version 3.47

Merge pull request #979 from fenglui/master
增加chatGLM int4配置支持小显存也可以选择chatGLM
2025-12-07 06:56:48 +00:00 · 2023-07-24 19:58:47 +08:00 · 2023-07-24 19:52:27 +08:00 · 2023-07-24 18:50:29 +08:00 · 2023-07-24 18:19:57 +08:00 · 2023-07-24 18:06:15 +08:00
--- a/README.md
+++ b/README.md
@@ -44,7 +44,7 @@ chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
 Latex论文一键校对 | [函数插件] 仿Grammarly对Latex文章进行语法、拼写纠错+输出对照PDF
 [谷歌学术统合小助手](https://www.bilibili.com/video/BV19L411U7ia) | [函数插件] 给定任意谷歌学术搜索页面URL，让gpt帮你[写relatedworks](https://www.bilibili.com/video/BV1GP411U7Az/)
 互联网信息聚合+GPT | [函数插件] 一键[让GPT从互联网获取信息](https://www.bilibili.com/video/BV1om4y127ck)回答问题，让信息永不过时
-⭐Arxiv论文精细翻译 | [函数插件] 一键[以超高质量翻译arxiv论文](https://www.bilibili.com/video/BV1dz4y1v77A/)，目前最好的论文翻译工具
+⭐Arxiv论文精细翻译 ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [函数插件] 一键[以超高质量翻译arxiv论文](https://www.bilibili.com/video/BV1dz4y1v77A/)，目前最好的论文翻译工具
 ⭐[实时语音对话输入](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [函数插件] 异步[监听音频](https://www.bilibili.com/video/BV1AV4y187Uy/)，自动断句，自动寻找回答时机
 公式/图片/表格显示 | 可以同时显示公式的[tex形式和渲染形式](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png)，支持公式、代码高亮
 多线程函数插件支持 | 支持多线调用chatgpt，一键处理[海量文本](https://www.bilibili.com/video/BV1FT411H7c5/)或程序
@@ -93,7 +93,7 @@ Latex论文一键校对 | [函数插件] 仿Grammarly对Latex文章进行语法

 1. 下载项目
 ```sh
-git clone https://github.com/binary-husky/gpt_academic.git
+git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
 cd gpt_academic
 ```

@@ -126,7 +126,7 @@ python -m pip install -r request_llm/requirements_chatglm.txt

 # 【可选步骤II】支持复旦MOSS
 python -m pip install -r request_llm/requirements_moss.txt
-git clone https://github.com/OpenLMLab/MOSS.git request_llm/moss  # 注意执行此行代码时，必须处于项目根路径
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llm/moss  # 注意执行此行代码时，必须处于项目根路径

 # 【可选步骤III】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", "newbing", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
@@ -149,7 +149,7 @@ python main.py
 [![basiclatex](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml)

 ``` sh
-git clone https://github.com/binary-husky/gpt_academic.git  # 下载项目
+git clone --depth=1 https://github.com/binary-husky/gpt_academic.git  # 下载项目
 cd gpt_academic                                 # 进入路径
 nano config.py                                      # 用任意文本编辑器编辑config.py, 配置 “Proxy”， “API_KEY” 以及 “WEB_PORT” (例如50923) 等
 docker build -t gpt-academic .                      # 安装
--- a/cc.json
+++ b/cc.json
@@ -1,39 +0,0 @@
-[
-    {
-        "name": "Box-1",
-        "width": 1,
-        "height": 1,
-        "depth": 1,
-        "location_x": 1,
-        "location_y": 0,
-        "location_z": 0
-    },
-    {
-        "name": "Box-2",
-        "width": 1,
-        "height": 1,
-        "depth": 1,
-        "location_x": -1,
-        "location_y": 0,
-        "location_z": 0
-    },
-    {
-        "name": "Box-3",
-        "width": 1,
-        "height": 1,
-        "depth": 1,
-        "location_x": 0,
-        "location_y": 1,
-        "location_z": 0
-    },
-    {
-        "name": "Box-4",
-        "width": 1,
-        "height": 1,
-        "depth": 1,
-        "location_x": 0,
-        "location_y": -1,
-        "location_z": 0
-    }
-
-]
--- a/config.py
+++ b/config.py
@@ -32,9 +32,9 @@ else:

 # ------------------------------------ 以下配置可以优化体验, 但大部分场合下并不需要修改 ------------------------------------

-# 重新URL重新定向，实现更换API_URL的作用（常规情况下，不要修改!! 高危设置！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"} 
-# 例如 API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions":"https://reverse-proxy-url/v1/chat/completions"}
+# 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"}
 API_URL_REDIRECT = {}


@@ -71,7 +71,7 @@ MAX_RETRY = 2
 # 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" # 可选 ↓↓↓
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
-# P.S. 其他可用的模型还包括 ["gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "claude-1-100k", "claude-2", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
+# P.S. 其他可用的模型还包括 ["gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "claude-1-100k", "claude-2", "internlm", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]


 # ChatGLM(2) Finetune Model Path （如果使用ChatGLM2微调模型，需要把"chatglmft"加入AVAIL_LLM_MODELS中）
@@ -80,6 +80,7 @@ ChatGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b

 # 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）
@@ -136,4 +137,8 @@ ALIYUN_APPKEY=""   # 例如 RoPlZrM88DnAFkZK


 # Claude API KEY
-ANTHROPIC_API_KEY = ""
+ANTHROPIC_API_KEY = ""
+
+
+# 自定义API KEY格式
+CUSTOM_API_KEY_PATTERN = ""
--- a/crazy_functional.py
+++ b/crazy_functional.py
@@ -416,17 +416,6 @@ def get_crazy_functions():
    except:
        print('Load function plugin failed')

-    try:
-        from crazy_functions.Three场景交互3D import 三维生成
-        function_plugins.update({
-            "ThreeJS 三维交互": {
-                "Color": "stop",
-                "AsButton": False,
-                "Function": HotReload(三维生成)
-            }
-        })
-    except:
-        print('Load function plugin failed')

    try:
        from toolbox import get_conf
--- a/crazy_functions/Latex输出PDF结果.py
+++ b/crazy_functions/Latex输出PDF结果.py
@@ -157,7 +157,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
    try:
        import glob, os, time, subprocess
        subprocess.Popen(['pdflatex', '-version'])
-        from .latex_utils import Latex精细分解与转化, 编译Latex
+        from .latex_fns.latex_actions import Latex精细分解与转化, 编译Latex
    except Exception as e:
        chatbot.append([ f"解析项目: {txt}",
            f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。安装方法https://tug.org/texlive/。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
@@ -234,7 +234,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
    try:
        import glob, os, time, subprocess
        subprocess.Popen(['pdflatex', '-version'])
-        from .latex_utils import Latex精细分解与转化, 编译Latex
+        from .latex_fns.latex_actions import Latex精细分解与转化, 编译Latex
    except Exception as e:
        chatbot.append([ f"解析项目: {txt}",
            f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。安装方法https://tug.org/texlive/。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
--- a/crazy_functions/Three场景交互3D.py
+++ b/crazy_functions/Three场景交互3D.py
@@ -1,249 +0,0 @@
-from toolbox import CatchException, update_ui, gen_time_str
-from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
-from .crazy_utils import input_clipping
-
-def inspect_dependency(chatbot, history):
-    # 尝试导入依赖，如果缺少依赖，则给出安装建议
-    try:
-        from VISUALIZE.mcom import mcom
-        return True
-    except:
-        chatbot.append(["导入依赖失败", "使用该模块需要额外依赖，安装方法:```pip install vhmap```"])
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        return False
-
-def get_code_block(reply):
-    try:
-        import json
-        json.loads(reply)
-        return reply
-    except:
-        pass
-
-    import re
-    pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
-    matches = re.findall(pattern, reply) # find all code blocks in text
-    res = ""
-    for match in matches:
-        if 'import ' not in match:
-            res = match.strip('python').strip('json')
-            break
-    if len(res) == 0:
-        print(reply)
-        raise RuntimeError("GPT is not generating proper Json.")
-    return res  #  code block
-
-def get_json_blocks(reply):
-    import re, json
-    pattern = r"{([\s\S]*?)}" # regex pattern to match code blocks
-    matches = re.findall(pattern, reply) # find all code blocks in text
-    res = []
-    for match in matches:
-        if '"name"' in match:
-            try:
-                res.append(json.loads("{" + f'{match}' + "}"))
-            except:
-                pass
-    return res  #  code block
-
-def read_json(code):
-    import json
-    return json.loads(code)
-     
-def parse_partial(vi, gpt_say):
-    # 解析Json
-    js = get_json_blocks(gpt_say)
-    vi.update(js)
-
-
-@CatchException
-def 三维生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
-    """
-    txt             输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
-    llm_kwargs      gpt模型参数，如温度和top_p等，一般原样传递下去就行
-    plugin_kwargs   插件模型的参数，暂时没有用武之地
-    chatbot         聊天显示框的句柄，用于显示给用户
-    history         聊天历史，前情提要
-    system_prompt   给gpt的静默提醒
-    web_port        当前软件运行的端口号
-    """
-    from .vhmap_interact.vhmap import vhmp_interface
-    vi = vhmp_interface()
-    # 基本信息：功能、贡献者
-    chatbot.append([
-        "函数插件功能？",
-        "生成3D, 此插件处于开发阶段, 建议暂时不要使用, 作者: binary-husky, 插件初始化中 ..."
-    ])
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
-    # 尝试导入依赖, 如果缺少依赖, 则给出安装建议
-    dep_ok = yield from inspect_dependency(chatbot=chatbot, history=history) # 刷新界面
-    if not dep_ok: return
-    
-    # 输入
-    i_say = prompt(txt)
-    # 开始
-    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=i_say, inputs_show_user=i_say, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
-        sys_prompt=r"You are a Json generator",
-        on_reply_update=lambda t:parse_partial(vi, t)
-    )
-    chatbot.append(["开始生成执行", "..."])
-    history.extend([i_say, gpt_say])
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
-    
-    # 解析Json
-    code = get_code_block(gpt_say)
-    js = read_json(code)
-    vi.update(js)
-    return
-
-
-def prompt(text):
-    return r"""
-> Requirements:
-    1. You can only use square Boxes to build cubes and walls.
-    2. The space you can work in is a sphere with origin (0,0,0) and radius 100.
-    3. The ground is z=0.
-    4. You can only use 100 boxes.
-    5. Format of each box is json, e.g.
-    {
-        "name": "Box-1",
-        "geometry": "box", // choose from "box", "octahedron", "sphere", "cylinder"
-        "size": 1.0,
-        "color": "rgb(255,165,0)",
-        "location_x": 1.0,
-        "location_y": 0.0,
-        "location_z": 0.0
-    },
-    6. Only produce json as output. Use markdown code block to wrap the json output.
-
-> Example:
-    User: Generate 4 different objects around the origin.
-    You:
-    ```
-    [
-        {
-            "name": "Box-1",
-            "size": 1.0,
-            "geometry": "box",
-            "color": "rgb(255,11,10)",
-            "location_x": 1.0,
-            "location_y": 0.0,
-            "location_z": 0.0
-        },
-        {
-            "name": "Box-2",
-            "size": 1.0,
-            "geometry": "octahedron",
-            "color": "rgb(255,11,10)",
-            "location_x": -1.0,
-            "location_y": 0.0,
-            "location_z": 0.0
-        },
-        {
-            "name": "Box-3",
-            "size": 1.0,
-            "geometry": "sphere",
-            "color": "rgb(255,11,10)",
-            "location_x": 0.0,
-            "location_y": 1.0,
-            "location_z": 0.0
-        },
-        {
-            "name": "Box-4",
-            "size": 1.0,
-            "geometry": "cylinder",
-            "color": "rgb(255,11,10)",
-            "location_x": 0.0,
-            "location_y": -1.0,
-            "location_z": 0.0
-        }
-    ]
-    ```
-
-> User: """ + text
-
-"""
-Please construct a 3D environment where a girl is sitting under a tree in a garden.
-
-Requirements:
-1. List objects in this scene and make a markdown list.
-2. The list must contain creative details, give at least 20 objects
-"""
-
-
-"""
-Convert the result to json, 
-Requirements:
-1. Format: [
-    {
-        "name": "object-1",
-        "location": [position_x, position_y, position_z]
-    }
-]
-2. Generate relative position of objects
-"""
-
-
-
-"""
-> Requirements:
-    1. You can use box, octahedron, sphere, cylinder to build objects.
-    2. The ground is z=0.
-    3. You can only use 100 boxes.
-    4. Format of each box is json, e.g.
-    {
-        "name": "Box-1",
-        "geometry": "box", // choose from "box", "octahedron", "sphere", "cylinder"
-        "size": 1.0,
-        "color": "rgb(255,165,0)",
-        "location_x": 1.0,
-        "location_y": 0.0,
-        "location_z": 0.0
-    },
-    5. Only produce json as output. Use markdown code block to wrap the json output.
-
-> Example:
-    ```
-    [
-        {
-            "name": "Box-1",
-            "size": 1.0,
-            "geometry": "box",
-            "color": "rgb(255,11,10)",
-            "location_x": 1.0,
-            "location_y": 0.0,
-            "location_z": 0.0
-        },
-        {
-            "name": "Box-2",
-            "size": 1.0,
-            "geometry": "octahedron",
-            "color": "rgb(255,11,10)",
-            "location_x": -1.0,
-            "location_y": 0.0,
-            "location_z": 0.0
-        },
-        {
-            "name": "Box-3",
-            "size": 1.0,
-            "geometry": "sphere",
-            "color": "rgb(255,11,10)",
-            "location_x": 0.0,
-            "location_y": 1.0,
-            "location_z": 0.0
-        },
-        {
-            "name": "Box-4",
-            "size": 1.0,
-            "geometry": "cylinder",
-            "color": "rgb(255,11,10)",
-            "location_x": 0.0,
-            "location_y": -1.0,
-            "location_z": 0.0
-        }
-    ]
-    ```
-"""
--- a/crazy_functions/crazy_functions_test.py
+++ b/crazy_functions/crazy_functions_test.py
@@ -17,7 +17,7 @@ validate_path() # validate path so you can run from base directory
 # ==============================================================================================================================

 from colorful import *
-from toolbox import get_conf, ChatBotWithCookies, load_chat_cookies
+from toolbox import get_conf, ChatBotWithCookies
 import contextlib
 import os
 import sys
@@ -32,7 +32,6 @@ llm_kwargs = {
    'max_length': None,
    'temperature':1.0,
 }
-llm_kwargs.update(load_chat_cookies())
 plugin_kwargs = { }
 chatbot = ChatBotWithCookies(llm_kwargs)
 history = []
@@ -196,9 +195,12 @@ def test_Latex():
    # txt = r"https://arxiv.org/abs/2303.08774"
    # txt = r"https://arxiv.org/abs/2303.12712"
    # txt = r"C:\Users\fuqingxu\arxiv_cache\2303.12712\workfolder"
-    txt = r"2306.17157" # 这个paper有个input命令文件名大小写错误！
-    
-
+    # txt = r"2306.17157" # 这个paper有个input命令文件名大小写错误！
+    # txt = "https://arxiv.org/abs/2205.14135"
+    # txt = r"C:\Users\fuqingxu\arxiv_cache\2205.14135\workfolder"
+    # txt = r"C:\Users\fuqingxu\arxiv_cache\2205.14135\workfolder"
+    txt = r"2210.03629"
+    txt = r"2307.04964"
    for cookies, cb, hist, msg in (Latex翻译中文并重新编译PDF)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
        cli_printer.print(cb)   #  print(cb)

@@ -227,15 +229,6 @@ def test_chatglm_finetune():
        cli_printer.print(cb)


-def 三维生成():
-    from crazy_functions.Three场景交互3D import 三维生成
-    txt = "Generate 10 boxes to form a triangle formation with random color."
-    plugin_kwargs = {"advanced_arg":""}
-
-    for cookies, cb, hist, msg in (三维生成)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
-        cli_printer.print(cb)
-
-
 if __name__ == "__main__":
    # test_解析一个Python项目()
    # test_Latex英文润色()
@@ -250,7 +243,7 @@ if __name__ == "__main__":
    # test_数学动画生成manim()
    # test_Langchain知识库()
    # test_Langchain知识库读取()
-    # test_Latex()
-    三维生成()
+    test_Latex()
+    # test_chatglm_finetune()
    input("程序完成，回车退出。")
    print("退出。")
--- a/crazy_functions/crazy_utils.py
+++ b/crazy_functions/crazy_utils.py
@@ -40,7 +40,6 @@ def request_gpt_model_in_new_thread_with_ui_alive(
        chatbot, history, sys_prompt, refresh_interval=0.2,
        handle_token_exceed=True, 
        retry_times_at_unknown_error=2,
-        on_reply_update=None
        ):
    """
    Request GPT model，请求GPT模型同时维持用户界面活跃。
@@ -124,7 +123,6 @@ def request_gpt_model_in_new_thread_with_ui_alive(
        if future.done():
            break
        chatbot[-1] = [chatbot[-1][0], mutable[0]]
-        if on_reply_update: on_reply_update(mutable[0])
        yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面

    final_result = future.result()
--- a/crazy_functions/latex_fns/latex_actions.py
+++ b/crazy_functions/latex_fns/latex_actions.py
@@ -1,320 +1,16 @@
 from toolbox import update_ui, update_ui_lastest_msg    # 刷新Gradio前端界面
 from toolbox import zip_folder, objdump, objload, promote_file_to_downloadzone
+from .latex_toolbox import PRESERVE, TRANSFORM
+from .latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
+from .latex_toolbox import reverse_forbidden_text_careful_brace, reverse_forbidden_text, convert_to_linklist, post_process
+from .latex_toolbox import fix_content, find_main_tex_file, merge_tex_files, compile_latex_with_timeout
+
 import os, shutil
 import re
 import numpy as np
+
 pj = os.path.join

-"""
-========================================================================
-Part One
-Latex segmentation with a binary mask (PRESERVE=0, TRANSFORM=1)
-========================================================================
-"""
-PRESERVE = 0
-TRANSFORM = 1
-
-def set_forbidden_text(text, mask, pattern, flags=0):
-    """
-    Add a preserve text area in this paper
-    e.g. with pattern = r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}"
-    you can mask out (mask = PRESERVE so that text become untouchable for GPT) 
-    everything between "\begin{equation}" and "\end{equation}"
-    """
-    if isinstance(pattern, list): pattern = '|'.join(pattern)
-    pattern_compile = re.compile(pattern, flags)
-    for res in pattern_compile.finditer(text):
-        mask[res.span()[0]:res.span()[1]] = PRESERVE
-    return text, mask
-
-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 compelete text area. 
-    e.g.
-    \begin{abstract} blablablablablabla. \end{abstract} 
-    """
-    if isinstance(pattern, list): pattern = '|'.join(pattern)
-    pattern_compile = re.compile(pattern, flags)
-    for res in pattern_compile.finditer(text):
-        if not forbid_wrapper:
-            mask[res.span()[0]:res.span()[1]] = TRANSFORM
-        else:
-            mask[res.regs[0][0]: res.regs[1][0]] = PRESERVE   # '\\begin{abstract}'
-            mask[res.regs[1][0]: res.regs[1][1]] = TRANSFORM   # abstract
-            mask[res.regs[1][1]: res.regs[0][1]] = PRESERVE   # abstract
-    return text, mask
-
-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 compelete text area. 
-    e.g.
-    \caption{blablablablabla\texbf{blablabla}blablabla.} 
-    """
-    pattern_compile = re.compile(pattern, flags)
-    for res in pattern_compile.finditer(text):
-        brace_level = -1
-        p = begin = end = res.regs[0][0]
-        for _ in range(1024*16):
-            if text[p] == '}' and brace_level == 0: break
-            elif text[p] == '}':  brace_level -= 1
-            elif text[p] == '{':  brace_level += 1
-            p += 1
-        end = p+1
-        mask[begin:end] = PRESERVE
-    return text, mask
-
-def reverse_forbidden_text_careful_brace(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 compelete text area. 
-    e.g.
-    \caption{blablablablabla\texbf{blablabla}blablabla.} 
-    """
-    pattern_compile = re.compile(pattern, flags)
-    for res in pattern_compile.finditer(text):
-        brace_level = 0
-        p = begin = end = res.regs[1][0]
-        for _ in range(1024*16):
-            if text[p] == '}' and brace_level == 0: break
-            elif text[p] == '}':  brace_level -= 1
-            elif text[p] == '{':  brace_level += 1
-            p += 1
-        end = p
-        mask[begin:end] = TRANSFORM
-        if forbid_wrapper:
-            mask[res.regs[0][0]:begin] = PRESERVE
-            mask[end:res.regs[0][1]] = PRESERVE
-    return text, mask
-
-def set_forbidden_text_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
-    """
-    Find all \begin{} ... \end{} text block that with less than limit_n_lines lines.
-    Add it to preserve area
-    """
-    pattern_compile = re.compile(pattern, flags)
-    def search_with_line_limit(text, mask):
-        for res in pattern_compile.finditer(text):
-            cmd = res.group(1)  # begin{what}
-            this = res.group(2) # content between begin and end
-            this_mask = mask[res.regs[2][0]:res.regs[2][1]]
-            white_list = ['document', 'abstract', 'lemma', 'definition', 'sproof', 
-                          'em', 'emph', 'textit', 'textbf', 'itemize', 'enumerate']
-            if (cmd in white_list) or this.count('\n') >= limit_n_lines: # use a magical number 42
-                this, this_mask = search_with_line_limit(this, this_mask)
-                mask[res.regs[2][0]:res.regs[2][1]] = this_mask
-            else:
-                mask[res.regs[0][0]:res.regs[0][1]] = PRESERVE
-        return text, mask
-    return search_with_line_limit(text, mask) 
-
-class LinkedListNode():
-    """
-    Linked List Node
-    """
-    def __init__(self, string, preserve=True) -> None:
-        self.string = string
-        self.preserve = preserve
-        self.next = None
-        # self.begin_line = 0
-        # self.begin_char = 0
-
-def convert_to_linklist(text, mask):
-    root = LinkedListNode("", preserve=True)
-    current_node = root
-    for c, m, i in zip(text, mask, range(len(text))):
-        if (m==PRESERVE and current_node.preserve) \
-            or (m==TRANSFORM and not current_node.preserve):
-            # add
-            current_node.string += c
-        else:
-            current_node.next = LinkedListNode(c, preserve=(m==PRESERVE))
-            current_node = current_node.next
-    return root
-"""
-========================================================================
-Latex Merge File
-========================================================================
-"""
-
-def 寻找Latex主文件(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)
-    """
-    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:
-            canidates.append(texf)
-        else:
-            continue
-
-    if len(canidates) == 0:
-        raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')
-    elif len(canidates) == 1:
-        return canidates[0]
-    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
-        canidates_score = []
-        # 给出一些判定模板文档的词作为扣分项
-        unexpected_words = ['\LaTeX', 'manuscript', 'Guidelines', 'font', 'citations', 'rejected', 'blind review', 'reviewers']
-        expected_words = ['\input', '\ref', '\cite']
-        for texf in canidates:
-            canidates_score.append(0)
-            with open(texf, 'r', encoding='utf8', errors='ignore') as f:
-                file_content = f.read()
-            for uw in unexpected_words:
-                if uw in file_content:
-                    canidates_score[-1] -= 1
-            for uw in expected_words:
-                if uw in file_content:
-                    canidates_score[-1] += 1
-        select = np.argmax(canidates_score) # 取评分最高者返回
-        return canidates[select]
-    
-def rm_comments(main_file):
-    new_file_remove_comment_lines = []
-    for l in main_file.splitlines():
-        # 删除整行的空注释
-        if l.lstrip().startswith("%"):
-            pass
-        else:
-            new_file_remove_comment_lines.append(l)
-    main_file = '\n'.join(new_file_remove_comment_lines)
-    # main_file = re.sub(r"\\include{(.*?)}", r"\\input{\1}", main_file)  # 将 \include 命令转换为 \input 命令
-    main_file = re.sub(r'(?<!\\)%.*', '', main_file)  # 使用正则表达式查找半行注释, 并替换为空字符串
-    return main_file
-
-def find_tex_file_ignore_case(fp):
-    dir_name = os.path.dirname(fp)
-    base_name = os.path.basename(fp)
-    if not base_name.endswith('.tex'): base_name+='.tex'
-    if os.path.exists(pj(dir_name, base_name)): return pj(dir_name, base_name)
-    # go case in-sensitive
-    import glob
-    for f in glob.glob(dir_name+'/*.tex'):
-        base_name_s = os.path.basename(fp)
-        if base_name_s.lower() == base_name.lower(): return f
-    return None
-
-def merge_tex_files_(project_foler, main_file, mode):
-    """
-    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)]):
-        f = s.group(1)
-        fp = os.path.join(project_foler, f)
-        fp = find_tex_file_ignore_case(fp)
-        if fp:
-            with open(fp, 'r', encoding='utf-8', errors='replace') as fx: c = fx.read()
-        else:
-            raise RuntimeError(f'找不到{fp}，Tex源文件缺失！')
-        c = merge_tex_files_(project_foler, c, mode)
-        main_file = main_file[:s.span()[0]] + c + main_file[s.span()[1]:]
-    return main_file
-
-def merge_tex_files(project_foler, main_file, mode):
-    """
-    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
-    """
-    main_file = merge_tex_files_(project_foler, main_file, mode)
-    main_file = rm_comments(main_file)
-
-    if mode == 'translate_zh':
-        # find paper documentclass
-        pattern = re.compile(r'\\documentclass.*\n')
-        match = pattern.search(main_file)
-        assert match is not None, "Cannot find documentclass statement!"
-        position = match.end()
-        add_ctex = '\\usepackage{ctex}\n'
-        add_url = '\\usepackage{url}\n' if '{url}' not in main_file else ''
-        main_file = main_file[:position] + add_ctex + add_url + main_file[position:]
-        # fontset=windows
-        import platform
-        main_file = re.sub(r"\\documentclass\[(.*?)\]{(.*?)}", r"\\documentclass[\1,fontset=windows,UTF8]{\2}",main_file)
-        main_file = re.sub(r"\\documentclass{(.*?)}", r"\\documentclass[fontset=windows,UTF8]{\1}",main_file)
-        # find paper abstract
-        pattern_opt1 = re.compile(r'\\begin\{abstract\}.*\n')
-        pattern_opt2 = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
-        match_opt1 = pattern_opt1.search(main_file)
-        match_opt2 = pattern_opt2.search(main_file)
-        assert (match_opt1 is not None) or (match_opt2 is not None), "Cannot find paper abstract section!"
-    return main_file
-
-
-
-"""
-========================================================================
-Post process
-========================================================================
-"""
-def mod_inbraket(match):
-    """
-    为啥chatgpt会把cite里面的逗号换成中文逗号呀 
-    """
-    # get the matched string
-    cmd = match.group(1)
-    str_to_modify = match.group(2)
-    # modify the matched string
-    str_to_modify = str_to_modify.replace('：', ':')    # 前面是中文冒号，后面是英文冒号
-    str_to_modify = str_to_modify.replace('，', ',')    # 前面是中文逗号，后面是英文逗号
-    # str_to_modify = 'BOOM'
-    return "\\" + cmd + "{" + str_to_modify + "}"
-
-def fix_content(final_tex, node_string):
-    """
-    Fix common GPT errors to increase success rate
-    """
-    final_tex = re.sub(r"(?<!\\)%", "\\%", final_tex)
-    final_tex = re.sub(r"\\([a-z]{2,10})\ \{", r"\\\1{", string=final_tex)
-    final_tex = re.sub(r"\\\ ([a-z]{2,10})\{", r"\\\1{", string=final_tex)
-    final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)
-
-    if "Traceback" in final_tex and "[Local Message]" in final_tex:
-        final_tex = node_string # 出问题了，还原原文
-    if node_string.count('\\begin') != final_tex.count('\\begin'):
-        final_tex = node_string # 出问题了，还原原文
-    if node_string.count('\_') > 0 and node_string.count('\_') > final_tex.count('\_'):
-        # walk and replace any _ without \
-        final_tex = re.sub(r"(?<!\\)_", "\\_", final_tex)
-
-    def compute_brace_level(string):
-        # this function count the number of { and }
-        brace_level = 0
-        for c in string:
-            if c == "{": brace_level += 1
-            elif c == "}": brace_level -= 1
-        return brace_level
-    def join_most(tex_t, tex_o):
-        # this function join translated string and original string when something goes wrong
-        p_t = 0
-        p_o = 0
-        def find_next(string, chars, begin):
-            p = begin
-            while p < len(string):
-                if string[p] in chars: return p, string[p]
-                p += 1
-            return None, None
-        while True:
-            res1, char = find_next(tex_o, ['{','}'], p_o)
-            if res1 is None: break
-            res2, char = find_next(tex_t, [char], p_t)
-            if res2 is None: break
-            p_o = res1 + 1
-            p_t = res2 + 1
-        return tex_t[:p_t] + tex_o[p_o:]
-
-    if compute_brace_level(final_tex) != compute_brace_level(node_string):
-        # 出问题了，还原部分原文，保证括号正确
-        final_tex = join_most(final_tex, node_string)
-    return final_tex

 def split_subprocess(txt, project_folder, return_dict, opts):
    """
@@ -326,7 +22,8 @@ def split_subprocess(txt, project_folder, return_dict, opts):
    mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM

    # 吸收title与作者以上的部分
-    text, mask = set_forbidden_text(text, mask, r"(.*?)\\maketitle", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, r"^(.*?)\\maketitle", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, r"^(.*?)\\begin{document}", re.DOTALL)
    # 吸收iffalse注释
    text, mask = set_forbidden_text(text, mask, r"\\iffalse(.*?)\\fi", re.DOTALL)
    # 吸收在42行以内的begin-end组合
@@ -356,77 +53,9 @@ def split_subprocess(txt, project_folder, return_dict, opts):
    text, mask = reverse_forbidden_text(text, mask, r"\\begin\{abstract\}(.*?)\\end\{abstract\}", re.DOTALL, forbid_wrapper=True)
    root = convert_to_linklist(text, mask)

-    # 修复括号
-    node = root
-    while True:
-        string = node.string
-        if node.preserve: 
-            node = node.next
-            if node is None: break
-            continue
-        def break_check(string):
-            str_stack = [""] # (lv, index)
-            for i, c in enumerate(string):
-                if c == '{':
-                    str_stack.append('{')
-                elif c == '}':
-                    if len(str_stack) == 1:
-                        print('stack fix')
-                        return i
-                    str_stack.pop(-1)
-                else:
-                    str_stack[-1] += c
-            return -1
-        bp = break_check(string)
+    # 最后一步处理，增强稳健性
+    root = post_process(root)

-        if bp == -1:
-            pass
-        elif bp == 0:
-            node.string = string[:1]
-            q = LinkedListNode(string[1:], False)
-            q.next = node.next
-            node.next = q
-        else:
-            node.string = string[:bp]
-            q = LinkedListNode(string[bp:], False)
-            q.next = node.next
-            node.next = q
-
-        node = node.next
-        if node is None: break
-
-    # 屏蔽空行和太短的句子
-    node = root
-    while True:
-        if len(node.string.strip('\n').strip(''))==0: node.preserve = True
-        if len(node.string.strip('\n').strip(''))<42: node.preserve = True
-        node = node.next
-        if node is None: break
-    node = root
-    while True:
-        if node.next and node.preserve and node.next.preserve:
-            node.string += node.next.string
-            node.next = node.next.next
-        node = node.next
-        if node is None: break
-
-    # 将前后断行符脱离
-    node = root
-    prev_node = None
-    while True:
-        if not node.preserve:
-            lstriped_ = node.string.lstrip().lstrip('\n')
-            if (prev_node is not None) and (prev_node.preserve) and (len(lstriped_)!=len(node.string)):
-                prev_node.string += node.string[:-len(lstriped_)]
-                node.string = lstriped_
-            rstriped_ = node.string.rstrip().rstrip('\n')
-            if (node.next is not None) and (node.next.preserve) and (len(rstriped_)!=len(node.string)):
-                node.next.string = node.string[len(rstriped_):] + node.next.string
-                node.string = rstriped_
-        # =====
-        prev_node = node
-        node = node.next
-        if node is None: break
    # 输出html调试文件，用红色标注处保留区（PRESERVE），用黑色标注转换区（TRANSFORM）
    with open(pj(project_folder, 'debug_log.html'), 'w', encoding='utf8') as f:
        segment_parts_for_gpt = []
@@ -437,7 +66,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
            show_html = node.string.replace('\n','<br/>')
            if not node.preserve:
                segment_parts_for_gpt.append(node.string)
-                f.write(f'<p style="color:black;">#{show_html}#</p>')
+                f.write(f'<p style="color:black;">#{node.range}{show_html}#</p>')
            else:
                f.write(f'<p style="color:red;">{show_html}</p>')
            node = node.next
@@ -448,8 +77,6 @@ def split_subprocess(txt, project_folder, return_dict, opts):
    return_dict['segment_parts_for_gpt'] = segment_parts_for_gpt
    return return_dict

-
-
 class LatexPaperSplit():
    """
    break down latex file to a linked list,
@@ -464,18 +91,32 @@ class LatexPaperSplit():
        # 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。}}\\\\" 

-    def merge_result(self, arr, mode, msg):
+
+    def merge_result(self, arr, mode, msg, buggy_lines=[], buggy_line_surgery_n_lines=10):
        """
        Merge the result after the GPT process completed
        """
        result_string = ""
-        p = 0
+        node_cnt = 0
+        line_cnt = 0
+        
        for node in self.nodes:
            if node.preserve:
+                line_cnt += node.string.count('\n')
                result_string += node.string
            else:
-                result_string += fix_content(arr[p], node.string)
-                p += 1
+                translated_txt = fix_content(arr[node_cnt], node.string)
+                begin_line = line_cnt
+                end_line = line_cnt + translated_txt.count('\n')
+
+                # reverse translation if any error
+                if any([begin_line-buggy_line_surgery_n_lines <= b_line <= end_line+buggy_line_surgery_n_lines for b_line in buggy_lines]):
+                    translated_txt = node.string
+
+                result_string += translated_txt
+                node_cnt += 1
+                line_cnt += translated_txt.count('\n')
+
        if mode == 'translate_zh':
            pattern = re.compile(r'\\begin\{abstract\}.*\n')
            match = pattern.search(result_string)
@@ -490,6 +131,7 @@ class LatexPaperSplit():
            result_string = result_string[:position] + self.msg + msg + self.msg_declare + result_string[position:]
        return result_string

+
    def split(self, txt, project_folder, opts): 
        """
        break down latex file to a linked list,
@@ -511,7 +153,6 @@ class LatexPaperSplit():
        return self.sp


-
 class LatexPaperFileGroup():
    """
    use tokenizer to break down text according to max_token_limit
@@ -539,7 +180,7 @@ class LatexPaperFileGroup():
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
-                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
+                from ..crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
@@ -560,41 +201,14 @@ class LatexPaperFileGroup():
                f.write(res)
        return manifest

-def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):
-
-    # write html
-    try:
-        import shutil
-        from .crazy_utils import construct_html
-        from toolbox import gen_time_str
-        ch = construct_html() 
-        orig = ""
-        trans = ""
-        final = []
-        for c,r in zip(sp_file_contents, sp_file_result): 
-            final.append(c)
-            final.append(r)
-        for i, k in enumerate(final): 
-            if i%2==0:
-                orig = k
-            if i%2==1:
-                trans = k
-                ch.add_row(a=orig, b=trans)
-        create_report_file_name = f"{gen_time_str()}.trans.html"
-        ch.save_file(create_report_file_name)
-        shutil.copyfile(pj('./gpt_log/', create_report_file_name), pj(project_folder, create_report_file_name))
-        promote_file_to_downloadzone(file=f'./gpt_log/{create_report_file_name}', chatbot=chatbot)
-    except:
-        from toolbox import trimmed_format_exc
-        print('writing html result failed:', trimmed_format_exc())

 def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread', switch_prompt=None, opts=[]):
    import time, os, re
-    from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
-    from .latex_utils import LatexPaperFileGroup, merge_tex_files, LatexPaperSplit, 寻找Latex主文件
+    from ..crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
+    from .latex_actions import LatexPaperFileGroup, LatexPaperSplit

    #  <-------- 寻找主tex文件 ----------> 
-    maintex = 寻找Latex主文件(file_manifest, mode)
+    maintex = find_main_tex_file(file_manifest, mode)
    chatbot.append((f"定位主Latex文件", f'[Local Message] 分析结果：该项目的Latex主文件是{maintex}, 如果分析错误, 请立即终止程序, 删除或修改歧义文件, 然后重试。主程序即将开始, 请稍候。'))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
    time.sleep(3)
@@ -668,54 +282,51 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
    #  <-------- 写出文件 ----------> 
    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']}。"
    final_tex = lps.merge_result(pfg.file_result, mode, msg)
+    objdump((lps, pfg.file_result, mode, msg), file=pj(project_folder,'merge_result.pkl'))
+
    with open(project_folder + f'/merge_{mode}.tex', 'w', encoding='utf-8', errors='replace') as f:
        if mode != 'translate_zh' or "binary" in final_tex: f.write(final_tex)
        

    #  <-------- 整理结果, 退出 ----------> 
-    chatbot.append((f"完成了吗？", 'GPT结果已输出, 正在编译PDF'))
+    chatbot.append((f"完成了吗？", 'GPT结果已输出, 即将编译PDF'))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

    #  <-------- 返回 ----------> 
    return project_folder + f'/merge_{mode}.tex'


-
-def remove_buggy_lines(file_path, log_path, tex_name, tex_name_pure, n_fix, work_folder_modified):
+def remove_buggy_lines(file_path, log_path, tex_name, tex_name_pure, n_fix, work_folder_modified, fixed_line=[]):
    try:
        with open(log_path, 'r', encoding='utf-8', errors='replace') as f:
            log = f.read()
-        with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
-            file_lines = f.readlines()
        import re
        buggy_lines = re.findall(tex_name+':([0-9]{1,5}):', log)
        buggy_lines = [int(l) for l in buggy_lines]
        buggy_lines = sorted(buggy_lines)
-        print("removing lines that has errors", buggy_lines)
-        file_lines.pop(buggy_lines[0]-1)
+        buggy_line = buggy_lines[0]-1
+        print("reversing tex line that has errors", buggy_line)
+
+        # 重组，逆转出错的段落
+        if buggy_line not in fixed_line:
+            fixed_line.append(buggy_line)
+
+        lps, file_result, mode, msg = objload(file=pj(work_folder_modified,'merge_result.pkl'))
+        final_tex = lps.merge_result(file_result, mode, msg, buggy_lines=fixed_line, buggy_line_surgery_n_lines=5*n_fix)
+
        with open(pj(work_folder_modified, f"{tex_name_pure}_fix_{n_fix}.tex"), 'w', encoding='utf-8', errors='replace') as f:
-            f.writelines(file_lines)
+            f.write(final_tex)
+
        return True, f"{tex_name_pure}_fix_{n_fix}", buggy_lines
    except:
        print("Fatal error occurred, but we cannot identify error, please download zip, read latex log, and compile manually.")
        return False, -1, [-1]
-    
-def compile_latex_with_timeout(command, cwd, timeout=60):
-    import subprocess
-    process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd)
-    try:
-        stdout, stderr = process.communicate(timeout=timeout)
-    except subprocess.TimeoutExpired:
-        process.kill()
-        stdout, stderr = process.communicate()
-        print("Process timed out!")
-        return False
-    return True
+

 def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_folder_original, work_folder_modified, work_folder, mode='default'):
    import os, time
-    current_dir = os.getcwd()
    n_fix = 1
+    fixed_line = []
    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
@@ -723,6 +334,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f

    while True:
        import os
+        may_exist_bbl = pj(work_folder_modified, f'merge.bbl')
+        target_bbl = pj(work_folder_modified, f'{main_file_modified}.bbl')
+        if os.path.exists(may_exist_bbl) and not os.path.exists(target_bbl):
+            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_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
@@ -756,7 +371,6 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)

-
        # <---------- 检查结果 ----------->
        results_ = ""
        original_pdf_success = os.path.exists(pj(work_folder_original, f'{main_file_original}.pdf'))
@@ -773,9 +387,19 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
        if modified_pdf_success:
            yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 即将退出 ...', 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')):
                shutil.copyfile(result_pdf, pj(work_folder, '..', 'translation', 'translate_zh.pdf'))
            promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot)  # promote file to web UI
+            # 将两个PDF拼接
+            if original_pdf_success: 
+                try:
+                    from .latex_toolbox import merge_pdfs
+                    concat_pdf = pj(work_folder_modified, f'comparison.pdf')
+                    merge_pdfs(origin_pdf, result_pdf, concat_pdf)
+                    promote_file_to_downloadzone(concat_pdf, rename_file=None, chatbot=chatbot)  # promote file to web UI
+                except Exception as e:
+                    pass
            return True # 成功啦
        else:
            if n_fix>=max_try: break
@@ -787,6 +411,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                tex_name_pure=f'{main_file_modified}',
                n_fix=n_fix,
                work_folder_modified=work_folder_modified,
+                fixed_line=fixed_line
            )
            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
@@ -794,4 +419,29 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
    return False # 失败啦


-
+def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):
+    # write html
+    try:
+        import shutil
+        from ..crazy_utils import construct_html
+        from toolbox import gen_time_str
+        ch = construct_html() 
+        orig = ""
+        trans = ""
+        final = []
+        for c,r in zip(sp_file_contents, sp_file_result): 
+            final.append(c)
+            final.append(r)
+        for i, k in enumerate(final): 
+            if i%2==0:
+                orig = k
+            if i%2==1:
+                trans = k
+                ch.add_row(a=orig, b=trans)
+        create_report_file_name = f"{gen_time_str()}.trans.html"
+        ch.save_file(create_report_file_name)
+        shutil.copyfile(pj('./gpt_log/', create_report_file_name), pj(project_folder, create_report_file_name))
+        promote_file_to_downloadzone(file=f'./gpt_log/{create_report_file_name}', chatbot=chatbot)
+    except:
+        from toolbox import trimmed_format_exc
+        print('writing html result failed:', trimmed_format_exc())
--- a/crazy_functions/latex_fns/latex_toolbox.py
+++ b/crazy_functions/latex_fns/latex_toolbox.py
@@ -0,0 +1,456 @@
+import os, shutil
+import re
+import numpy as np
+PRESERVE = 0
+TRANSFORM = 1
+
+pj = os.path.join
+
+class LinkedListNode():
+    """
+    Linked List Node
+    """
+    def __init__(self, string, preserve=True) -> None:
+        self.string = string
+        self.preserve = preserve
+        self.next = None
+        self.range = None
+        # self.begin_line = 0
+        # self.begin_char = 0
+
+def convert_to_linklist(text, mask):
+    root = LinkedListNode("", preserve=True)
+    current_node = root
+    for c, m, i in zip(text, mask, range(len(text))):
+        if (m==PRESERVE and current_node.preserve) \
+            or (m==TRANSFORM and not current_node.preserve):
+            # add
+            current_node.string += c
+        else:
+            current_node.next = LinkedListNode(c, preserve=(m==PRESERVE))
+            current_node = current_node.next
+    return root
+
+def post_process(root):
+    # 修复括号
+    node = root
+    while True:
+        string = node.string
+        if node.preserve: 
+            node = node.next
+            if node is None: break
+            continue
+        def break_check(string):
+            str_stack = [""] # (lv, index)
+            for i, c in enumerate(string):
+                if c == '{':
+                    str_stack.append('{')
+                elif c == '}':
+                    if len(str_stack) == 1:
+                        print('stack fix')
+                        return i
+                    str_stack.pop(-1)
+                else:
+                    str_stack[-1] += c
+            return -1
+        bp = break_check(string)
+
+        if bp == -1:
+            pass
+        elif bp == 0:
+            node.string = string[:1]
+            q = LinkedListNode(string[1:], False)
+            q.next = node.next
+            node.next = q
+        else:
+            node.string = string[:bp]
+            q = LinkedListNode(string[bp:], False)
+            q.next = node.next
+            node.next = q
+
+        node = node.next
+        if node is None: break
+
+    # 屏蔽空行和太短的句子
+    node = root
+    while True:
+        if len(node.string.strip('\n').strip(''))==0: node.preserve = True
+        if len(node.string.strip('\n').strip(''))<42: node.preserve = True
+        node = node.next
+        if node is None: break
+    node = root
+    while True:
+        if node.next and node.preserve and node.next.preserve:
+            node.string += node.next.string
+            node.next = node.next.next
+        node = node.next
+        if node is None: break
+
+    # 将前后断行符脱离
+    node = root
+    prev_node = None
+    while True:
+        if not node.preserve:
+            lstriped_ = node.string.lstrip().lstrip('\n')
+            if (prev_node is not None) and (prev_node.preserve) and (len(lstriped_)!=len(node.string)):
+                prev_node.string += node.string[:-len(lstriped_)]
+                node.string = lstriped_
+            rstriped_ = node.string.rstrip().rstrip('\n')
+            if (node.next is not None) and (node.next.preserve) and (len(rstriped_)!=len(node.string)):
+                node.next.string = node.string[len(rstriped_):] + node.next.string
+                node.string = rstriped_
+        # =====
+        prev_node = node
+        node = node.next
+        if node is None: break
+
+    # 标注节点的行数范围
+    node = root
+    n_line = 0
+    expansion = 2
+    while True:
+        n_l = node.string.count('\n')
+        node.range = [n_line-expansion, n_line+n_l+expansion]   # 失败时，扭转的范围
+        n_line = n_line+n_l
+        node = node.next
+        if node is None: break
+    return root
+
+
+"""
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+Latex segmentation with a binary mask (PRESERVE=0, TRANSFORM=1)
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+"""
+
+
+def set_forbidden_text(text, mask, pattern, flags=0):
+    """
+    Add a preserve text area in this paper
+    e.g. with pattern = r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}"
+    you can mask out (mask = PRESERVE so that text become untouchable for GPT) 
+    everything between "\begin{equation}" and "\end{equation}"
+    """
+    if isinstance(pattern, list): pattern = '|'.join(pattern)
+    pattern_compile = re.compile(pattern, flags)
+    for res in pattern_compile.finditer(text):
+        mask[res.span()[0]:res.span()[1]] = PRESERVE
+    return text, mask
+
+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 compelete text area. 
+    e.g.
+    \begin{abstract} blablablablablabla. \end{abstract} 
+    """
+    if isinstance(pattern, list): pattern = '|'.join(pattern)
+    pattern_compile = re.compile(pattern, flags)
+    for res in pattern_compile.finditer(text):
+        if not forbid_wrapper:
+            mask[res.span()[0]:res.span()[1]] = TRANSFORM
+        else:
+            mask[res.regs[0][0]: res.regs[1][0]] = PRESERVE   # '\\begin{abstract}'
+            mask[res.regs[1][0]: res.regs[1][1]] = TRANSFORM   # abstract
+            mask[res.regs[1][1]: res.regs[0][1]] = PRESERVE   # abstract
+    return text, mask
+
+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 compelete text area. 
+    e.g.
+    \caption{blablablablabla\texbf{blablabla}blablabla.} 
+    """
+    pattern_compile = re.compile(pattern, flags)
+    for res in pattern_compile.finditer(text):
+        brace_level = -1
+        p = begin = end = res.regs[0][0]
+        for _ in range(1024*16):
+            if text[p] == '}' and brace_level == 0: break
+            elif text[p] == '}':  brace_level -= 1
+            elif text[p] == '{':  brace_level += 1
+            p += 1
+        end = p+1
+        mask[begin:end] = PRESERVE
+    return text, mask
+
+def reverse_forbidden_text_careful_brace(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 compelete text area. 
+    e.g.
+    \caption{blablablablabla\texbf{blablabla}blablabla.} 
+    """
+    pattern_compile = re.compile(pattern, flags)
+    for res in pattern_compile.finditer(text):
+        brace_level = 0
+        p = begin = end = res.regs[1][0]
+        for _ in range(1024*16):
+            if text[p] == '}' and brace_level == 0: break
+            elif text[p] == '}':  brace_level -= 1
+            elif text[p] == '{':  brace_level += 1
+            p += 1
+        end = p
+        mask[begin:end] = TRANSFORM
+        if forbid_wrapper:
+            mask[res.regs[0][0]:begin] = PRESERVE
+            mask[end:res.regs[0][1]] = PRESERVE
+    return text, mask
+
+def set_forbidden_text_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
+    """
+    Find all \begin{} ... \end{} text block that with less than limit_n_lines lines.
+    Add it to preserve area
+    """
+    pattern_compile = re.compile(pattern, flags)
+    def search_with_line_limit(text, mask):
+        for res in pattern_compile.finditer(text):
+            cmd = res.group(1)  # begin{what}
+            this = res.group(2) # content between begin and end
+            this_mask = mask[res.regs[2][0]:res.regs[2][1]]
+            white_list = ['document', 'abstract', 'lemma', 'definition', 'sproof', 
+                          'em', 'emph', 'textit', 'textbf', 'itemize', 'enumerate']
+            if (cmd in white_list) or this.count('\n') >= limit_n_lines: # use a magical number 42
+                this, this_mask = search_with_line_limit(this, this_mask)
+                mask[res.regs[2][0]:res.regs[2][1]] = this_mask
+            else:
+                mask[res.regs[0][0]:res.regs[0][1]] = PRESERVE
+        return text, mask
+    return search_with_line_limit(text, mask) 
+
+
+
+"""
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+Latex Merge File
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+"""
+
+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)
+    """
+    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:
+            canidates.append(texf)
+        else:
+            continue
+
+    if len(canidates) == 0:
+        raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')
+    elif len(canidates) == 1:
+        return canidates[0]
+    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
+        canidates_score = []
+        # 给出一些判定模板文档的词作为扣分项
+        unexpected_words = ['\LaTeX', 'manuscript', 'Guidelines', 'font', 'citations', 'rejected', 'blind review', 'reviewers']
+        expected_words = ['\input', '\ref', '\cite']
+        for texf in canidates:
+            canidates_score.append(0)
+            with open(texf, 'r', encoding='utf8', errors='ignore') as f:
+                file_content = f.read()
+            for uw in unexpected_words:
+                if uw in file_content:
+                    canidates_score[-1] -= 1
+            for uw in expected_words:
+                if uw in file_content:
+                    canidates_score[-1] += 1
+        select = np.argmax(canidates_score) # 取评分最高者返回
+        return canidates[select]
+    
+def rm_comments(main_file):
+    new_file_remove_comment_lines = []
+    for l in main_file.splitlines():
+        # 删除整行的空注释
+        if l.lstrip().startswith("%"):
+            pass
+        else:
+            new_file_remove_comment_lines.append(l)
+    main_file = '\n'.join(new_file_remove_comment_lines)
+    # main_file = re.sub(r"\\include{(.*?)}", r"\\input{\1}", main_file)  # 将 \include 命令转换为 \input 命令
+    main_file = re.sub(r'(?<!\\)%.*', '', main_file)  # 使用正则表达式查找半行注释, 并替换为空字符串
+    return main_file
+
+def find_tex_file_ignore_case(fp):
+    dir_name = os.path.dirname(fp)
+    base_name = os.path.basename(fp)
+    if not base_name.endswith('.tex'): base_name+='.tex'
+    if os.path.exists(pj(dir_name, base_name)): return pj(dir_name, base_name)
+    # go case in-sensitive
+    import glob
+    for f in glob.glob(dir_name+'/*.tex'):
+        base_name_s = os.path.basename(fp)
+        if base_name_s.lower() == base_name.lower(): return f
+    return None
+
+def merge_tex_files_(project_foler, main_file, mode):
+    """
+    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)]):
+        f = s.group(1)
+        fp = os.path.join(project_foler, f)
+        fp = find_tex_file_ignore_case(fp)
+        if fp:
+            with open(fp, 'r', encoding='utf-8', errors='replace') as fx: c = fx.read()
+        else:
+            raise RuntimeError(f'找不到{fp}，Tex源文件缺失！')
+        c = merge_tex_files_(project_foler, c, mode)
+        main_file = main_file[:s.span()[0]] + c + main_file[s.span()[1]:]
+    return main_file
+
+def merge_tex_files(project_foler, main_file, mode):
+    """
+    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
+    """
+    main_file = merge_tex_files_(project_foler, main_file, mode)
+    main_file = rm_comments(main_file)
+
+    if mode == 'translate_zh':
+        # find paper documentclass
+        pattern = re.compile(r'\\documentclass.*\n')
+        match = pattern.search(main_file)
+        assert match is not None, "Cannot find documentclass statement!"
+        position = match.end()
+        add_ctex = '\\usepackage{ctex}\n'
+        add_url = '\\usepackage{url}\n' if '{url}' not in main_file else ''
+        main_file = main_file[:position] + add_ctex + add_url + main_file[position:]
+        # fontset=windows
+        import platform
+        main_file = re.sub(r"\\documentclass\[(.*?)\]{(.*?)}", r"\\documentclass[\1,fontset=windows,UTF8]{\2}",main_file)
+        main_file = re.sub(r"\\documentclass{(.*?)}", r"\\documentclass[fontset=windows,UTF8]{\1}",main_file)
+        # find paper abstract
+        pattern_opt1 = re.compile(r'\\begin\{abstract\}.*\n')
+        pattern_opt2 = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
+        match_opt1 = pattern_opt1.search(main_file)
+        match_opt2 = pattern_opt2.search(main_file)
+        assert (match_opt1 is not None) or (match_opt2 is not None), "Cannot find paper abstract section!"
+    return main_file
+
+
+"""
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+Post process
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+"""
+def mod_inbraket(match):
+    """
+    为啥chatgpt会把cite里面的逗号换成中文逗号呀 
+    """
+    # get the matched string
+    cmd = match.group(1)
+    str_to_modify = match.group(2)
+    # modify the matched string
+    str_to_modify = str_to_modify.replace('：', ':')    # 前面是中文冒号，后面是英文冒号
+    str_to_modify = str_to_modify.replace('，', ',')    # 前面是中文逗号，后面是英文逗号
+    # str_to_modify = 'BOOM'
+    return "\\" + cmd + "{" + str_to_modify + "}"
+
+def fix_content(final_tex, node_string):
+    """
+    Fix common GPT errors to increase success rate
+    """
+    final_tex = re.sub(r"(?<!\\)%", "\\%", final_tex)
+    final_tex = re.sub(r"\\([a-z]{2,10})\ \{", r"\\\1{", string=final_tex)
+    final_tex = re.sub(r"\\\ ([a-z]{2,10})\{", r"\\\1{", string=final_tex)
+    final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)
+
+    if "Traceback" in final_tex and "[Local Message]" in final_tex:
+        final_tex = node_string # 出问题了，还原原文
+    if node_string.count('\\begin') != final_tex.count('\\begin'):
+        final_tex = node_string # 出问题了，还原原文
+    if node_string.count('\_') > 0 and node_string.count('\_') > final_tex.count('\_'):
+        # walk and replace any _ without \
+        final_tex = re.sub(r"(?<!\\)_", "\\_", final_tex)
+
+    def compute_brace_level(string):
+        # this function count the number of { and }
+        brace_level = 0
+        for c in string:
+            if c == "{": brace_level += 1
+            elif c == "}": brace_level -= 1
+        return brace_level
+    def join_most(tex_t, tex_o):
+        # this function join translated string and original string when something goes wrong
+        p_t = 0
+        p_o = 0
+        def find_next(string, chars, begin):
+            p = begin
+            while p < len(string):
+                if string[p] in chars: return p, string[p]
+                p += 1
+            return None, None
+        while True:
+            res1, char = find_next(tex_o, ['{','}'], p_o)
+            if res1 is None: break
+            res2, char = find_next(tex_t, [char], p_t)
+            if res2 is None: break
+            p_o = res1 + 1
+            p_t = res2 + 1
+        return tex_t[:p_t] + tex_o[p_o:]
+
+    if compute_brace_level(final_tex) != compute_brace_level(node_string):
+        # 出问题了，还原部分原文，保证括号正确
+        final_tex = join_most(final_tex, node_string)
+    return final_tex
+    
+def compile_latex_with_timeout(command, cwd, timeout=60):
+    import subprocess
+    process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd)
+    try:
+        stdout, stderr = process.communicate(timeout=timeout)
+    except subprocess.TimeoutExpired:
+        process.kill()
+        stdout, stderr = process.communicate()
+        print("Process timed out!")
+        return False
+    return True
+
+
+
+def merge_pdfs(pdf1_path, pdf2_path, output_path):
+    import PyPDF2
+    Percent = 0.8
+    # Open the first PDF file
+    with open(pdf1_path, 'rb') as pdf1_file:
+        pdf1_reader = PyPDF2.PdfFileReader(pdf1_file)
+        # Open the second PDF file
+        with open(pdf2_path, 'rb') as pdf2_file:
+            pdf2_reader = PyPDF2.PdfFileReader(pdf2_file)
+            # Create a new PDF file to store the merged pages
+            output_writer = PyPDF2.PdfFileWriter()
+            # Determine the number of pages in each PDF file
+            num_pages = max(pdf1_reader.numPages, pdf2_reader.numPages)
+            # Merge the pages from the two PDF files
+            for page_num in range(num_pages):
+                # Add the page from the first PDF file
+                if page_num < pdf1_reader.numPages:
+                    page1 = pdf1_reader.getPage(page_num)
+                else:
+                    page1 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
+                # Add the page from the second PDF file
+                if page_num < pdf2_reader.numPages:
+                    page2 = pdf2_reader.getPage(page_num)
+                else:
+                    page2 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
+                # Create a new empty page with double width
+                new_page = PyPDF2.PageObject.createBlankPage(
+                    width = int(int(page1.mediaBox.getWidth()) + int(page2.mediaBox.getWidth()) * Percent),
+                    height = max(page1.mediaBox.getHeight(), page2.mediaBox.getHeight())
+                )
+                new_page.mergeTranslatedPage(page1, 0, 0)
+                new_page.mergeTranslatedPage(page2, int(int(page1.mediaBox.getWidth())-int(page2.mediaBox.getWidth())* (1-Percent)), 0)
+                output_writer.addPage(new_page)
+            # Save the merged PDF file
+            with open(output_path, 'wb') as output_file:
+                output_writer.write(output_file)
--- a/crazy_functions/vhmap_interact/vhmap.py
+++ b/crazy_functions/vhmap_interact/vhmap.py
@@ -1,38 +0,0 @@
-from toolbox import update_ui, get_conf, trimmed_format_exc
-import threading
-
-def Singleton(cls):
-    _instance = {}
- 
-    def _singleton(*args, **kargs):
-        if cls not in _instance:
-            _instance[cls] = cls(*args, **kargs)
-        return _instance[cls]
- 
-    return _singleton
-
-@Singleton
-class vhmp_interface():
-    def __init__(self) -> None:
-        from VISUALIZE.mcom_rt import mcom
-        self.vis3d = mcom(path='TEMP/v2d_logger/', draw_mode='Threejs')
-        self.vis3d.v2d_init()
-        self.vis3d.设置样式('star')
-        # vis3d.设置样式('star')       # 布置星空
-        self.vis3d.其他几何体之旋转缩放和平移('box', 'BoxGeometry(1,1,1)',   0,0,0,  1,1,1, 0,0,0) 
-        # declare geo 'oct1', init with OctahedronGeometry, then (1)rotate & (2)scale & (3)translate
-        self.vis3d.其他几何体之旋转缩放和平移('octahedron', 'OctahedronGeometry(1,0)', 0,0,0,  1,1,1, 0,0,0)   # 八面体
-        # 需要换成其他几何体，请把'OctahedronGeometry(1,0)'替换，参考网址 https://threejs.org/docs/index.html?q=Geometry
-        self.vis3d.其他几何体之旋转缩放和平移('sphere', 'SphereGeometry(1)',   0,0,0,  1,1,1, 0,0,0) # 球体
-        self.vis3d.其他几何体之旋转缩放和平移('cylinder', 'CylinderGeometry(1,1,5,32)',   0,0,0,  1,1,1, 0,0,0) # 球体
-
-    def update(self, json):
-        for obj in json:
-            self.vis3d.发送几何体(
-                f'{obj["geometry"]}|{obj["name"]}|{obj["color"]}|{obj["size"]}',   # 填入 ‘形状|几何体之ID标识|颜色|大小’即可
-                obj["location_x"], 
-                obj["location_y"], 
-                obj["location_z"],
-                ro_x=0, ro_y=0, ro_z=0,                         # 三维位置+欧拉旋转变换，六自由度
-                track_n_frame=0)                                # 显示历史20帧留下的轨迹
-        self.vis3d.结束关键帧()
--- a/main.py
+++ b/main.py
@@ -22,8 +22,10 @@ def main():
    # 问询记录, python 版本建议3.9+（越新越好）
    import logging, uuid
    os.makedirs("gpt_log", exist_ok=True)
-    try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8")
-    except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO)
+    try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8", format="%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
+    except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO,  format="%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
+    # Disable logging output from the 'httpx' logger
+    logging.getLogger("httpx").setLevel(logging.WARNING)
    print("所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log, 请注意自我隐私保护哦！")

    # 一些普通功能模块
--- a/request_llm/bridge_all.py
+++ b/request_llm/bridge_all.py
@@ -248,7 +248,6 @@ if "moss" in AVAIL_LLM_MODELS:
 if "stack-claude" in AVAIL_LLM_MODELS:
    from .bridge_stackclaude import predict_no_ui_long_connection as claude_noui
    from .bridge_stackclaude import predict as claude_ui
-    # claude
    model_info.update({
        "stack-claude": {
            "fn_with_ui": claude_ui,
@@ -263,7 +262,6 @@ if "newbing-free" in AVAIL_LLM_MODELS:
    try:
        from .bridge_newbingfree import predict_no_ui_long_connection as newbingfree_noui
        from .bridge_newbingfree import predict as newbingfree_ui
-        # claude
        model_info.update({
            "newbing-free": {
                "fn_with_ui": newbingfree_ui,
@@ -280,7 +278,6 @@ if "newbing" in AVAIL_LLM_MODELS:   # same with newbing-free
    try:
        from .bridge_newbingfree import predict_no_ui_long_connection as newbingfree_noui
        from .bridge_newbingfree import predict as newbingfree_ui
-        # claude
        model_info.update({
            "newbing": {
                "fn_with_ui": newbingfree_ui,
@@ -297,7 +294,6 @@ if "chatglmft" in AVAIL_LLM_MODELS:   # same with newbing-free
    try:
        from .bridge_chatglmft import predict_no_ui_long_connection as chatglmft_noui
        from .bridge_chatglmft import predict as chatglmft_ui
-        # claude
        model_info.update({
            "chatglmft": {
                "fn_with_ui": chatglmft_ui,
@@ -310,7 +306,22 @@ if "chatglmft" in AVAIL_LLM_MODELS:   # same with newbing-free
        })
    except:
        print(trimmed_format_exc())
-
+if "internlm" in AVAIL_LLM_MODELS:
+    try:
+        from .bridge_internlm import predict_no_ui_long_connection as internlm_noui
+        from .bridge_internlm import predict as internlm_ui
+        model_info.update({
+            "internlm": {
+                "fn_with_ui": internlm_ui,
+                "fn_without_ui": internlm_noui,
+                "endpoint": None,
+                "max_token": 4096,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            }
+        })
+    except:
+        print(trimmed_format_exc())

 def LLM_CATCH_EXCEPTION(f):
    """
--- a/request_llm/bridge_chatglm.py
+++ b/request_llm/bridge_chatglm.py
@@ -37,15 +37,23 @@ class GetGLMHandle(Process):
        # 子进程执行
        # 第一次运行，加载参数
        retry = 0
+        LOCAL_MODEL_QUANT, device = get_conf('LOCAL_MODEL_QUANT', 'LOCAL_MODEL_DEVICE')
+
+        if LOCAL_MODEL_QUANT == "INT4":         # INT4
+            _model_name_ = "THUDM/chatglm2-6b-int4"
+        elif LOCAL_MODEL_QUANT == "INT8":       # INT8
+            _model_name_ = "THUDM/chatglm2-6b-int8"
+        else:
+            _model_name_ = "THUDM/chatglm2-6b"  # FP16
+
        while True:
            try:
                if self.chatglm_model is None:
-                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
-                    device, = get_conf('LOCAL_MODEL_DEVICE')
+                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
                    if device=='cpu':
-                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).float()
+                        self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
                    else:
-                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).half().cuda()
+                        self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
                    self.chatglm_model = self.chatglm_model.eval()
                    break
                else:
--- a/request_llm/bridge_chatgpt.py
+++ b/request_llm/bridge_chatgpt.py
@@ -174,9 +174,10 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                chunk = next(stream_response)
            except StopIteration:
                # 非OpenAI官方接口的出现这样的报错，OpenAI和API2D不会走这里
-                from toolbox import regular_txt_to_markdown; tb_str = '```\n' + trimmed_format_exc() + '```'
-                chatbot[-1] = (chatbot[-1][0], f"[Local Message] 远程返回错误: \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk.decode())}")
-                yield from update_ui(chatbot=chatbot, history=history, msg="远程返回错误:" + chunk.decode()) # 刷新界面
+                chunk_decoded = chunk.decode()
+                error_msg = chunk_decoded
+                chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
+                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
            
            # print(chunk.decode()[6:])
@@ -187,7 +188,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
            if chunk:
                try:
                    chunk_decoded = chunk.decode()
-                    # 前者API2D的
+                    # 前者是API2D的结束条件，后者是OPENAI的结束条件
                    if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0):
                        # 判定为数据流的结束，gpt_replying_buffer也写完了
                        logging.info(f'[response] {gpt_replying_buffer}')
@@ -200,41 +201,45 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                    history[-1] = gpt_replying_buffer
                    chatbot[-1] = (history[-2], history[-1])
                    yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
-
                except Exception as e:
-                    traceback.print_exc()
                    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
-                    openai_website = ' 请登录OpenAI查看详情 https://platform.openai.com/signup'
-                    if "reduce the length" in error_msg:
-                        if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入：history[-2] 是本次输入, history[-1] 是本次输出
-                        history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'], 
-                                               max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)")
-                        # history = []    # 清除历史
-                    elif "does not exist" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格.")
-                    elif "Incorrect API key" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务. " + openai_website)
-                    elif "exceeded your current quota" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务." + openai_website)
-                    elif "account is not active" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] Your account is not active. OpenAI以账户失效为由, 拒绝服务." + openai_website)
-                    elif "associated with a deactivated account" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] You are associated with a deactivated account. OpenAI以账户失效为由, 拒绝服务." + openai_website)
-                    elif "bad forward key" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] Bad forward key. API2D账户额度不足.")
-                    elif "Not enough point" in error_msg:
-                        chatbot[-1] = (chatbot[-1][0], "[Local Message] Not enough point. API2D账户点数不足.")
-                    else:
-                        from toolbox import regular_txt_to_markdown
-                        tb_str = '```\n' + trimmed_format_exc() + '```'
-                        chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded)}")
+                    chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
                    yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
+                    print(error_msg)
                    return

+def handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg):
+    from .bridge_all import model_info
+    openai_website = ' 请登录OpenAI查看详情 https://platform.openai.com/signup'
+    if "reduce the length" in error_msg:
+        if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入：history[-2] 是本次输入, history[-1] 是本次输出
+        history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'], 
+                                               max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)")
+                        # history = []    # 清除历史
+    elif "does not exist" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格.")
+    elif "Incorrect API key" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务. " + openai_website)
+    elif "exceeded your current quota" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务." + openai_website)
+    elif "account is not active" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] Your account is not active. OpenAI以账户失效为由, 拒绝服务." + openai_website)
+    elif "associated with a deactivated account" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] You are associated with a deactivated account. OpenAI以账户失效为由, 拒绝服务." + openai_website)
+    elif "bad forward key" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] Bad forward key. API2D账户额度不足.")
+    elif "Not enough point" in error_msg:
+        chatbot[-1] = (chatbot[-1][0], "[Local Message] Not enough point. API2D账户点数不足.")
+    else:
+        from toolbox import regular_txt_to_markdown
+        tb_str = '```\n' + trimmed_format_exc() + '```'
+        chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded)}")
+    return chatbot, history
+
 def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
    """
    整合所有信息，选择LLM模型，生成http请求，为发送请求做准备
--- a/request_llm/bridge_internlm.py
+++ b/request_llm/bridge_internlm.py
@@ -0,0 +1,315 @@
+
+from transformers import AutoModel, AutoTokenizer
+import time
+import threading
+import importlib
+from toolbox import update_ui, get_conf, Singleton
+from multiprocessing import Process, Pipe
+
+model_name = "InternLM"
+cmd_to_install = "`pip install ???`"
+load_message = f"{model_name}尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，{model_name}消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
+def try_to_import_special_deps():
+    import sentencepiece
+
+user_prompt = "<|User|>:{user}<eoh>\n"
+robot_prompt = "<|Bot|>:{robot}<eoa>\n"
+cur_query_prompt = "<|User|>:{user}<eoh>\n<|Bot|>:"
+
+
+def combine_history(prompt, hist):
+    messages = hist
+    total_prompt = ""
+    for message in messages:
+        cur_content = message
+        cur_prompt = user_prompt.replace("{user}", cur_content[0])
+        total_prompt += cur_prompt
+        cur_prompt = robot_prompt.replace("{robot}", cur_content[1])
+        total_prompt += cur_prompt
+    total_prompt = total_prompt + cur_query_prompt.replace("{user}", prompt)
+    return total_prompt
+
+
+@Singleton
+class GetInternlmHandle(Process):
+    def __init__(self):
+        # ⭐主进程执行
+        super().__init__(daemon=True)
+        self.parent, self.child = Pipe()
+        self._model = None
+        self._tokenizer = None
+        self.info = ""
+        self.success = True
+        self.check_dependency()
+        self.start()
+        self.threadLock = threading.Lock()
+
+    def ready(self):
+        # ⭐主进程执行
+        return self._model is not None
+
+    def load_model_and_tokenizer(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        import torch
+        from transformers import AutoModelForCausalLM, AutoTokenizer
+        device, = get_conf('LOCAL_MODEL_DEVICE')
+        if self._model is None:
+            tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True)
+            if device=='cpu':
+                model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True).to(torch.bfloat16)
+            else:
+                model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True).to(torch.bfloat16).cuda()
+
+            model = model.eval()
+        return model, tokenizer
+
+    def llm_stream_generator(self, **kwargs):
+        import torch
+        import logging
+        import copy
+        import warnings
+        import torch.nn as nn
+        from transformers.generation.utils import LogitsProcessorList, StoppingCriteriaList, GenerationConfig
+
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        def adaptor():
+            model = self._model
+            tokenizer = self._tokenizer
+            prompt = kwargs['query']
+            max_length = kwargs['max_length']
+            top_p = kwargs['top_p']
+            temperature = kwargs['temperature']
+            history = kwargs['history']
+            real_prompt = combine_history(prompt, history)
+            return model, tokenizer, real_prompt, max_length, top_p, temperature
+        
+        model, tokenizer, prompt, max_length, top_p, temperature = adaptor()
+        prefix_allowed_tokens_fn = None
+        logits_processor = None
+        stopping_criteria = None
+        additional_eos_token_id = 103028
+        generation_config = None
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ https://github.com/InternLM/InternLM/blob/efbf5335709a8c8faeac6eaf07193973ff1d56a1/web_demo.py#L25
+
+        inputs = tokenizer([prompt], padding=True, return_tensors="pt")
+        input_length = len(inputs["input_ids"][0])
+        for k, v in inputs.items():
+            inputs[k] = v.cuda()
+        input_ids = inputs["input_ids"]
+        batch_size, input_ids_seq_length = input_ids.shape[0], input_ids.shape[-1]
+        if generation_config is None:
+            generation_config = model.generation_config
+        generation_config = copy.deepcopy(generation_config)
+        model_kwargs = generation_config.update(**kwargs)
+        bos_token_id, eos_token_id = generation_config.bos_token_id, generation_config.eos_token_id
+        if isinstance(eos_token_id, int):
+            eos_token_id = [eos_token_id]
+        if additional_eos_token_id is not None:
+            eos_token_id.append(additional_eos_token_id)
+        has_default_max_length = kwargs.get("max_length") is None and generation_config.max_length is not None
+        if has_default_max_length and generation_config.max_new_tokens is None:
+            warnings.warn(
+                f"Using `max_length`'s default ({generation_config.max_length}) to control the generation length. "
+                "This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we"
+                " recommend using `max_new_tokens` to control the maximum length of the generation.",
+                UserWarning,
+            )
+        elif generation_config.max_new_tokens is not None:
+            generation_config.max_length = generation_config.max_new_tokens + input_ids_seq_length
+            if not has_default_max_length:
+                logging.warn(
+                    f"Both `max_new_tokens` (={generation_config.max_new_tokens}) and `max_length`(="
+                    f"{generation_config.max_length}) seem to have been set. `max_new_tokens` will take precedence. "
+                    "Please refer to the documentation for more information. "
+                    "(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)",
+                    UserWarning,
+                )
+
+        if input_ids_seq_length >= generation_config.max_length:
+            input_ids_string = "input_ids"
+            logging.warning(
+                f"Input length of {input_ids_string} is {input_ids_seq_length}, but `max_length` is set to"
+                f" {generation_config.max_length}. This can lead to unexpected behavior. You should consider"
+                " increasing `max_new_tokens`."
+            )
+
+        # 2. Set generation parameters if not already defined
+        logits_processor = logits_processor if logits_processor is not None else LogitsProcessorList()
+        stopping_criteria = stopping_criteria if stopping_criteria is not None else StoppingCriteriaList()
+
+        logits_processor = model._get_logits_processor(
+            generation_config=generation_config,
+            input_ids_seq_length=input_ids_seq_length,
+            encoder_input_ids=input_ids,
+            prefix_allowed_tokens_fn=prefix_allowed_tokens_fn,
+            logits_processor=logits_processor,
+        )
+
+        stopping_criteria = model._get_stopping_criteria(
+            generation_config=generation_config, stopping_criteria=stopping_criteria
+        )
+        logits_warper = model._get_logits_warper(generation_config)
+
+        unfinished_sequences = input_ids.new(input_ids.shape[0]).fill_(1)
+        scores = None
+        while True:
+            model_inputs = model.prepare_inputs_for_generation(input_ids, **model_kwargs)
+            # forward pass to get next token
+            outputs = model(
+                **model_inputs,
+                return_dict=True,
+                output_attentions=False,
+                output_hidden_states=False,
+            )
+
+            next_token_logits = outputs.logits[:, -1, :]
+
+            # pre-process distribution
+            next_token_scores = logits_processor(input_ids, next_token_logits)
+            next_token_scores = logits_warper(input_ids, next_token_scores)
+
+            # sample
+            probs = nn.functional.softmax(next_token_scores, dim=-1)
+            if generation_config.do_sample:
+                next_tokens = torch.multinomial(probs, num_samples=1).squeeze(1)
+            else:
+                next_tokens = torch.argmax(probs, dim=-1)
+
+            # update generated ids, model inputs, and length for next step
+            input_ids = torch.cat([input_ids, next_tokens[:, None]], dim=-1)
+            model_kwargs = model._update_model_kwargs_for_generation(
+                outputs, model_kwargs, is_encoder_decoder=False
+            )
+            unfinished_sequences = unfinished_sequences.mul((min(next_tokens != i for i in eos_token_id)).long())
+            
+            output_token_ids = input_ids[0].cpu().tolist()
+            output_token_ids = output_token_ids[input_length:]
+            for each_eos_token_id in eos_token_id:
+                if output_token_ids[-1] == each_eos_token_id:
+                    output_token_ids = output_token_ids[:-1]
+            response = tokenizer.decode(output_token_ids)
+
+            yield response
+            # stop when each sentence is finished, or if we exceed the maximum length
+            if unfinished_sequences.max() == 0 or stopping_criteria(input_ids, scores):
+                return
+
+
+
+    def check_dependency(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        try:
+            try_to_import_special_deps()
+            self.info = "依赖检测通过"
+            self.success = True
+        except:
+            self.info = f"缺少{model_name}的依赖，如果要使用{model_name}，除了基础的pip依赖以外，您还需要运行{cmd_to_install}安装{model_name}的依赖。"
+            self.success = False
+
+    def run(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        # 第一次运行，加载参数
+        try:
+            self._model, self._tokenizer = self.load_model_and_tokenizer()
+        except:
+            from toolbox import trimmed_format_exc
+            self.child.send(f'[Local Message] 不能正常加载{model_name}的参数.' + '\n```\n' + trimmed_format_exc() + '\n```\n')
+            raise RuntimeError(f"不能正常加载{model_name}的参数！")
+
+        while True:
+            # 进入任务等待状态
+            kwargs = self.child.recv()
+            # 收到消息，开始请求
+            try:
+                for response_full in self.llm_stream_generator(**kwargs):
+                    self.child.send(response_full)
+            except:
+                from toolbox import trimmed_format_exc
+                self.child.send(f'[Local Message] 调用{model_name}失败.' + '\n```\n' + trimmed_format_exc() + '\n```\n')
+            # 请求处理结束，开始下一个循环
+            self.child.send('[Finish]')
+
+    def stream_chat(self, **kwargs):
+        # ⭐主进程执行
+        self.threadLock.acquire()
+        self.parent.send(kwargs)
+        while True:
+            res = self.parent.recv()
+            if res != '[Finish]':
+                yield res
+            else:
+                break
+        self.threadLock.release()
+    
+    
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 GPT-Academic
+# ------------------------------------------------------------------------------------------------------------------------
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
+    """
+        ⭐多线程方法
+        函数的说明请见 request_llm/bridge_all.py
+    """
+    _llm_handle = GetInternlmHandle()
+    if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + _llm_handle.info
+    if not _llm_handle.success: 
+        error = _llm_handle.info
+        _llm_handle = None
+        raise RuntimeError(error)
+
+    # chatglm 没有 sys_prompt 接口，因此把prompt加入 history
+    history_feedin = []
+    history_feedin.append(["What can I do?", sys_prompt])
+    for i in range(len(history)//2):
+        history_feedin.append([history[2*i], history[2*i+1]] )
+
+    watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
+    response = ""
+    for response in _llm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+        if len(observe_window) >= 1:  observe_window[0] = response
+        if len(observe_window) >= 2:  
+            if (time.time()-observe_window[1]) > watch_dog_patience:
+                raise RuntimeError("程序终止。")
+    return response
+
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+    """
+        ⭐单线程方法
+        函数的说明请见 request_llm/bridge_all.py
+    """
+    chatbot.append((inputs, ""))
+
+    _llm_handle = GetInternlmHandle()
+    chatbot[-1] = (inputs, load_message + "\n\n" + _llm_handle.info)
+    yield from update_ui(chatbot=chatbot, history=[])
+    if not _llm_handle.success: 
+        _llm_handle = None
+        return
+
+    if additional_fn is not None:
+        import core_functional
+        importlib.reload(core_functional)    # 热更新prompt
+        core_functional = core_functional.get_core_functions()
+        if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
+        inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
+
+    # 处理历史信息
+    history_feedin = []
+    history_feedin.append(["What can I do?", system_prompt] )
+    for i in range(len(history)//2):
+        history_feedin.append([history[2*i], history[2*i+1]] )
+
+    # 开始接收chatglm的回复
+    response = f"[Local Message]: 等待{model_name}响应中 ..."
+    for response in _llm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+        chatbot[-1] = (inputs, response)
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    # 总结输出
+    if response == f"[Local Message]: 等待{model_name}响应中 ...":
+        response = f"[Local Message]: {model_name}响应异常 ..."
+    history.extend([inputs, response])
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/request_llm/edge_gpt_free.py
+++ b/request_llm/edge_gpt_free.py
@@ -447,6 +447,15 @@ class _ChatHub:
        """
        Ask a question to the bot
        """
+        req_header = HEADERS
+        if self.cookies is not None:
+            ws_cookies = []
+            for cookie in self.cookies:
+                ws_cookies.append(f"{cookie['name']}={cookie['value']}")
+            req_header.update({
+                'Cookie': ';'.join(ws_cookies),
+            })
+            
        timeout = aiohttp.ClientTimeout(total=30)
        self.session = aiohttp.ClientSession(timeout=timeout)

@@ -455,7 +464,7 @@ class _ChatHub:
        # Check if websocket is closed
        self.wss = await self.session.ws_connect(
            wss_link,
-            headers=HEADERS,
+            headers=req_header,
            ssl=ssl_context,
            proxy=self.proxy,
            autoping=False,
@@ -510,7 +519,11 @@ class _ChatHub:
        resp_txt_no_link = ""
        while not final:
            msg = await self.wss.receive()
-            objects = msg.data.split(DELIMITER)
+            try:
+                objects = msg.data.split(DELIMITER)
+            except :
+                continue
+            
            for obj in objects:
                if obj is None or not obj:
                    continue
@@ -1109,4 +1122,4 @@ class ImageQuery(Query):


 if __name__ == "__main__":
-    main()
+    main()
--- a/request_llm/test_llms.py
+++ b/request_llm/test_llms.py
@@ -14,7 +14,8 @@ if __name__ == "__main__":
    # from request_llm.bridge_moss import predict_no_ui_long_connection
    # from request_llm.bridge_jittorllms_pangualpha import predict_no_ui_long_connection
    # from request_llm.bridge_jittorllms_llama import predict_no_ui_long_connection
-    from request_llm.bridge_claude import predict_no_ui_long_connection
+    # from request_llm.bridge_claude import predict_no_ui_long_connection
+    from request_llm.bridge_internlm import predict_no_ui_long_connection

    llm_kwargs = {
        'max_length': 512,
@@ -22,45 +23,8 @@ if __name__ == "__main__":
        'temperature': 1,
    }

-    result = predict_no_ui_long_connection(inputs="你好", 
-                                        llm_kwargs=llm_kwargs,
-                                        history=[],
-                                        sys_prompt="")
+    result = predict_no_ui_long_connection( inputs="请问什么是质子？", 
+                                            llm_kwargs=llm_kwargs,
+                                            history=["你好", "我好！"],
+                                            sys_prompt="")
    print('final result:', result)
-
-
-
-    # # print(result)
-    # from multiprocessing import Process, Pipe
-    # class GetGLMHandle(Process):
-    #     def __init__(self):
-    #         super().__init__(daemon=True)
-    #         pass
-    #     def run(self):
-    #         # 子进程执行
-    #         # 第一次运行，加载参数
-    #         def validate_path():
-    #             import os, sys
-    #             dir_name = os.path.dirname(__file__)
-    #             root_dir_assume = os.path.abspath(os.path.dirname(__file__) +  '/..')
-    #             os.chdir(root_dir_assume + '/request_llm/jittorllms')
-    #             sys.path.append(root_dir_assume + '/request_llm/jittorllms')
-    #         validate_path() # validate path so you can run from base directory
-    #         jittorllms_model = None
-    #         import types
-    #         try:
-    #             if jittorllms_model is None:
-    #                 from models import get_model
-    #                 # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
-    #                 args_dict = {'model': 'chatrwkv'}
-    #                 print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
-    #                 jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
-    #                 print('done get model')
-    #         except:
-    #             # self.child.send('[Local Message] Call jittorllms fail 不能正常加载jittorllms的参数。')
-    #             raise RuntimeError("不能正常加载jittorllms的参数！")
-    # x = GetGLMHandle()
-    # x.start()
-
-
-    # input()
--- a/requirements.txt
+++ b/requirements.txt
@@ -18,3 +18,4 @@ openai
 numpy
 arxiv
 rich
+pypdf2==2.12.1
--- a/toolbox.py
+++ b/toolbox.py
@@ -538,7 +538,11 @@ def load_chat_cookies():
    return {'api_key': API_KEY, 'llm_model': LLM_MODEL}

 def is_openai_api_key(key):
-    API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
+    CUSTOM_API_KEY_PATTERN, = get_conf('CUSTOM_API_KEY_PATTERN')
+    if len(CUSTOM_API_KEY_PATTERN) != 0:
+        API_MATCH_ORIGINAL = re.match(CUSTOM_API_KEY_PATTERN, key)
+    else:
+        API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
    return bool(API_MATCH_ORIGINAL)

 def is_azure_api_key(key):
@@ -594,7 +598,7 @@ def select_api_key(keys, llm_model):
            if is_azure_api_key(k): avail_key_list.append(k)

    if len(avail_key_list) == 0:
-        raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。您可能选择了错误的模型或请求源（右下角更换模型菜单中可切换openai,azure和api2d请求源）")
+        raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。您可能选择了错误的模型或请求源（右下角更换模型菜单中可切换openai,azure,claude,api2d等请求源）。")

    api_key = random.choice(avail_key_list) # 随机负载均衡
    return api_key
@@ -670,13 +674,14 @@ def read_single_conf_with_lru_cache(arg):

    # 在读取API_KEY时，检查一下是不是忘了改config
    if arg == 'API_KEY':
-        print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和API2D的api-key。也支持同时填写多个api-key，如API_KEY=\"openai-key1,openai-key2,api2d-key3\"")
+        print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和Azure的api-key。也支持同时填写多个api-key，如API_KEY=\"openai-key1,openai-key2,azure-key3\"")
        print亮蓝(f"[API_KEY] 您既可以在config.py中修改api-key(s)，也可以在问题输入区输入临时的api-key(s)，然后回车键提交后即可生效。")
        if is_any_api_key(r):
            print亮绿(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
        else:
-            print亮红( "[API_KEY] 正确的 API_KEY 是'sk'开头的51位密钥（OpenAI），或者 'fk'开头的41位密钥，请在config文件中修改API密钥之后再运行。")
+            print亮红( "[API_KEY] 您的 API_KEY 不满足任何一种已知的密钥格式，请在config文件中修改API密钥之后再运行。")
    if arg == 'proxies':
+        if not read_single_conf_with_lru_cache('USE_PROXY'): r = None   # 检查USE_PROXY，防止proxies单独起作用
        if r is None:
            print亮红('[PROXY] 网络代理状态：未配置。无代理状态下很可能无法访问OpenAI家族的模型。建议：检查USE_PROXY选项是否修改。')
        else:
@@ -685,6 +690,7 @@ def read_single_conf_with_lru_cache(arg):
    return r


+@lru_cache(maxsize=128)
 def get_conf(*args):
    # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
    res = []
@@ -883,4 +889,16 @@ def objload(file='objdump.tmp'):
        return
    with open(file, 'rb') as f:
        return pickle.load(f)
-    
+    
+def Singleton(cls):
+    """
+    一个单实例装饰器
+    """
+    _instance = {}
+ 
+    def _singleton(*args, **kargs):
+        if cls not in _instance:
+            _instance[cls] = cls(*args, **kargs)
+        return _instance[cls]
+ 
+    return _singleton
--- a/6
+++ b/6
@@ -1,5 +1,5 @@
 {
-  "version": 3.46,
+  "version": 3.47,
  "show_feature": true,
-  "new_feature": "临时修复theme的文件丢失问题 <-> 新增实时语音对话插件（自动断句，脱手对话） <-> 支持加载自定义的ChatGLM2微调模型 <-> 动态ChatBot窗口高度 <-> 修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件"
-}
+  "new_feature": "优化一键升级 <-> 提高arxiv翻译速度和成功率 <-> 支持自定义APIKEY格式 <-> 临时修复theme的文件丢失问题 <-> 新增实时语音对话插件（自动断句，脱手对话） <-> 支持加载自定义的ChatGLM2微调模型 <-> 动态ChatBot窗口高度 <-> 修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持"
+}
作者	SHA1	备注	提交日期
binary-husky	e4e2430255	version 3.47	2023-07-24 19:58:47 +08:00
binary-husky	1732127a28	Merge pull request #979 from fenglui/master 增加chatGLM int4配置支持小显存也可以选择chatGLM	2023-07-24 19:52:27 +08:00
binary-husky	56bb8b6498	improve re efficiency	2023-07-24 18:50:29 +08:00
binary-husky	e93b6fa3a6	Add GLM INT8	2023-07-24 18:19:57 +08:00
binary-husky	dd4ba0ea22	Merge branch 'master' of https://github.com/fenglui/gpt_academic into fenglui-master	2023-07-24 18:06:15 +08:00
binary-husky	c2701c9ce5	Merge pull request #986 from one-pr/git-clone 默认仅 clone 最新的代码，减小 git clone 的大小	2023-07-24 17:48:35 +08:00
woclass	2f019ce359	优化 README.md 中的其他 git clone	2023-07-24 15:14:48 +08:00
woclass	c5b147aeb7	默认仅 clone 最新的代码，减小 git clone 的大小	2023-07-24 15:14:42 +08:00
fenglui	5813d65e52	增加chatGLM int4配置支持小显存也可以选择chatGLM	2023-07-22 08:29:15 +08:00
binary-husky	a393edfaa4	ALLOW CUSTOM API KEY PATTERN	2023-07-21 22:49:07 +08:00
binary-husky	dd7a01cda5	Merge pull request #976 from fenglui/master fix msg.data.split(DELIMITER) exception when msg.data is int	2023-07-21 17:02:29 +08:00
fenglui	00a3b91f95	fix msg.data.split(DELIMITER) exception when msg.data is int	2023-07-21 03:51:33 +08:00
qingxu fu	61ba544282	add latex test samples	2023-07-20 19:49:23 +08:00
qingxu fu	b5b8c123e4	latex plugin stability improvement	2023-07-20 19:39:22 +08:00
qingxu fu	d9ceba959f	expand range after failure	2023-07-20 18:39:02 +08:00
qingxu fu	6b5b040701	remove pdf merge	2023-07-20 18:29:06 +08:00
qingxu fu	4f4c09a5f3	增强Latex修复能力	2023-07-20 18:08:22 +08:00
qingxu fu	067bc97cce	Merge branch 'interface-interlm' of https://github.com/binary-husky/chatgpt_academic into interface-interlm	2023-07-20 12:46:52 +08:00
qingxu fu	7368580cd6	concat pdf after translation	2023-07-20 12:46:48 +08:00
binary-husky	df90db210c	Merge branch 'master' into interface-interlm	2023-07-20 11:40:45 +08:00
binary-husky	0927ed20a2	edit default configuration	2023-07-20 11:39:35 +08:00
binary-husky	73b22f85be	compat third party gpt error handle	2023-07-20 11:09:22 +08:00
binary-husky	b8d77557b0	Update README.md	2023-07-20 10:12:42 +08:00
binary-husky	99b8fce8f3	Merge pull request #965 from QQisQQ/patch-2 解决new bing 报错200 (fix new bing error code 200 )	2023-07-19 10:15:15 +08:00
binary-husky	16364f1b2d	Merge pull request #966 from doujiang-zheng/master Add timestamp for chat_secrets.log and disable the verbose httpx log.	2023-07-19 10:14:36 +08:00
doujiang-zheng	3b88e00cfb	Add timestamp for chat_secrets.log and disable the verbose httpx log.	2023-07-19 09:43:59 +08:00
QQisQQ	0c8c539e9b	解决new bing 报错200 (fix new bing error code 200 ) modify from `16e00af9d5` works for my issue: ``` Traceback (most recent call last): File "./request_llm/bridge_newbingfree.py", line 152, in run asyncio.run(self.async_run()) File "/root/miniconda3/envs/py311/lib/python3.11/asyncio/runners.py", line 190, in run return runner.run(main) ^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/py311/lib/python3.11/asyncio/runners.py", line 118, in run return self._loop.run_until_complete(task) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/py311/lib/python3.11/asyncio/base_events.py", line 653, in run_until_complete return future.result() ^^^^^^^^^^^^^^^ File "./request_llm/bridge_newbingfree.py", line 98, in async_run async for final, response in self.newbing_model.ask_stream( File "./request_llm/edge_gpt_free.py", line 676, in ask_stream async for response in self.chat_hub.ask_stream( File "./request_llm/edge_gpt_free.py", line 456, in ask_stream self.wss = await self.session.ws_connect( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/py311/lib/python3.11/site-packages/aiohttp/client.py", line 795, in _ws_connect raise WSServerHandshakeError( aiohttp.client_exceptions.WSServerHandshakeError: 200, message='Invalid response status', url=URL('wss://sydney.bing.com/sydney/ChatHub') ```	2023-07-19 04:39:15 +08:00
binary-husky	fd549fb986	merge success	2023-07-18 19:51:13 +08:00
binary-husky	babb775cfb	interface with interlm	2023-07-18 16:33:34 +08:00