crazy_functions/vt_fns/vt_state.py

@@ -5,7 +5,7 @@ class VoidTerminalState():
         self.reset_state()
 
     def reset_state(self):
-        self.has_provided_explanation = False
+        self.has_provided_explaination = False
 
     def lock_plugin(self, chatbot):
         chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'

crazy_functions/互动小游戏.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, update_ui_latest_msg
+from toolbox import CatchException, update_ui, update_ui_lastest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection

crazy_functions/函数动态生成.py

@@ -15,7 +15,7 @@ Testing:
 
 
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
-from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
+from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
 from crazy_functions.crazy_utils import input_clipping, try_install_deps
 from crazy_functions.gen_fns.gen_fns_shared import is_function_successfully_generated
@@ -27,7 +27,7 @@ import time
 import glob
 import multiprocessing
 
-template = """
+templete = """
 ```python
 import ...  # Put dependencies here, e.g. import numpy as np.
 
@@ -77,10 +77,10 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
 
     # 第二步
     prompt_compose = [
-        "If previous stage is successful, rewrite the function you have just written to satisfy following template: \n",
+        "If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n",
-        template
+        templete
     ]
-    i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable template. "
+    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,
@@ -164,18 +164,18 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
     if get_plugin_arg(plugin_kwargs, key="file_path_arg", default=False):
         file_path = get_plugin_arg(plugin_kwargs, key="file_path_arg", default=None)
         file_list.append(file_path)
-        yield from update_ui_latest_msg(f"当前文件: {file_path}", chatbot, history, 1)
+        yield from update_ui_lastest_msg(f"当前文件: {file_path}", chatbot, history, 1)
     elif have_any_recent_upload_files(chatbot):
         file_dir = get_recent_file_prompt_support(chatbot)
         file_list = glob.glob(os.path.join(file_dir, '**/*'), recursive=True)
-        yield from update_ui_latest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
+        yield from update_ui_lastest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
     else:
         chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
-        yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
+        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
         return  # 2. 如果没有文件
     if len(file_list) == 0:
         chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
-        yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
+        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
         return  # 2. 如果没有文件
 
     # 读取文件
@@ -183,7 +183,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
 
     # 粗心检查
     if is_the_upload_folder(txt):
-        yield from update_ui_latest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
+        yield from update_ui_lastest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
         return
 
     # 开始干正事
@@ -195,7 +195,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
             code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
                 yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
             chatbot.append(["代码生成阶段结束", ""])
-            yield from update_ui_latest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
+            yield from update_ui_lastest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
             # ⭐ 分离代码块
             code = get_code_block(code)
             # ⭐ 检查模块
@@ -206,11 +206,11 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
             if not traceback: traceback = trimmed_format_exc()
         # 处理异常
         if not traceback: traceback = trimmed_format_exc()
-        yield from update_ui_latest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
+        yield from update_ui_lastest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
 
     # 代码生成结束, 开始执行
     TIME_LIMIT = 15
-    yield from update_ui_latest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
+    yield from update_ui_lastest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
     manager = multiprocessing.Manager()
     return_dict = manager.dict()
 

crazy_functions/多智能体.py

@@ -8,7 +8,7 @@
 
 import time
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
-from toolbox import get_conf, select_api_key, update_ui_latest_msg, Singleton
+from toolbox import get_conf, select_api_key, update_ui_lastest_msg, Singleton
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
 from crazy_functions.crazy_utils import input_clipping, try_install_deps
 from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses

crazy_functions/批量文件询问.py

@@ -0,0 +1,493 @@
+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概述，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"根据以下内容，按要求：{self.plugin_kwargs['advanced_arg']}，"
+                             f"总结文件 {os.path.basename(rel_path)} 的主要内容。")
+                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} 的总结"],
+                        llm_kwargs=self.llm_kwargs,
+                        chatbot=self.chatbot,
+                        history_array=[summary_texts],
+                        sys_prompt_array=["总结文件内容。"],
+                    )
+                    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
+        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)

crazy_functions/批量翻译PDF文档_NOUGAT.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
-from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
+from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
 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
 from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency

crazy_functions/数学动画生成manim.py

@@ -166,7 +166,7 @@ class PointWithTrace(Scene):
 
 ```
 
-# do not use get_graph, this function is deprecated
+# do not use get_graph, this funciton is deprecated
 
 class ExampleFunctionGraph(Scene):
     def construct(self):

crazy_functions/生成多种Mermaid图表.py

@@ -324,16 +324,16 @@ def 生成多种Mermaid图表(
     if os.path.exists(txt):  # 如输入区无内容则直接解析历史记录
         from crazy_functions.pdf_fns.parse_word import extract_text_from_files
 
-        file_exist, final_result, page_one, file_manifest, exception = (
+        file_exist, final_result, page_one, file_manifest, excption = (
             extract_text_from_files(txt, chatbot, history)
         )
     else:
         file_exist = False
-        exception = ""
+        excption = ""
         file_manifest = []
 
-    if exception != "":
+    if excption != "":
-        if exception == "word":
+        if excption == "word":
             report_exception(
                 chatbot,
                 history,
@@ -341,7 +341,7 @@ def 生成多种Mermaid图表(
                 b=f"找到了.doc文件，但是该文件格式不被支持，请先转化为.docx格式。",
             )
 
-        elif exception == "pdf":
+        elif excption == "pdf":
             report_exception(
                 chatbot,
                 history,
@@ -349,7 +349,7 @@ def 生成多种Mermaid图表(
                 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```。",
             )
 
-        elif exception == "word_pip":
+        elif excption == "word_pip":
             report_exception(
                 chatbot,
                 history,

crazy_functions/知识库问答.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_latest_msg, get_log_folder, get_user
+from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_lastest_msg, get_log_folder, get_user
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
 from loguru import logger
 install_msg ="""
@@ -42,7 +42,7 @@ def 知识库文件注入(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         # from crazy_functions.crazy_utils import try_install_deps
         # try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
-        # yield from update_ui_latest_msg("安装完成，您可以再次重试。", chatbot, history)
+        # yield from update_ui_lastest_msg("安装完成，您可以再次重试。", chatbot, history)
         return
 
     # < --------------------读取文件--------------- >
@@ -95,7 +95,7 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         # from crazy_functions.crazy_utils import try_install_deps
         # try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
-        # yield from update_ui_latest_msg("安装完成，您可以再次重试。", chatbot, history)
+        # yield from update_ui_lastest_msg("安装完成，您可以再次重试。", chatbot, history)
         return
 
     # < -------------------  --------------- >

crazy_functions/虚空终端.py

@@ -47,7 +47,7 @@ explain_msg = """
 from pydantic import BaseModel, Field
 from typing import List
 from toolbox import CatchException, update_ui, is_the_upload_folder
-from toolbox import update_ui_latest_msg, disable_auto_promotion
+from toolbox import update_ui_lastest_msg, disable_auto_promotion
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.crazy_utils import input_clipping
@@ -113,19 +113,19 @@ def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
     # 用简单的关键词检测用户意图
     is_certain, _ = analyze_intention_with_simple_rules(txt)
     if is_the_upload_folder(txt):
-        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=False)
+        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=False)
         appendix_msg = "\n\n**很好，您已经上传了文件**，现在请您描述您的需求。"
 
-    if is_certain or (state.has_provided_explanation):
+    if is_certain or (state.has_provided_explaination):
         # 如果意图明确，跳过提示环节
-        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
+        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
         state.unlock_plugin(chatbot=chatbot)
         yield from update_ui(chatbot=chatbot, history=history)
         yield from 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
         return
     else:
         # 如果意图模糊，提示
-        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
+        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
         state.lock_plugin(chatbot=chatbot)
         chatbot.append(("虚空终端状态:", explain_msg+appendix_msg))
         yield from update_ui(chatbot=chatbot, history=history)
@@ -141,7 +141,7 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     # ⭐ ⭐ ⭐ 分析用户意图
     is_certain, user_intention = analyze_intention_with_simple_rules(txt)
     if not is_certain:
-        yield from update_ui_latest_msg(
+        yield from update_ui_lastest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
         gpt_json_io = GptJsonIO(UserIntention)
         rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
@@ -154,13 +154,13 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
             user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
             lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
         except JsonStringError as e:
-            yield from update_ui_latest_msg(
+            yield from update_ui_lastest_msg(
                 lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型（{llm_kwargs['llm_model']}）不能理解您的意图", chatbot=chatbot, history=history, delay=0)
             return
     else:
         pass
 
-    yield from update_ui_latest_msg(
+    yield from update_ui_lastest_msg(
         lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
         chatbot=chatbot, history=history, delay=0)
 

crazy_functions/语音助手.py

@@ -42,7 +42,7 @@ class AsyncGptTask():
             MAX_TOKEN_ALLO = 2560
             i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO)
             gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt,
-                                                            observe_window=observe_window[index], console_silence=True)
+                                                            observe_window=observe_window[index], console_slience=True)
         except ConnectionAbortedError as token_exceed_err:
             logger.error('至少一个线程任务Token溢出而失败', e)
         except Exception as e:

crazy_functions/谷歌检索小助手.py

@@ -1,6 +1,6 @@
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from toolbox import CatchException, report_exception, promote_file_to_downloadzone
-from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion, write_history_to_file
+from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
 import logging
 import requests
 import time
@@ -156,7 +156,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     history = []
     meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
     if len(meta_paper_info_list) == 0:
-        yield from update_ui_latest_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)
+        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
     for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):

docs/GithubAction+AllCapacity

@@ -5,10 +5,6 @@ FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
 
 # edge-tts需要的依赖，某些pip包所需的依赖
 RUN apt update && apt install ffmpeg build-essential -y
-RUN apt-get install -y fontconfig
-RUN ln -s /usr/local/texlive/2023/texmf-dist/fonts/truetype /usr/share/fonts/truetype/texlive
-RUN fc-cache -fv
-RUN apt-get clean
 
 # use python3 as the system default python
 WORKDIR /gpt
@@ -34,7 +30,7 @@ RUN python3 -m pip install -r request_llms/requirements_qwen.txt
 RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
 RUN python3 -m pip install -r request_llms/requirements_newbing.txt
 RUN python3 -m pip install nougat-ocr
-RUN python3 -m pip cache purge
+
 
 # 预热Tiktoken模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'

docs/GithubAction+ChatGLM+Moss

@@ -7,7 +7,6 @@ RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
 
 # edge-tts需要的依赖，某些pip包所需的依赖
 RUN apt update && apt install ffmpeg build-essential -y
-RUN apt-get clean
 
 # use python3 as the system default python
 RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
@@ -23,7 +22,6 @@ RUN python3 -m pip install -r request_llms/requirements_moss.txt
 RUN python3 -m pip install -r request_llms/requirements_qwen.txt
 RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
 RUN python3 -m pip install -r request_llms/requirements_newbing.txt
-RUN python3 -m pip cache purge
 
 
 # 预热Tiktoken模块

docs/GithubAction+NoLocal

@@ -18,7 +18,5 @@ RUN apt update && apt install ffmpeg -y
 # 可选步骤，用于预热模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
-RUN python3 -m pip cache purge && apt-get clean
-
 # 启动
 CMD ["python3", "-u", "main.py"]

docs/GithubAction+NoLocal+Latex

@@ -30,7 +30,5 @@ COPY --chown=gptuser:gptuser . .
 # 可选步骤，用于预热模块
 RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
-RUN python3 -m pip cache purge
-
 # 启动
 CMD ["python3", "-u", "main.py"]

docs/GithubAction+NoLocal+Vectordb

@@ -24,8 +24,6 @@ RUN apt update && apt install ffmpeg -y
 
 # 可选步骤，用于预热模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
-RUN python3 -m pip cache purge && apt-get clean
-
 
 # 启动
 CMD ["python3", "-u", "main.py"]

docs/WindowsRun.bat

@@ -1,26 +0,0 @@
-@echo off
-setlocal
-
-:: 设置环境变量
-set ENV_NAME=gpt
-set ENV_PATH=%~dp0%ENV_NAME%
-set SCRIPT_PATH=%~dp0main.py
-
-:: 判断环境是否已解压
-if not exist "%ENV_PATH%" (
-    echo Extracting environment...
-    mkdir "%ENV_PATH%"
-    tar -xzf gpt.tar.gz -C "%ENV_PATH%"
-    
-    :: 运行conda环境激活脚本
-    call "%ENV_PATH%\Scripts\activate.bat"
-) else (
-    :: 如果环境已存在,直接激活
-    call "%ENV_PATH%\Scripts\activate.bat"
-)
-echo Start to run program:
-:: 运行Python脚本
-python "%SCRIPT_PATH%"
-
-endlocal
-pause

docs/translate_english.json

@@ -1141,7 +1141,7 @@
     "内容太长了都会触发token数量溢出的错误": "An error of token overflow will be triggered if the content is too long",
     "chatbot 为WebUI中显示的对话列表": "chatbot is the conversation list displayed in WebUI",
     "修改它": "Modify it",
-    "然后yield出去": "Then yield it out",
+    "然后yeild出去": "Then yield it out",
     "可以直接修改对话界面内容": "You can directly modify the conversation interface content",
     "additional_fn代表点击的哪个按钮": "additional_fn represents which button is clicked",
     "按钮见functional.py": "See functional.py for buttons",
@@ -1732,7 +1732,7 @@
     "或者重启之后再度尝试": "Or try again after restarting",
     "免费": "Free",
     "仅在Windows系统进行了测试": "Tested only on Windows system",
-    "欢迎加README中的QQ联系开发者": "Feel free to contact the developer via QQ in README",
+    "欢迎加REAME中的QQ联系开发者": "Feel free to contact the developer via QQ in REAME",
     "当前知识库内的有效文件": "Valid files in the current knowledge base",
     "您可以到Github Issue区": "You can go to the Github Issue area",
     "刷新Gradio前端界面": "Refresh the Gradio frontend interface",
@@ -1759,7 +1759,7 @@
     "报错信息如下. 如果是与网络相关的问题": "Error message as follows. If it is related to network issues",
     "功能描述": "Function description",
     "禁止移除或修改此警告": "Removal or modification of this warning is prohibited",
-    "ArXiv翻译": "ArXiv translation",
+    "Arixv翻译": "Arixv translation",
     "读取优先级": "Read priority",
     "包含documentclass关键字": "Contains the documentclass keyword",
     "根据文本使用GPT模型生成相应的图像": "Generate corresponding images using GPT model based on the text",
@@ -1998,7 +1998,7 @@
     "开始最终总结": "Start final summary",
     "openai的官方KEY需要伴随组织编码": "Openai's official KEY needs to be accompanied by organizational code",
     "将子线程的gpt结果写入chatbot": "Write the GPT result of the sub-thread into the chatbot",
-    "ArXiv论文精细翻译": "Fine translation of ArXiv paper",
+    "Arixv论文精细翻译": "Fine translation of Arixv paper",
     "开始接收chatglmft的回复": "Start receiving replies from chatglmft",
     "请先将.doc文档转换为.docx文档": "Please convert .doc documents to .docx documents first",
     "避免多用户干扰": "Avoid multiple user interference",
@@ -2360,7 +2360,7 @@
     "请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件": "Please set ALLOW_RESET_CONFIG=True in config.py and restart the software",
     "按照自然语言描述生成一个动画 | 输入参数是一段话": "Generate an animation based on natural language description | Input parameter is a sentence",
     "你的hf用户名如qingxu98": "Your hf username is qingxu98",
-    "ArXiv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of ArXiv paper | Input parameter is the ID of arxiv paper",
+    "Arixv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of Arixv paper | Input parameter is the ID of arxiv paper",
     "无法获取 abstract": "Unable to retrieve abstract",
     "尽可能地仅用一行命令解决我的要求": "Try to solve my request using only one command",
     "提取插件参数": "Extract plugin parameters",

docs/translate_japanese.json

@@ -753,7 +753,7 @@
     "手动指定和筛选源代码文件类型": "ソースコードファイルタイプを手動で指定およびフィルタリングする",
     "更多函数插件": "その他の関数プラグイン",
     "看门狗的耐心": "監視犬の忍耐力",
-    "然后yield出去": "そして出力する",
+    "然后yeild出去": "そして出力する",
     "拆分过长的IPynb文件": "長すぎるIPynbファイルを分割する",
     "1. 把input的余量留出来": "1. 入力の余裕を残す",
     "请求超时": "リクエストがタイムアウトしました",
@@ -1803,7 +1803,7 @@
     "默认值为1000": "デフォルト値は1000です",
     "写出文件": "ファイルに書き出す",
     "生成的视频文件路径": "生成されたビデオファイルのパス",
-    "ArXiv论文精细翻译": "ArXiv論文の詳細な翻訳",
+    "Arixv论文精细翻译": "Arixv論文の詳細な翻訳",
     "用latex编译为PDF对修正处做高亮": "LaTeXでコンパイルしてPDFに修正をハイライトする",
     "点击“停止”键可终止程序": "「停止」ボタンをクリックしてプログラムを終了できます",
     "否则将导致每个人的Claude问询历史互相渗透": "さもないと、各人のClaudeの問い合わせ履歴が相互に侵入します",
@@ -1987,7 +1987,7 @@
     "前面是中文逗号": "前面是中文逗号",
     "的依赖": "的依赖",
     "材料如下": "材料如下",
-    "欢迎加README中的QQ联系开发者": "欢迎加README中的QQ联系开发者",
+    "欢迎加REAME中的QQ联系开发者": "欢迎加REAME中的QQ联系开发者",
     "开始下载": "開始ダウンロード",
     "100字以内": "100文字以内",
     "创建request": "リクエストの作成",

docs/translate_traditionalchinese.json

@@ -771,7 +771,7 @@
     "查询代理的地理位置": "查詢代理的地理位置",
     "是否在输入过长时": "是否在輸入過長時",
     "chatGPT分析报告": "chatGPT分析報告",
-    "然后yield出去": "然後yield出去",
+    "然后yeild出去": "然後yield出去",
     "用户取消了程序": "使用者取消了程式",
     "琥珀色": "琥珀色",
     "这里是特殊函数插件的高级参数输入区": "這裡是特殊函數插件的高級參數輸入區",
@@ -1587,7 +1587,7 @@
     "否则将导致每个人的Claude问询历史互相渗透": "否則將導致每個人的Claude問詢歷史互相滲透",
     "提问吧! 但注意": "提問吧！但注意",
     "待处理的word文档路径": "待處理的word文檔路徑",
-    "欢迎加README中的QQ联系开发者": "歡迎加README中的QQ聯繫開發者",
+    "欢迎加REAME中的QQ联系开发者": "歡迎加REAME中的QQ聯繫開發者",
     "建议暂时不要使用": "建議暫時不要使用",
     "Latex没有安装": "Latex沒有安裝",
     "在这里放一些网上搜集的demo": "在這裡放一些網上搜集的demo",
@@ -1989,7 +1989,7 @@
     "请耐心等待": "請耐心等待",
     "在执行完成之后": "在執行完成之後",
     "参数简单": "參數簡單",
-    "ArXiv论文精细翻译": "ArXiv論文精細翻譯",
+    "Arixv论文精细翻译": "Arixv論文精細翻譯",
     "备份和下载": "備份和下載",
     "当前报错的latex代码处于第": "當前報錯的latex代碼處於第",
     "Markdown翻译": "Markdown翻譯",

main.py

@@ -1,7 +1,10 @@
-import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
+import os, json; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
 
 help_menu_description = \
-"""
+"""Github源代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic),
+感谢热情的[开发者们❤️](https://github.com/binary-husky/gpt_academic/graphs/contributors).
+</br></br>常见问题请查阅[项目Wiki](https://github.com/binary-husky/gpt_academic/wiki),
+如遇到Bug请前往[Bug反馈](https://github.com/binary-husky/gpt_academic/issues).
 </br></br>普通对话使用说明: 1. 输入问题; 2. 点击提交
 </br></br>基础功能区使用说明: 1. 输入文本; 2. 点击任意基础功能区按钮
 </br></br>函数插件区使用说明: 1. 输入路径/问题, 或者上传文件; 2. 点击任意函数插件区按钮
@@ -31,9 +34,9 @@ def encode_plugin_info(k, plugin)->str:
 
 def main():
     import gradio as gr
-    if gr.__version__ not in ['3.32.15']:
+    if gr.__version__ not in ['3.32.9', '3.32.10', '3.32.11']:
         raise ModuleNotFoundError("使用项目内置Gradio获取最优体验! 请运行 `pip install -r requirements.txt` 指令安装内置Gradio及其他依赖, 详情信息见requirements.txt.")
-
+    
     # 一些基础工具
     from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
 
@@ -46,7 +49,7 @@ def main():
     # 读取配置
     proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION = get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION')
     CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = get_conf('CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
-    ENABLE_AUDIO, AUTO_CLEAR_TXT, AVAIL_FONTS, AVAIL_THEMES, THEME, ADD_WAIFU = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'AVAIL_FONTS', 'AVAIL_THEMES', 'THEME', 'ADD_WAIFU')
+    ENABLE_AUDIO, AUTO_CLEAR_TXT, PATH_LOGGING, AVAIL_THEMES, THEME, ADD_WAIFU = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING', 'AVAIL_THEMES', 'THEME', 'ADD_WAIFU')
     NUM_CUSTOM_BASIC_BTN, SSL_KEYFILE, SSL_CERTFILE = get_conf('NUM_CUSTOM_BASIC_BTN', 'SSL_KEYFILE', 'SSL_CERTFILE')
     DARK_MODE, INIT_SYS_PROMPT, ADD_WAIFU, TTS_TYPE = get_conf('DARK_MODE', 'INIT_SYS_PROMPT', 'ADD_WAIFU', 'TTS_TYPE')
     if LLM_MODEL not in AVAIL_LLM_MODELS: AVAIL_LLM_MODELS += [LLM_MODEL]
@@ -54,8 +57,8 @@ def main():
     # 如果WEB_PORT是-1, 则随机选取WEB端口
     PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
     from check_proxy import get_current_version
-    from themes.theme import adjust_theme, advanced_css, theme_declaration, js_code_clear, js_code_show_or_hide
+    from themes.theme import adjust_theme, advanced_css, theme_declaration, js_code_clear, js_code_reset, js_code_show_or_hide, js_code_show_or_hide_group2
-    from themes.theme import js_code_for_toggle_darkmode
+    from themes.theme import js_code_for_toggle_darkmode, js_code_for_persistent_cookie_init
     from themes.theme import load_dynamic_theme, to_cookie_str, from_cookie_str, assign_user_uuid
     title_html = f"<h1 align=\"center\">GPT 学术优化 {get_current_version()}</h1>{theme_declaration}"
 
@@ -65,7 +68,7 @@ def main():
     functional = get_core_functions()
 
     # 高级函数插件
-    from crazy_functional import get_crazy_functions, get_multiplex_button_functions
+    from crazy_functional import get_crazy_functions
     DEFAULT_FN_GROUPS = get_conf('DEFAULT_FN_GROUPS')
     plugins = get_crazy_functions()
     all_plugin_groups = list(set([g for _, plugin in plugins.items() for g in plugin['Group'].split('|')]))
@@ -103,7 +106,7 @@ def main():
             with gr_L2(scale=2, elem_id="gpt-chat"):
                 chatbot = gr.Chatbot(label=f"当前模型：{LLM_MODEL}", elem_id="gpt-chatbot")
                 if LAYOUT == "TOP-DOWN":  chatbot.style(height=CHATBOT_HEIGHT)
-                history, _, _ = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
+                history, history_cache, history_cache_update = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
             with gr_L2(scale=1, elem_id="gpt-panel"):
                 with gr.Accordion("输入区", open=True, elem_id="input-panel") as area_input_primary:
                     with gr.Row():
@@ -111,7 +114,12 @@ def main():
                     with gr.Row(elem_id="gpt-submit-row"):
                         multiplex_submit_btn = gr.Button("提交", elem_id="elem_submit_visible", variant="primary")
                         multiplex_sel = gr.Dropdown(
-                            choices=get_multiplex_button_functions().keys(), value="常规对话",
+                            choices=[
+                                "常规对话", 
+                                "多模型对话", 
+                                "智能召回 RAG",
+                                # "智能上下文", 
+                            ], value="常规对话",
                             interactive=True, label='', show_label=False,
                             elem_classes='normal_mut_select', elem_id="gpt-submit-dropdown").style(container=False)
                         submit_btn = gr.Button("提交", elem_id="elem_submit", variant="primary", visible=False)
@@ -171,20 +179,16 @@ def main():
                         with gr.Accordion("点击展开“文件下载区”。", open=False) as area_file_up:
                             file_upload = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple", elem_id="elem_upload")
 
-
         # 左上角工具栏定义
         from themes.gui_toolbar import define_gui_toolbar
         checkboxes, checkboxes_2, max_length_sl, theme_dropdown, system_prompt, file_upload_2, md_dropdown, top_p, temperature = \
-            define_gui_toolbar(AVAIL_LLM_MODELS, LLM_MODEL, INIT_SYS_PROMPT, THEME, AVAIL_THEMES, AVAIL_FONTS, ADD_WAIFU, help_menu_description, js_code_for_toggle_darkmode)
+            define_gui_toolbar(AVAIL_LLM_MODELS, LLM_MODEL, INIT_SYS_PROMPT, THEME, AVAIL_THEMES, ADD_WAIFU, help_menu_description, js_code_for_toggle_darkmode)
 
         # 浮动菜单定义
         from themes.gui_floating_menu import define_gui_floating_menu
         area_input_secondary, txt2, area_customize, _, resetBtn2, clearBtn2, stopBtn2 = \
             define_gui_floating_menu(customize_btns, functional, predefined_btns, cookies, web_cookie_cache)
 
-        # 浮动时间线定义
-        gr.Spark()
-
         # 插件二级菜单的实现
         from themes.gui_advanced_plugin_class import define_gui_advanced_plugin_class
         new_plugin_callback, route_switchy_bt_with_arg, usr_confirmed_arg = \
@@ -207,14 +211,14 @@ def main():
             ret.update({area_customize: gr.update(visible=("自定义菜单" in a))})
             return ret
         checkboxes_2.select(fn_area_visibility_2, [checkboxes_2], [area_customize] )
-        checkboxes_2.select(None, [checkboxes_2], None, _js="""apply_checkbox_change_for_group2""")
+        checkboxes_2.select(None, [checkboxes_2], None, _js=js_code_show_or_hide_group2)
 
         # 整理反复出现的控件句柄组合
         input_combo = [cookies, max_length_sl, md_dropdown, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg]
         input_combo_order = ["cookies", "max_length_sl", "md_dropdown", "txt", "txt2", "top_p", "temperature", "chatbot", "history", "system_prompt", "plugin_advanced_arg"]
         output_combo = [cookies, chatbot, history, status]
         predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True)], outputs=output_combo)
-
+        
         # 提交按钮、重置按钮
         multiplex_submit_btn.click(
             None, [multiplex_sel], None, _js="""(multiplex_sel)=>multiplex_function_begin(multiplex_sel)""")
@@ -223,8 +227,11 @@ def main():
         multiplex_sel.select(
             None, [multiplex_sel], None, _js=f"""(multiplex_sel)=>run_multiplex_shift(multiplex_sel)""")
         cancel_handles.append(submit_btn.click(**predict_args))
-        resetBtn.click(None, None, [chatbot, history, status], _js= """clear_conversation""")   # 先在前端快速清除chatbot&status
+        resetBtn.click(None, None, [chatbot, history, status], _js=js_code_reset)   # 先在前端快速清除chatbot&status
-        resetBtn2.click(None, None, [chatbot, history, status], _js="""clear_conversation""")  # 先在前端快速清除chatbot&status
+        resetBtn2.click(None, None, [chatbot, history, status], _js=js_code_reset)  # 先在前端快速清除chatbot&status
+        reset_server_side_args = (lambda history: ([], [], "已重置", json.dumps(history)), [history], [chatbot, history, status, history_cache])
+        resetBtn.click(*reset_server_side_args)    # 再在后端清除history，把history转存history_cache备用
+        resetBtn2.click(*reset_server_side_args)   # 再在后端清除history，把history转存history_cache备用
         clearBtn.click(None, None, [txt, txt2], _js=js_code_clear)
         clearBtn2.click(None, None, [txt, txt2], _js=js_code_clear)
         if AUTO_CLEAR_TXT:
@@ -324,7 +331,7 @@ def main():
         from shared_utils.cookie_manager import load_web_cookie_cache__fn_builder
         load_web_cookie_cache = load_web_cookie_cache__fn_builder(customize_btns, cookies, predefined_btns)
         app_block.load(load_web_cookie_cache, inputs = [web_cookie_cache, cookies],
-            outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js="""persistent_cookie_init""")
+            outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js=js_code_for_persistent_cookie_init)
         app_block.load(None, inputs=[], outputs=None, _js=f"""()=>GptAcademicJavaScriptInit("{DARK_MODE}","{INIT_SYS_PROMPT}","{ADD_WAIFU}","{LAYOUT}","{TTS_TYPE}")""")    # 配置暗色主题或亮色主题
         app_block.load(None, inputs=[], outputs=None, _js="""()=>{REP}""".replace("REP", register_advanced_plugin_init_arr))
 

request_llms/bridge_all.py

@@ -26,9 +26,6 @@ from .bridge_chatglm import predict as chatglm_ui
 from .bridge_chatglm3 import predict_no_ui_long_connection as chatglm3_noui
 from .bridge_chatglm3 import predict as chatglm3_ui
 
-from .bridge_chatglm4 import predict_no_ui_long_connection as chatglm4_noui
-from .bridge_chatglm4 import predict as chatglm4_ui
-
 from .bridge_qianfan import predict_no_ui_long_connection as qianfan_noui
 from .bridge_qianfan import predict as qianfan_ui
 
@@ -79,8 +76,6 @@ cohere_endpoint = "https://api.cohere.ai/v1/chat"
 ollama_endpoint = "http://localhost:11434/api/chat"
 yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions"
 deepseekapi_endpoint = "https://api.deepseek.com/v1/chat/completions"
-grok_model_endpoint = "https://api.x.ai/v1/chat/completions"
-volcengine_endpoint = "https://ark.cn-beijing.volces.com/api/v3/chat/completions"
 
 if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
 azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
@@ -102,8 +97,6 @@ if cohere_endpoint in API_URL_REDIRECT: cohere_endpoint = API_URL_REDIRECT[coher
 if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollama_endpoint]
 if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint]
 if deepseekapi_endpoint in API_URL_REDIRECT: deepseekapi_endpoint = API_URL_REDIRECT[deepseekapi_endpoint]
-if grok_model_endpoint in API_URL_REDIRECT: grok_model_endpoint = API_URL_REDIRECT[grok_model_endpoint]
-if volcengine_endpoint in API_URL_REDIRECT: volcengine_endpoint = API_URL_REDIRECT[volcengine_endpoint]
 
 # 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
@@ -219,16 +212,6 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
-    "chatgpt-4o-latest": {
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "endpoint": openai_endpoint,
-        "has_multimodal_capacity": True,
-        "max_token": 128000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
-    },
-
     "gpt-4o-2024-05-13": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
@@ -275,88 +258,16 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
         "openai_disable_system_prompt": True,
         "openai_disable_stream": True,
-        "openai_force_temperature_one": True,
     },
-
     "o1-mini": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
         "endpoint": openai_endpoint,
-        "can_multi_thread": True,
         "max_token": 128000,
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
         "openai_disable_system_prompt": True,
         "openai_disable_stream": True,
-        "openai_force_temperature_one": True,
-    },
-
-    "o1-2024-12-17": {
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "endpoint": openai_endpoint,
-        "max_token": 200000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
-        "openai_disable_system_prompt": True,
-        "openai_disable_stream": True,
-        "openai_force_temperature_one": True,
-    },
-
-    "o1": {
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "endpoint": openai_endpoint,
-        "max_token": 200000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
-        "openai_disable_system_prompt": True,
-        "openai_disable_stream": True,
-        "openai_force_temperature_one": True,
-    },
-
-    "gpt-4.1":{
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "has_multimodal_capacity": True,
-        "endpoint": openai_endpoint,
-        "max_token": 828000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
-    },
-
-    "gpt-4.1-mini":{
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "has_multimodal_capacity": True,
-        "endpoint": openai_endpoint,
-        "max_token": 828000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
-    },
-
-    "o3":{
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "has_multimodal_capacity": True,
-        "endpoint": openai_endpoint,
-        "max_token": 828000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
-        "openai_disable_system_prompt": True,
-        "openai_disable_stream": True,
-        "openai_force_temperature_one": True,
-    },
-
-    "o4-mini":{
-        "fn_with_ui": chatgpt_ui,
-        "fn_without_ui": chatgpt_noui,
-        "has_multimodal_capacity": True,
-        "can_multi_thread": True,
-        "endpoint": openai_endpoint,
-        "max_token": 828000,
-        "tokenizer": tokenizer_gpt4,
-        "token_cnt": get_token_num_gpt4,
     },
 
     "gpt-4-turbo": {
@@ -474,14 +385,6 @@ 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": {
@@ -493,7 +396,6 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
-    # ChatGLM本地模型
     # 将 chatglm 直接对齐到 chatglm2
     "chatglm": {
         "fn_with_ui": chatglm_ui,
@@ -519,14 +421,6 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
-    "chatglm4": {
-        "fn_with_ui": chatglm4_ui,
-        "fn_without_ui": chatglm4_noui,
-        "endpoint": None,
-        "max_token": 8192,
-        "tokenizer": tokenizer_gpt35,
-        "token_cnt": get_token_num_gpt35,
-    },
     "qianfan": {
         "fn_with_ui": qianfan_ui,
         "fn_without_ui": qianfan_noui,
@@ -575,15 +469,6 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
-    "gemini-2.0-flash": {
-        "fn_with_ui": genai_ui,
-        "fn_without_ui": genai_noui,
-        "endpoint": gemini_endpoint,
-        "has_multimodal_capacity": True,
-        "max_token": 1024 * 204800,
-        "tokenizer": tokenizer_gpt35,
-        "token_cnt": get_token_num_gpt35,
-    },
 
     # cohere
     "cohere-command-r-plus": {
@@ -867,13 +752,8 @@ if "qwen-local" in AVAIL_LLM_MODELS:
         })
     except:
         logger.error(trimmed_format_exc())
-
+# -=-=-=-=-=-=- 通义-在线模型 -=-=-=-=-=-=-
-# -=-=-=-=-=-=- 阿里云百炼（通义）-在线模型 -=-=-=-=-=-=-
+if "qwen-turbo" in AVAIL_LLM_MODELS or "qwen-plus" in AVAIL_LLM_MODELS or "qwen-max" in AVAIL_LLM_MODELS:   # zhipuai
-qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus",
-               "dashscope-deepseek-r1","dashscope-deepseek-v3",
-               "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-qwen3-32b",
-               ]
-if any(item in qwen_models for item in AVAIL_LLM_MODELS):
     try:
         from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
         from .bridge_qwen import predict as qwen_ui
@@ -883,7 +763,7 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
                 "fn_without_ui": qwen_noui,
                 "can_multi_thread": True,
                 "endpoint": None,
-                "max_token": 100000,
+                "max_token": 6144,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
@@ -892,7 +772,7 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
                 "fn_without_ui": qwen_noui,
                 "can_multi_thread": True,
                 "endpoint": None,
-                "max_token": 129024,
+                "max_token": 30720,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
@@ -901,79 +781,13 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
                 "fn_without_ui": qwen_noui,
                 "can_multi_thread": True,
                 "endpoint": None,
-                "max_token": 30720,
+                "max_token": 28672,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "qwen-max-latest": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 30720,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "qwen-max-2025-01-25": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 30720,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "dashscope-deepseek-r1": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "enable_reasoning": True,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 57344,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "dashscope-deepseek-v3": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 57344,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "dashscope-qwen3-14b": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "enable_reasoning": True,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 129024,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "dashscope-qwen3-235b-a22b": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 129024,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            "dashscope-qwen3-32b": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
-                "can_multi_thread": True,
-                "endpoint": None,
-                "max_token": 129024,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             }
         })
     except:
         logger.error(trimmed_format_exc())
-
 # -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
 yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
 if any(item in yi_models for item in AVAIL_LLM_MODELS):
@@ -1054,31 +868,6 @@ if any(item in yi_models for item in AVAIL_LLM_MODELS):
         })
     except:
         logger.error(trimmed_format_exc())
-
-
-# -=-=-=-=-=-=- Grok model from x.ai -=-=-=-=-=-=-
-grok_models = ["grok-beta"]
-if any(item in grok_models for item in AVAIL_LLM_MODELS):
-    try:
-        grok_beta_128k_noui, grok_beta_128k_ui = get_predict_function(
-            api_key_conf_name="GROK_API_KEY", max_output_token=8192, disable_proxy=False
-        )
-        
-        model_info.update({
-            "grok-beta": {
-                "fn_with_ui": grok_beta_128k_ui,
-                "fn_without_ui": grok_beta_128k_noui,
-                "can_multi_thread": True,  
-                "endpoint": grok_model_endpoint,
-                "max_token": 128000,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-            },
-            
-        })
-    except:
-        logger.error(trimmed_format_exc())
-
 # -=-=-=-=-=-=- 讯飞星火认知大模型 -=-=-=-=-=-=-
 if "spark" in AVAIL_LLM_MODELS:
     try:
@@ -1180,7 +969,7 @@ if "zhipuai" in AVAIL_LLM_MODELS:   # zhipuai 是glm-4的别名，向后兼容
         })
     except:
         logger.error(trimmed_format_exc())
-# -=-=-=-=-=-=- 幻方-深度求索本地大模型 -=-=-=-=-=-=-
+# -=-=-=-=-=-=- 幻方-深度求索大模型 -=-=-=-=-=-=-
 if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
     try:
         from .bridge_deepseekcoder import predict_no_ui_long_connection as deepseekcoder_noui
@@ -1197,21 +986,19 @@ if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
         })
     except:
         logger.error(trimmed_format_exc())
-
 # -=-=-=-=-=-=- 幻方-深度求索大模型在线API -=-=-=-=-=-=-
-claude_models = ["deepseek-chat", "deepseek-coder", "deepseek-reasoner"]
+if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS:
-if any(item in claude_models for item in AVAIL_LLM_MODELS):
     try:
         deepseekapi_noui, deepseekapi_ui = get_predict_function(
             api_key_conf_name="DEEPSEEK_API_KEY", max_output_token=4096, disable_proxy=False
-        )
+            )
         model_info.update({
             "deepseek-chat":{
                 "fn_with_ui": deepseekapi_ui,
                 "fn_without_ui": deepseekapi_noui,
                 "endpoint": deepseekapi_endpoint,
                 "can_multi_thread": True,
-                "max_token": 64000,
+                "max_token": 32000,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
@@ -1224,73 +1011,9 @@ if any(item in claude_models for item in AVAIL_LLM_MODELS):
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
-            "deepseek-reasoner":{
-                "fn_with_ui": deepseekapi_ui,
-                "fn_without_ui": deepseekapi_noui,
-                "endpoint": deepseekapi_endpoint,
-                "can_multi_thread": True,
-                "max_token": 64000,
-                "tokenizer": tokenizer_gpt35,
-                "token_cnt": get_token_num_gpt35,
-                "enable_reasoning": True
-            },
         })
     except:
         logger.error(trimmed_format_exc())
-
-# -=-=-=-=-=-=- 火山引擎 对齐支持 -=-=-=-=-=-=-
-for model in [m for m in AVAIL_LLM_MODELS if m.startswith("volcengine-")]:
-    # 为了更灵活地接入volcengine多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["volcengine-deepseek-r1-250120(max_token=6666)"]
-    # 其中
-    #   "volcengine-"          是前缀（必要）
-    #   "deepseek-r1-250120"   是模型名（必要）
-    #   "(max_token=6666)"     是配置（非必要）
-    model_info_extend = model_info
-    model_info_extend.update({
-        "deepseek-r1-250120": {
-            "max_token": 16384,
-            "enable_reasoning": True,
-            "can_multi_thread": True,
-            "endpoint": volcengine_endpoint,
-            "tokenizer": tokenizer_gpt35,
-            "token_cnt": get_token_num_gpt35,
-        },
-        "deepseek-v3-241226": {
-            "max_token": 16384,
-            "enable_reasoning": False,
-            "can_multi_thread": True,
-            "endpoint": volcengine_endpoint,
-            "tokenizer": tokenizer_gpt35,
-            "token_cnt": get_token_num_gpt35,
-        },
-    })
-    try:
-        origin_model_name, max_token_tmp = read_one_api_model_name(model)
-        # 如果是已知模型，则尝试获取其信息
-        original_model_info = model_info_extend.get(origin_model_name.replace("volcengine-", "", 1), None)
-    except:
-        logger.error(f"volcengine模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
-        continue
-
-    volcengine_noui, volcengine_ui = get_predict_function(api_key_conf_name="ARK_API_KEY", max_output_token=8192, disable_proxy=True, model_remove_prefix = ["volcengine-"])
-
-    this_model_info = {
-        "fn_with_ui": volcengine_ui,
-        "fn_without_ui": volcengine_noui,
-        "endpoint": volcengine_endpoint,
-        "can_multi_thread": True,
-        "max_token": 64000,
-        "tokenizer": tokenizer_gpt35,
-        "token_cnt": get_token_num_gpt35,
-    }
-
-    # 同步已知模型的其他信息
-    attribute = "has_multimodal_capacity"
-    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
-    attribute = "enable_reasoning"
-    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
-    model_info.update({model: this_model_info})
-
 # -=-=-=-=-=-=- one-api 对齐支持 -=-=-=-=-=-=-
 for model in [m for m in AVAIL_LLM_MODELS if m.startswith("one-api-")]:
     # 为了更灵活地接入one-api多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["one-api-mixtral-8x7b(max_token=6666)"]
@@ -1429,9 +1152,9 @@ def LLM_CATCH_EXCEPTION(f):
     """
     装饰器函数，将错误显示出来
     """
-    def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_silence:bool):
+    def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_slience:bool):
         try:
-            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
+            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
         except Exception as e:
             tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
             observe_window[0] = tb_str
@@ -1439,7 +1162,7 @@ def LLM_CATCH_EXCEPTION(f):
     return decorated
 
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_silence:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_slience:bool=False):
     """
     发送至LLM，等待回复，一次性完成，不显示中间过程。但内部（尽可能地）用stream的方法避免中途网线被掐。
     inputs：
@@ -1461,7 +1184,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
     if '&' not in model:
         # 如果只询问“一个”大语言模型（多数情况）：
         method = model_info[model]["fn_without_ui"]
-        return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
+        return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
     else:
         # 如果同时询问“多个”大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
         executor = ThreadPoolExecutor(max_workers=4)
@@ -1478,7 +1201,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
             method = model_info[model]["fn_without_ui"]
             llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
             llm_kwargs_feedin['llm_model'] = model
-            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_silence)
+            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_slience)
             futures.append(future)
 
         def mutex_manager(window_mutex, observe_window):
@@ -1555,11 +1278,6 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
 
     inputs = apply_gpt_academic_string_mask(inputs, mode="show_llm")
 
-    if llm_kwargs['llm_model'] not in model_info:
-        from toolbox import update_ui
-        chatbot.append([inputs, f"很抱歉，模型 '{llm_kwargs['llm_model']}' 暂不支持<br/>(1) 检查config中的AVAIL_LLM_MODELS选项<br/>(2) 检查request_llms/bridge_all.py中的模型路由"])
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
     method = model_info[llm_kwargs['llm_model']]["fn_with_ui"]  # 如果这里报错，检查config中的AVAIL_LLM_MODELS选项
 
     if additional_fn: # 根据基础功能区 ModelOverride 参数调整模型类型

request_llms/bridge_chatglm3.py

@@ -23,33 +23,39 @@ class GetGLM3Handle(LocalLLMHandle):
         import os
         import platform
 
-        LOCAL_MODEL_PATH, LOCAL_MODEL_QUANT, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE")
+        LOCAL_MODEL_QUANT, device = get_conf("LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE")
-        model_path = LOCAL_MODEL_PATH
+        _model_name_ = "THUDM/chatglm3-6b"
+        # if LOCAL_MODEL_QUANT == "INT4":  # INT4
+        #     _model_name_ = "THUDM/chatglm3-6b-int4"
+        # elif LOCAL_MODEL_QUANT == "INT8":  # INT8
+        #     _model_name_ = "THUDM/chatglm3-6b-int8"
+        # else:
+        #     _model_name_ = "THUDM/chatglm3-6b"  # FP16
         with ProxyNetworkActivate("Download_LLM"):
             chatglm_tokenizer = AutoTokenizer.from_pretrained(
-                model_path, trust_remote_code=True
+                _model_name_, trust_remote_code=True
             )
             if device == "cpu":
                 chatglm_model = AutoModel.from_pretrained(
-                    model_path,
+                    _model_name_,
                     trust_remote_code=True,
                     device="cpu",
                 ).float()
             elif LOCAL_MODEL_QUANT == "INT4":  # INT4
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=model_path,
+                    pretrained_model_name_or_path=_model_name_,
                     trust_remote_code=True,
                     quantization_config=BitsAndBytesConfig(load_in_4bit=True),
                 )
             elif LOCAL_MODEL_QUANT == "INT8":  # INT8
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=model_path,
+                    pretrained_model_name_or_path=_model_name_,
                     trust_remote_code=True,
                     quantization_config=BitsAndBytesConfig(load_in_8bit=True),
                 )
             else:
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=model_path,
+                    pretrained_model_name_or_path=_model_name_,
                     trust_remote_code=True,
                     device="cuda",
                 )

request_llms/bridge_chatglm4.py

@@ -1,81 +0,0 @@
-model_name = "ChatGLM4"
-cmd_to_install = """
-`pip install -r request_llms/requirements_chatglm4.txt`
-`pip install modelscope`
-`modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat`
-"""
-
-
-from toolbox import get_conf, ProxyNetworkActivate
-from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
-
-
-# ------------------------------------------------------------------------------------------------------------------------
-# 🔌💻 Local Model
-# ------------------------------------------------------------------------------------------------------------------------
-class GetGLM4Handle(LocalLLMHandle):
-
-    def load_model_info(self):
-        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
-        self.model_name = model_name
-        self.cmd_to_install = cmd_to_install
-
-    def load_model_and_tokenizer(self):
-        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
-        import torch
-        from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer
-        import os
-
-        LOCAL_MODEL_PATH, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_DEVICE")
-        model_path = LOCAL_MODEL_PATH
-        chatglm_tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
-        chatglm_model = AutoModelForCausalLM.from_pretrained(
-            model_path,
-            torch_dtype=torch.bfloat16,
-            low_cpu_mem_usage=True,
-            trust_remote_code=True,
-            device=device
-        ).eval().to(device)
-        self._model = chatglm_model
-        self._tokenizer = chatglm_tokenizer
-        return self._model, self._tokenizer
-
-
-    def llm_stream_generator(self, **kwargs):
-        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
-        def adaptor(kwargs):
-            query = kwargs["query"]
-            max_length = kwargs["max_length"]
-            top_p = kwargs["top_p"]
-            temperature = kwargs["temperature"]
-            history = kwargs["history"]
-            return query, max_length, top_p, temperature, history
-
-        query, max_length, top_p, temperature, history = adaptor(kwargs)
-        inputs = self._tokenizer.apply_chat_template([{"role": "user", "content": query}],
-                                       add_generation_prompt=True,
-                                       tokenize=True,
-                                       return_tensors="pt",
-                                       return_dict=True
-                                       ).to(self._model.device)
-        gen_kwargs = {"max_length": max_length, "do_sample": True, "top_k": top_p}
-
-        outputs = self._model.generate(**inputs, **gen_kwargs)
-        outputs = outputs[:, inputs['input_ids'].shape[1]:]
-        response = self._tokenizer.decode(outputs[0], skip_special_tokens=True)
-        yield response
-
-    def try_to_import_special_deps(self, **kwargs):
-        # import something that will raise error if the user does not install requirement_*.txt
-        # 🏃‍♂️🏃‍♂️🏃‍♂️ 主进程执行
-        import importlib
-
-        # importlib.import_module('modelscope')
-
-
-# ------------------------------------------------------------------------------------------------------------------------
-# 🔌💻 GPT-Academic Interface
-# ------------------------------------------------------------------------------------------------------------------------
-predict_no_ui_long_connection, predict = get_local_llm_predict_fns(
-    GetGLM4Handle, model_name, history_format="chatglm3"
-)

request_llms/bridge_chatglmft.py

@@ -139,7 +139,7 @@ global glmft_handle
 glmft_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_silence:bool=False):
+                                  observe_window:list=[], console_slience:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_chatgpt.py

@@ -23,13 +23,8 @@ from loguru import logger
 from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history
 from toolbox import trimmed_format_exc, is_the_upload_folder, read_one_api_model_name, log_chat
 from toolbox import ChatBotWithCookies, have_any_recent_upload_image_files, encode_image
-proxies, WHEN_TO_USE_PROXY, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
+proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
-    get_conf('proxies', 'WHEN_TO_USE_PROXY', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG', 'AZURE_CFG_ARRAY')
+    get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG', 'AZURE_CFG_ARRAY')
-
-if "Connect_OpenAI" not in WHEN_TO_USE_PROXY:
-    if proxies is not None:
-        logger.error("虽然您配置了代理设置，但不会在连接OpenAI的过程中起作用，请检查WHEN_TO_USE_PROXY配置。")
-        proxies = None
 
 timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
                   '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
@@ -125,7 +120,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
     """
     发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -185,25 +180,19 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
                 raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。")
             else:
                 raise RuntimeError("OpenAI拒绝了请求：" + error_msg)
-        if ('data: [DONE]' in chunk_decoded): break # api2d & one-api 正常完成
+        if ('data: [DONE]' in chunk_decoded): break # api2d 正常完成
         # 提前读取一些信息 （用于判断异常）
         if has_choices and not choice_valid:
             # 一些垃圾第三方接口的出现这样的错误
             continue
         json_data = chunkjson['choices'][0]
         delta = json_data["delta"]
-
+        if len(delta) == 0: break
-        if len(delta) == 0:
-            is_termination_certain = False
-            if (has_choices) and (chunkjson['choices'][0].get('finish_reason', 'null') == 'stop'): is_termination_certain = True
-            if is_termination_certain: break
-            else: continue # 对于不符合规范的狗屎接口，这里需要继续
-
         if (not has_content) and has_role: continue
         if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口："+delta)
         if has_content: # has_role = True/False
             result += delta["content"]
-            if not console_silence: print(delta["content"], end='')
+            if not console_slience: print(delta["content"], end='')
             if observe_window is not None:
                 # 观测窗，把已经获取的数据显示出去
                 if len(observe_window) >= 1:
@@ -231,7 +220,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     from request_llms.bridge_all import model_info
@@ -296,8 +285,6 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
         history.extend([inputs, ""])
 
     retry = 0
-    previous_ui_reflesh_time = 0
-    ui_reflesh_min_interval = 0.0
     while True:
         try:
             # make a POST request to the API endpoint, stream=True
@@ -310,13 +297,13 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
             yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg) # 刷新界面
             if retry > MAX_RETRY: raise TimeoutError
 
+
     if not stream:
         # 该分支仅适用于不支持stream的o1模型，其他情形一律不适用
         yield from handle_o1_model_special(response, inputs, llm_kwargs, chatbot, history)
         return
 
     if stream:
-        reach_termination = False   # 处理一些 new-api 的奇葩异常
         gpt_replying_buffer = ""
         is_head_of_the_stream = True
         stream_response =  response.iter_lines()
@@ -329,14 +316,11 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                 error_msg = chunk_decoded
                 # 首先排除一个one-api没有done数据包的第三方Bug情形
                 if len(gpt_replying_buffer.strip()) > 0 and len(error_msg) == 0:
-                    yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的接口，建议选择更稳定的接口。")
+                    yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的非OpenAI官方接口，建议选择更稳定的接口。")
-                    if not reach_termination:
-                        reach_termination = True
-                        log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                     break
                 # 其他情况，直接返回报错
                 chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
-                yield from update_ui(chatbot=chatbot, history=history, msg="接口返回了错误:" + chunk.decode()) # 刷新界面
+                yield from update_ui(chatbot=chatbot, history=history, msg="非OpenAI官方接口返回了错误:" + chunk.decode()) # 刷新界面
                 return
 
             # 提前读取一些信息 （用于判断异常）
@@ -346,8 +330,6 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                 # 数据流的第一帧不携带content
                 is_head_of_the_stream = False; continue
 
-            if "error" in chunk_decoded: logger.error(f"接口返回了未知错误: {chunk_decoded}")
-
             if chunk:
                 try:
                     if has_choices and not choice_valid:
@@ -356,25 +338,14 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                     if ('data: [DONE]' not in chunk_decoded) and len(chunk_decoded) > 0 and (chunkjson is None):
                         # 传递进来一些奇怪的东西
                         raise ValueError(f'无法读取以下数据，请检查配置。\n\n{chunk_decoded}')
-                    # 前者是API2D & One-API的结束条件，后者是OPENAI的结束条件
+                    # 前者是API2D的结束条件，后者是OPENAI的结束条件
-                    one_api_terminate = ('data: [DONE]' in chunk_decoded)
+                    if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
-                    openai_terminate = (has_choices) and (len(chunkjson['choices'][0]["delta"]) == 0)
+                        # 判定为数据流的结束，gpt_replying_buffer也写完了
-                    if one_api_terminate or openai_terminate:
+                        log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
-                        is_termination_certain = False
+                        break
-                        if one_api_terminate: is_termination_certain = True # 抓取符合规范的结束条件
-                        elif (has_choices) and (chunkjson['choices'][0].get('finish_reason', 'null') == 'stop'): is_termination_certain = True # 抓取符合规范的结束条件
-                        if is_termination_certain:
-                            reach_termination = True
-                            log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
-                            break # 对于符合规范的接口，这里可以break
-                        else:
-                            continue # 对于不符合规范的接口，这里需要继续
-                    # 到这里，我们已经可以假定必须包含choice了
-                    try:
-                        status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
-                    except:
-                        logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
                     # 处理数据流的主体
+                    status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
+                    # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出
                     if has_content:
                         # 正常情况
                         gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
@@ -382,27 +353,22 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                         # 一些第三方接口的出现这样的错误，兼容一下吧
                         continue
                     else:
-                        # 至此已经超出了正常接口应该进入的范围，一些第三方接口会出现这样的错误
+                        # 至此已经超出了正常接口应该进入的范围，一些垃圾第三方接口会出现这样的错误
-                        if chunkjson['choices'][0]["delta"].get("content", None) is None:
+                        if chunkjson['choices'][0]["delta"]["content"] is None: continue # 一些垃圾第三方接口出现这样的错误，兼容一下吧
-                            logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
-                            continue
                         gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
 
                     history[-1] = gpt_replying_buffer
                     chatbot[-1] = (history[-2], history[-1])
-                    if time.time() - previous_ui_reflesh_time > ui_reflesh_min_interval:
+                    yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
-                        yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
-                        previous_ui_reflesh_time = time.time()
                 except Exception as e:
                     yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
                     chunk = get_full_error(chunk, stream_response)
                     chunk_decoded = chunk.decode()
                     error_msg = chunk_decoded
                     chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
-                    logger.error(error_msg)
                     yield from update_ui(chatbot=chatbot, history=history, msg="Json解析异常" + error_msg) # 刷新界面
+                    logger.error(error_msg)
                     return
-        yield from update_ui(chatbot=chatbot, history=history, msg="完成") # 刷新界面
         return  # return from stream-branch
 
 def handle_o1_model_special(response, inputs, llm_kwargs, chatbot, history):
@@ -570,8 +536,6 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st
         "n": 1,
         "stream": stream,
     }
-    openai_force_temperature_one = model_info[llm_kwargs['llm_model']].get('openai_force_temperature_one', False)
+
-    if openai_force_temperature_one:
-        payload.pop('temperature')
     return headers,payload
 

request_llms/bridge_chatgpt_vision.py

@@ -16,7 +16,7 @@ import base64
 import glob
 from loguru import logger
 from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder, \
-    update_ui_latest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
+    update_ui_lastest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
 
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
@@ -67,7 +67,7 @@ def verify_endpoint(endpoint):
     """
     return endpoint
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
     raise NotImplementedError
 
 
@@ -183,7 +183,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                     if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
                         # 判定为数据流的结束，gpt_replying_buffer也写完了
                         lastmsg = chatbot[-1][-1] + f"\n\n\n\n「{llm_kwargs['llm_model']}调用结束，该模型不具备上下文对话能力，如需追问，请及时切换模型。」"
-                        yield from update_ui_latest_msg(lastmsg, chatbot, history, delay=1)
+                        yield from update_ui_lastest_msg(lastmsg, chatbot, history, delay=1)
                         log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                         break
                     # 处理数据流的主体

request_llms/bridge_claude.py

@@ -69,7 +69,7 @@ def decode_chunk(chunk):
     return need_to_pass, chunkjson, is_last_chunk
 
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
     """
     发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -151,7 +151,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     if inputs == "":     inputs = "空空如也的输入栏"

request_llms/bridge_cohere.py

@@ -68,7 +68,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
     """
     发送，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -111,7 +111,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
         if chunkjson['event_type'] == 'stream-start': continue
         if chunkjson['event_type'] == 'text-generation':
             result += chunkjson["text"]
-            if not console_silence: print(chunkjson["text"], end='')
+            if not console_slience: print(chunkjson["text"], end='')
             if observe_window is not None:
                 # 观测窗，把已经获取的数据显示出去
                 if len(observe_window) >= 1:
@@ -132,7 +132,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     # if is_any_api_key(inputs):

request_llms/bridge_deepseekcoder.py

@@ -6,6 +6,7 @@ from toolbox import get_conf
 from request_llms.local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
 from threading import Thread
 from loguru import logger
+import torch
 import os
 
 def download_huggingface_model(model_name, max_retry, local_dir):
@@ -28,7 +29,6 @@ class GetCoderLMHandle(LocalLLMHandle):
         self.cmd_to_install = cmd_to_install
 
     def load_model_and_tokenizer(self):
-        import torch
         # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
         with ProxyNetworkActivate('Download_LLM'):
             from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer

request_llms/bridge_google_gemini.py

@@ -8,7 +8,7 @@ import os
 import time
 from request_llms.com_google import GoogleChatInit
 from toolbox import ChatBotWithCookies
-from toolbox import get_conf, update_ui, update_ui_latest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
+from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY')
 timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
@@ -16,7 +16,7 @@ timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check
 
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[],
-                                  console_silence:bool=False):
+                                  console_slience:bool=False):
     # 检查API_KEY
     if get_conf("GEMINI_API_KEY") == "":
         raise ValueError(f"请配置 GEMINI_API_KEY。")
@@ -60,7 +60,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
 
     # 检查API_KEY
     if get_conf("GEMINI_API_KEY") == "":
-        yield from update_ui_latest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
         return
 
     # 适配润色区域

request_llms/bridge_jittorllms_llama.py

@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
                 if self.jittorllms_model is None:
                     device = get_conf('LOCAL_MODEL_DEVICE')
                     from .jittorllms.models import get_model
-                    # available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
                     args_dict = {'model': 'llama'}
                     print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
                     self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
@@ -107,7 +107,7 @@ global llama_glm_handle
 llama_glm_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_silence:bool=False):
+                                  observe_window:list=[], console_slience:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_jittorllms_pangualpha.py

@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
                 if self.jittorllms_model is None:
                     device = get_conf('LOCAL_MODEL_DEVICE')
                     from .jittorllms.models import get_model
-                    # available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
                     args_dict = {'model': 'pangualpha'}
                     print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
                     self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
@@ -107,7 +107,7 @@ global pangu_glm_handle
 pangu_glm_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_silence:bool=False):
+                                  observe_window:list=[], console_slience:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_jittorllms_rwkv.py

@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
                 if self.jittorllms_model is None:
                     device = get_conf('LOCAL_MODEL_DEVICE')
                     from .jittorllms.models import get_model
-                    # available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
                     args_dict = {'model': 'chatrwkv'}
                     print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
                     self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
@@ -107,7 +107,7 @@ global rwkv_glm_handle
 rwkv_glm_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_silence:bool=False):
+                                  observe_window:list=[], console_slience:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py