merge frontier branch (#1620)

* Zhipu sdk update 适配最新的智谱SDK，支持GLM4v (#1502) * 适配 google gemini 优化为从用户input中提取文件 * 适配最新的智谱SDK、支持glm-4v * requirements.txt fix * pending history check --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com> * Update "生成多种Mermaid图表" plugin: Separate out the file reading function (#1520) * Update crazy_functional.py with new functionality deal with PDF * Update crazy_functional.py and Mermaid.py for plugin_kwargs * Update crazy_functional.py with new chart type: mind map * Update SELECT_PROMPT and i_say_show_user messages * Update ArgsReminder message in get_crazy_functions() function * Update with read md file and update PROMPTS * Return the PROMPTS as the test found that the initial version worked best * Update Mermaid chart generation function * version 3.71 * 解决issues #1510 * Remove unnecessary text from sys_prompt in 解析历史输入 function * Remove sys_prompt message in 解析历史输入 function * Update bridge_all.py: supports gpt-4-turbo-preview (#1517) * Update bridge_all.py: supports gpt-4-turbo-preview supports gpt-4-turbo-preview * Update bridge_all.py --------- Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> * Update config.py: supports gpt-4-turbo-preview (#1516) * Update config.py: supports gpt-4-turbo-preview supports gpt-4-turbo-preview * Update config.py --------- Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> * Refactor 解析历史输入 function to handle file input * Update Mermaid chart generation functionality * rename files and functions --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com> Co-authored-by: hongyi-zhao <hongyi.zhao@gmail.com> Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> * 接入mathpix ocr功能 (#1468) * Update Latex输出PDF结果.py 借助mathpix实现了PDF翻译中文并重新编译PDF * Update config.py add mathpix appid & appkey * Add 'PDF翻译中文并重新编译PDF' feature to plugins. --------- Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> * fix zhipuai * check picture * remove glm-4 due to bug * 修改config * 检查MATHPIX_APPID * Remove unnecessary code and update function_plugins dictionary * capture non-standard token overflow * bug fix #1524 * change mermaid style * 支持mermaid 滚动放大缩小重置,鼠标滚动和拖拽 (#1530) * 支持mermaid 滚动放大缩小重置,鼠标滚动和拖拽 * 微调未果先stage一下 * update --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com> Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> * ver 3.72 * change live2d * save the status of ``clear btn` in cookie * 前端选择保持 * js ui bug fix * reset btn bug fix * update live2d tips * fix missing get_token_num method * fix live2d toggle switch * fix persistent custom btn with cookie * fix zhipuai feedback with core functionality * Refactor button update and clean up functions * tailing space removal * Fix missing MATHPIX_APPID and MATHPIX_APPKEY configuration * Prompt fix、脑图提示词优化 (#1537) * 适配 google gemini 优化为从用户input中提取文件 * 脑图提示词优化 * Fix missing MATHPIX_APPID and MATHPIX_APPKEY configuration --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com> * 优化“PDF翻译中文并重新编译PDF”插件 (#1602) * Add gemini_endpoint to API_URL_REDIRECT (#1560) * Add gemini_endpoint to API_URL_REDIRECT * Update gemini-pro and gemini-pro-vision model_info endpoints * Update to support new claude models (#1606) * Add anthropic library and update claude models * 更新bridge_claude.py文件，添加了对图片输入的支持。修复了一些bug。 * 添加Claude_3_Models变量以限制图片数量 * Refactor code to improve readability and maintainability * minor claude bug fix * more flexible one-api support * reformat config * fix one-api new access bug * dummy * compat non-standard api * version 3.73 --------- Co-authored-by: XIao <46100050+Kilig947@users.noreply.github.com> Co-authored-by: Menghuan1918 <menghuan2003@outlook.com> Co-authored-by: hongyi-zhao <hongyi.zhao@gmail.com> Co-authored-by: Hao Ma <893017927@qq.com> Co-authored-by: zeyuan huang <599012428@qq.com>
2024-03-11 17:26:09 +08:00
parent cd18663800
commit c3140ce344
85 changed files with 866 additions and 642 deletions
--- a/crazy_functions/Latex全文润色.py
+++ b/crazy_functions/Latex全文润色.py
@@ -46,7 +46,7 @@ class PaperFileGroup():
                manifest.append(path + '.polish.tex')
                f.write(res)
        return manifest
-    
+
    def zip_result(self):
        import os, time
        folder = os.path.dirname(self.file_paths[0])
@@ -59,7 +59,7 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
    from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency


-    #  <-------- 读取Latex文件，删除其中的所有注释 ----------> 
+    #  <-------- 读取Latex文件，删除其中的所有注释 ---------->
    pfg = PaperFileGroup()

    for index, fp in enumerate(file_manifest):
@@ -73,31 +73,31 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
            pfg.file_paths.append(fp)
            pfg.file_contents.append(clean_tex_content)

-    #  <-------- 拆分过长的latex文件 ----------> 
+    #  <-------- 拆分过长的latex文件 ---------->
    pfg.run_file_split(max_token_limit=1024)
    n_split = len(pfg.sp_file_contents)


-    #  <-------- 多线程润色开始 ----------> 
+    #  <-------- 多线程润色开始 ---------->
    if language == 'en':
        if mode == 'polish':
-            inputs_array = ["Below is a section from an academic paper, polish this section to meet the academic standard, " + 
-                            "improve the grammar, clarity and overall readability, do not modify any latex command such as \section, \cite and equations:" + 
+            inputs_array = ["Below is a section from an academic paper, polish this section to meet the academic standard, " +
+                            "improve the grammar, clarity and overall readability, do not modify any latex command such as \section, \cite and equations:" +
                            f"\n\n{frag}" for frag in pfg.sp_file_contents]
        else:
-            inputs_array = [r"Below is a section from an academic paper, proofread this section." + 
-                            r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " + 
-                            r"Answer me only with the revised text:" + 
+            inputs_array = [r"Below is a section from an academic paper, proofread this section." +
+                            r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " +
+                            r"Answer me only with the revised text:" +
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"Polish {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
    elif language == 'zh':
        if mode == 'polish':
-            inputs_array = [f"以下是一篇学术论文中的一段内容，请将此部分润色以满足学术标准，提高语法、清晰度和整体可读性，不要修改任何LaTeX命令，例如\section，\cite和方程式：" + 
+            inputs_array = [f"以下是一篇学术论文中的一段内容，请将此部分润色以满足学术标准，提高语法、清晰度和整体可读性，不要修改任何LaTeX命令，例如\section，\cite和方程式：" +
                            f"\n\n{frag}" for frag in pfg.sp_file_contents]
        else:
-            inputs_array = [f"以下是一篇学术论文中的一段内容，请对这部分内容进行语法矫正。不要修改任何LaTeX命令，例如\section，\cite和方程式：" + 
-                            f"\n\n{frag}" for frag in pfg.sp_file_contents] 
+            inputs_array = [f"以下是一篇学术论文中的一段内容，请对这部分内容进行语法矫正。不要修改任何LaTeX命令，例如\section，\cite和方程式：" +
+                            f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"润色 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array=["你是一位专业的中文学术论文作家。" for _ in range(n_split)]

@@ -113,7 +113,7 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
        scroller_max_len = 80
    )

-    #  <-------- 文本碎片重组为完整的tex文件，整理结果为压缩包 ----------> 
+    #  <-------- 文本碎片重组为完整的tex文件，整理结果为压缩包 ---------->
    try:
        pfg.sp_file_result = []
        for i_say, gpt_say in zip(gpt_response_collection[0::2], gpt_response_collection[1::2]):
@@ -124,7 +124,7 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
    except:
        print(trimmed_format_exc())

-    #  <-------- 整理结果，退出 ----------> 
+    #  <-------- 整理结果，退出 ---------->
    create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
    res = write_history_to_file(gpt_response_collection, file_basename=create_report_file_name)
    promote_file_to_downloadzone(res, chatbot=chatbot)
--- a/crazy_functions/Latex全文翻译.py
+++ b/crazy_functions/Latex全文翻译.py
@@ -39,7 +39,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
    import time, os, re
    from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency

-    #  <-------- 读取Latex文件，删除其中的所有注释 ----------> 
+    #  <-------- 读取Latex文件，删除其中的所有注释 ---------->
    pfg = PaperFileGroup()

    for index, fp in enumerate(file_manifest):
@@ -53,11 +53,11 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
            pfg.file_paths.append(fp)
            pfg.file_contents.append(clean_tex_content)

-    #  <-------- 拆分过长的latex文件 ----------> 
+    #  <-------- 拆分过长的latex文件 ---------->
    pfg.run_file_split(max_token_limit=1024)
    n_split = len(pfg.sp_file_contents)

-    #  <-------- 抽取摘要 ----------> 
+    #  <-------- 抽取摘要 ---------->
    # if language == 'en':
    #     abs_extract_inputs = f"Please write an abstract for this paper"

@@ -70,14 +70,14 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
    #     sys_prompt="Your job is to collect information from materials。",
    # )

-    #  <-------- 多线程润色开始 ----------> 
+    #  <-------- 多线程润色开始 ---------->
    if language == 'en->zh':
-        inputs_array = ["Below is a section from an English academic paper, translate it into Chinese, do not modify any latex command such as \section, \cite and equations:" + 
+        inputs_array = ["Below is a section from an English academic paper, translate it into Chinese, do not modify any latex command such as \section, \cite and equations:" +
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
    elif language == 'zh->en':
-        inputs_array = [f"Below is a section from a Chinese academic paper, translate it into English, do not modify any latex command such as \section, \cite and equations:" + 
+        inputs_array = [f"Below is a section from a Chinese academic paper, translate it into English, do not modify any latex command such as \section, \cite and equations:" +
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
@@ -93,7 +93,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
        scroller_max_len = 80
    )

-    #  <-------- 整理结果，退出 ----------> 
+    #  <-------- 整理结果，退出 ---------->
    create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
    res = write_history_to_file(gpt_response_collection, create_report_file_name)
    promote_file_to_downloadzone(res, chatbot=chatbot)
--- a/crazy_functions/Latex输出PDF.py
+++ b/crazy_functions/Latex输出PDF.py
@@ -1,4 +1,4 @@
-from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone
+from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone, check_repeat_upload, map_file_to_sha256
 from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip_result, gen_time_str
 from functools import partial
 import glob, os, requests, time, json, tarfile
@@ -40,7 +40,7 @@ def switch_prompt(pfg, mode, more_requirement):


 def desend_to_extracted_folder_if_exist(project_folder):
-    """ 
+    """
    Descend into the extracted folder if it exists, otherwise return the original folder.

    Args:
@@ -56,7 +56,7 @@ def desend_to_extracted_folder_if_exist(project_folder):


 def move_project(project_folder, arxiv_id=None):
-    """ 
+    """
    Create a new work folder and copy the project folder to it.

    Args:
@@ -112,9 +112,9 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
    if ('.' in txt) and ('/' not in txt) and is_float(txt[:10]):  # is arxiv ID
        txt = 'https://arxiv.org/abs/' + txt[:10]

-    if not txt.startswith('https://arxiv.org'): 
+    if not txt.startswith('https://arxiv.org'):
        return txt, None    # 是本地文件，跳过下载
-    
+
    # <-------------- inspect format ------------->
    chatbot.append([f"检测到arxiv文档连接", '尝试下载 ...'])
    yield from update_ui(chatbot=chatbot, history=history)
@@ -214,7 +214,7 @@ def pdf2tex_project(pdf_file_path):
        return None


-# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= 插件主程序1 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=    
+# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= 插件主程序1 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=


@CatchException
@@ -291,7 +291,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
    return success


-# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= 插件主程序2 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=    
+# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= 插件主程序2 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

@CatchException
 def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
@@ -326,7 +326,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
        txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
    except tarfile.ReadError as e:
        yield from update_ui_lastest_msg(
-            "无法自动下载该论文的Latex源码，请前往arxiv打开此论文下载页面，点other Formats，然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。", 
+            "无法自动下载该论文的Latex源码，请前往arxiv打开此论文下载页面，点other Formats，然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。",
            chatbot=chatbot, history=history)
        return

@@ -385,7 +385,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
    return success


-#  =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 插件主程序3  =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=   
+#  =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 插件主程序3  =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

@CatchException
 def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
@@ -438,47 +438,101 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
        return

-    # <-------------- convert pdf into tex ------------->
-    project_folder = pdf2tex_project(file_manifest[0])
+    hash_tag = map_file_to_sha256(file_manifest[0])

-    # Translate English Latex to Chinese Latex, and compile it
-    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
-    if len(file_manifest) == 0:
-        report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
-        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
-        return
+    # <-------------- check repeated pdf ------------->
+    chatbot.append([f"检查PDF是否被重复上传", "正在检查..."])
+    yield from update_ui(chatbot=chatbot, history=history)
+    repeat, project_folder = check_repeat_upload(file_manifest[0], hash_tag)

-    # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    except_flag = False

-    # <-------------- move latex project away from temp folder ------------->
-    project_folder = move_project(project_folder)
+    if repeat:
+        yield from update_ui_lastest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)

-    # <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
-    if not os.path.exists(project_folder + '/merge_translate_zh.tex'):
-        yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
-                                       chatbot, history, system_prompt, mode='translate_zh',
-                                       switch_prompt=_switch_prompt_)
+        try:
+            trans_html_file = [f for f in glob.glob(f'{project_folder}/**/*.trans.html', recursive=True)][0]
+            promote_file_to_downloadzone(trans_html_file, rename_file=None, chatbot=chatbot)

-    # <-------------- compile PDF ------------->
-    success = yield from 编译Latex(chatbot, history, main_file_original='merge',
-                                   main_file_modified='merge_translate_zh', mode='translate_zh',
-                                   work_folder_original=project_folder, work_folder_modified=project_folder,
-                                   work_folder=project_folder)
+            translate_pdf = [f for f in glob.glob(f'{project_folder}/**/merge_translate_zh.pdf', recursive=True)][0]
+            promote_file_to_downloadzone(translate_pdf, rename_file=None, chatbot=chatbot)

-    # <-------------- zip PDF ------------->
-    zip_res = zip_result(project_folder)
-    if success:
-        chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
-        yield from update_ui(chatbot=chatbot, history=history);
-        time.sleep(1)  # 刷新界面
-        promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
-    else:
-        chatbot.append((f"失败了",
-                        '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux，请检查系统字体（见Github wiki） ...'))
-        yield from update_ui(chatbot=chatbot, history=history);
-        time.sleep(1)  # 刷新界面
-        promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
+            comparison_pdf = [f for f in glob.glob(f'{project_folder}/**/comparison.pdf', recursive=True)][0]
+            promote_file_to_downloadzone(comparison_pdf, rename_file=None, chatbot=chatbot)        

-    # <-------------- we are done ------------->
-    return success
+            zip_res = zip_result(project_folder)
+            promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
+
+            return True
+        
+        except:
+            report_exception(chatbot, history, b=f"发现重复上传，但是无法找到相关文件")
+            yield from update_ui(chatbot=chatbot, history=history)
+            
+            chatbot.append([f"没有相关文件", '尝试重新翻译PDF...'])
+            yield from update_ui(chatbot=chatbot, history=history)
+
+            except_flag = True
+            
+    
+    elif not repeat or except_flag:
+        yield from update_ui_lastest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
+
+        # <-------------- convert pdf into tex ------------->
+        chatbot.append([f"解析项目: {txt}", "正在将PDF转换为tex项目，请耐心等待..."])
+        yield from update_ui(chatbot=chatbot, history=history)
+        project_folder = pdf2tex_project(file_manifest[0])
+        if project_folder is None:
+            report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"PDF转换为tex项目失败")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return False
+
+        # <-------------- translate latex file into Chinese ------------->
+        yield from update_ui_lastest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
+        file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
+        if len(file_manifest) == 0:
+            report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+            return
+
+        # <-------------- if is a zip/tar file ------------->
+        project_folder = desend_to_extracted_folder_if_exist(project_folder)
+
+        # <-------------- move latex project away from temp folder ------------->
+        project_folder = move_project(project_folder)
+
+        # <-------------- set a hash tag for repeat-checking ------------->
+        with open(pj(project_folder, hash_tag + '.tag'), 'w') as f:
+            f.write(hash_tag)
+            f.close()
+
+
+        # <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
+        if not os.path.exists(project_folder + '/merge_translate_zh.tex'):
+            yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
+                                        chatbot, history, system_prompt, mode='translate_zh',
+                                        switch_prompt=_switch_prompt_)
+
+        # <-------------- compile PDF ------------->
+        yield from update_ui_lastest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
+        success = yield from 编译Latex(chatbot, history, main_file_original='merge',
+                                    main_file_modified='merge_translate_zh', mode='translate_zh',
+                                    work_folder_original=project_folder, work_folder_modified=project_folder,
+                                    work_folder=project_folder)
+
+        # <-------------- zip PDF ------------->
+        zip_res = zip_result(project_folder)
+        if success:
+            chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
+            yield from update_ui(chatbot=chatbot, history=history);
+            time.sleep(1)  # 刷新界面
+            promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
+        else:
+            chatbot.append((f"失败了",
+                            '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux，请检查系统字体（见Github wiki） ...'))
+            yield from update_ui(chatbot=chatbot, history=history);
+            time.sleep(1)  # 刷新界面
+            promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
+
+        # <-------------- we are done ------------->
+        return success
--- a/crazy_functions/agent_fns/pipe.py
+++ b/crazy_functions/agent_fns/pipe.py
@@ -72,7 +72,7 @@ class PluginMultiprocessManager:
        if file_type.lower() in ['png', 'jpg']:
            image_path = os.path.abspath(fp)
            self.chatbot.append([
-                '检测到新生图像:', 
+                '检测到新生图像:',
                f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
            ])
            yield from update_ui(chatbot=self.chatbot, history=self.history)
@@ -114,21 +114,21 @@ class PluginMultiprocessManager:
            self.cnt = 1
            self.parent_conn = self.launch_subprocess_with_pipe() # ⭐⭐⭐
        repeated, cmd_to_autogen = self.send_command(txt)
-        if txt == 'exit': 
+        if txt == 'exit':
            self.chatbot.append([f"结束", "结束信号已明确，终止AutoGen程序。"])
            yield from update_ui(chatbot=self.chatbot, history=self.history)
            self.terminate()
            return "terminate"
-        
+
        # patience = 10
-        
+
        while True:
            time.sleep(0.5)
            if not self.alive:
                # the heartbeat watchdog might have it killed
                self.terminate()
                return "terminate"
-            if self.parent_conn.poll(): 
+            if self.parent_conn.poll():
                self.feed_heartbeat_watchdog()
                if "[GPT-Academic] 等待中" in self.chatbot[-1][-1]:
                    self.chatbot.pop(-1)  # remove the last line
@@ -152,8 +152,8 @@ class PluginMultiprocessManager:
                    yield from update_ui(chatbot=self.chatbot, history=self.history)
                if msg.cmd == "interact":
                    yield from self.overwatch_workdir_file_change()
-                    self.chatbot.append([f"程序抵达用户反馈节点.", msg.content + 
-                                         "\n\n等待您的进一步指令." + 
+                    self.chatbot.append([f"程序抵达用户反馈节点.", msg.content +
+                                         "\n\n等待您的进一步指令." +
                                         "\n\n(1) 一般情况下您不需要说什么, 清空输入区, 然后直接点击“提交”以继续. " +
                                         "\n\n(2) 如果您需要补充些什么, 输入要反馈的内容, 直接点击“提交”以继续. " +
                                         "\n\n(3) 如果您想终止程序, 输入exit, 直接点击“提交”以终止AutoGen并解锁. "
--- a/crazy_functions/agent_fns/watchdog.py
+++ b/crazy_functions/agent_fns/watchdog.py
@@ -8,7 +8,7 @@ class WatchDog():
        self.interval = interval
        self.msg = msg
        self.kill_dog = False
-    
+
    def watch(self):
        while True:
            if self.kill_dog: break
--- a/crazy_functions/chatglm微调工具.py
+++ b/crazy_functions/chatglm微调工具.py
@@ -46,7 +46,7 @@ def 微调数据集生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
    chatbot.append(("这是什么功能？", "[Local Message] 微调数据集生成"))
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    args = plugin_kwargs.get("advanced_arg", None)
-    if args is None: 
+    if args is None:
        chatbot.append(("没给定指令", "退出"))
        yield from update_ui(chatbot=chatbot, history=history); return
    else:
@@ -69,7 +69,7 @@ def 微调数据集生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
            sys_prompt_array=[arguments.system_prompt for _ in (batch)],
            max_workers=10  # OpenAI所允许的最大并行过载
        )
-    
+
        with open(txt+'.generated.json', 'a+', encoding='utf8') as f:
            for b, r in zip(batch, res[1::2]):
                f.write(json.dumps({"content":b, "summary":r}, ensure_ascii=False)+'\n')
@@ -95,12 +95,12 @@ def 启动微调(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
    chatbot.append(("这是什么功能？", "[Local Message] 微调数据集生成"))
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    args = plugin_kwargs.get("advanced_arg", None)
-    if args is None: 
+    if args is None:
        chatbot.append(("没给定指令", "退出"))
        yield from update_ui(chatbot=chatbot, history=history); return
    else:
        arguments = string_to_options(arguments=args)
-      
+


    pre_seq_len = arguments.pre_seq_len             # 128
--- a/crazy_functions/diagram_fns/file_tree.py
+++ b/crazy_functions/diagram_fns/file_tree.py
@@ -10,7 +10,7 @@ class FileNode:
        self.parenting_ship = []
        self.comment = ""
        self.comment_maxlen_show = 50
-        
+
    @staticmethod
    def add_linebreaks_at_spaces(string, interval=10):
        return '\n'.join(string[i:i+interval] for i in range(0, len(string), interval))
--- a/crazy_functions/game_fns/game_ascii_art.py
+++ b/crazy_functions/game_fns/game_ascii_art.py
@@ -8,7 +8,7 @@ import random

 class MiniGame_ASCII_Art(GptAcademicGameBaseState):
    def step(self, prompt, chatbot, history):
-        if self.step_cnt == 0:  
+        if self.step_cnt == 0:
            chatbot.append(["我画你猜（动物）", "请稍等..."])
        else:
            if prompt.strip() == 'exit':
--- a/crazy_functions/game_fns/game_interactive_story.py
+++ b/crazy_functions/game_fns/game_interactive_story.py
@@ -88,8 +88,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
        self.story = []
        chatbot.append(["互动写故事", f"这次的故事开头是：{self.headstart}"])
        self.sys_prompt_ = '你是一个想象力丰富的杰出作家。正在与你的朋友互动，一起写故事，因此你每次写的故事段落应少于300字（结局除外）。'
-        
-        
+
+
    def generate_story_image(self, story_paragraph):
        try:
            from crazy_functions.图片生成 import gen_image
@@ -98,13 +98,13 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            return f'<br/><div align="center"><img src="file={image_path}"></div>'
        except:
            return ''
-        
+
    def step(self, prompt, chatbot, history):
-        
+
        """
        首先，处理游戏初始化等特殊情况
        """
-        if self.step_cnt == 0:  
+        if self.step_cnt == 0:
            self.begin_game_step_0(prompt, chatbot, history)
            self.lock_plugin(chatbot)
            self.cur_task = 'head_start'
@@ -132,7 +132,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            inputs_ = prompts_hs.format(headstart=self.headstart)
            history_ = []
            story_paragraph = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs_, '故事开头', self.llm_kwargs, 
+                inputs_, '故事开头', self.llm_kwargs,
                chatbot, history_, self.sys_prompt_
            )
            self.story.append(story_paragraph)
@@ -147,7 +147,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            inputs_ = prompts_interact.format(previously_on_story=previously_on_story)
            history_ = []
            self.next_choices = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs_, '请在以下几种故事走向中，选择一种（当然，您也可以选择给出其他故事走向）：', self.llm_kwargs, 
+                inputs_, '请在以下几种故事走向中，选择一种（当然，您也可以选择给出其他故事走向）：', self.llm_kwargs,
                chatbot,
                history_,
                self.sys_prompt_
@@ -166,7 +166,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            inputs_ = prompts_resume.format(previously_on_story=previously_on_story, choice=self.next_choices, user_choice=prompt)
            history_ = []
            story_paragraph = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs_, f'下一段故事（您的选择是：{prompt}）。', self.llm_kwargs, 
+                inputs_, f'下一段故事（您的选择是：{prompt}）。', self.llm_kwargs,
                chatbot, history_, self.sys_prompt_
            )
            self.story.append(story_paragraph)
@@ -181,10 +181,10 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            inputs_ = prompts_interact.format(previously_on_story=previously_on_story)
            history_ = []
            self.next_choices = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs_, 
-                '请在以下几种故事走向中，选择一种。当然，您也可以给出您心中的其他故事走向。另外，如果您希望剧情立即收尾，请输入剧情走向，并以“剧情收尾”四个字提示程序。', self.llm_kwargs, 
-                chatbot, 
-                history_, 
+                inputs_,
+                '请在以下几种故事走向中，选择一种。当然，您也可以给出您心中的其他故事走向。另外，如果您希望剧情立即收尾，请输入剧情走向，并以“剧情收尾”四个字提示程序。', self.llm_kwargs,
+                chatbot,
+                history_,
                self.sys_prompt_
            )
            self.cur_task = 'user_choice'
@@ -200,7 +200,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            inputs_ = prompts_terminate.format(previously_on_story=previously_on_story, user_choice=prompt)
            history_ = []
            story_paragraph = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs_, f'故事收尾（您的选择是：{prompt}）。', self.llm_kwargs, 
+                inputs_, f'故事收尾（您的选择是：{prompt}）。', self.llm_kwargs,
                chatbot, history_, self.sys_prompt_
            )
            # # 配图
--- a/crazy_functions/game_fns/game_utils.py
+++ b/crazy_functions/game_fns/game_utils.py
@@ -5,7 +5,7 @@ def get_code_block(reply):
    import re
    pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
    matches = re.findall(pattern, reply) # find all code blocks in text
-    if len(matches) == 1: 
+    if len(matches) == 1:
        return "```" + matches[0] + "```" #  code block
    raise RuntimeError("GPT is not generating proper code.")

@@ -13,10 +13,10 @@ def is_same_thing(a, b, llm_kwargs):
    from pydantic import BaseModel, Field
    class IsSameThing(BaseModel):
        is_same_thing: bool = Field(description="determine whether two objects are same thing.", default=False)
-        
-    def run_gpt_fn(inputs, sys_prompt, history=[]): 
+
+    def run_gpt_fn(inputs, sys_prompt, history=[]):
        return predict_no_ui_long_connection(
-            inputs=inputs, llm_kwargs=llm_kwargs, 
+            inputs=inputs, llm_kwargs=llm_kwargs,
            history=history, sys_prompt=sys_prompt, observe_window=[]
        )

@@ -24,7 +24,7 @@ def is_same_thing(a, b, llm_kwargs):
    inputs_01 = "Identity whether the user input and the target is the same thing: \n target object: {a} \n user input object: {b} \n\n\n".format(a=a, b=b)
    inputs_01 += "\n\n\n Note that the user may describe the target object with a different language, e.g. cat and 猫 are the same thing."
    analyze_res_cot_01 = run_gpt_fn(inputs_01, "", [])
-    
+
    inputs_02 = inputs_01 + gpt_json_io.format_instructions
    analyze_res = run_gpt_fn(inputs_02, "", [inputs_01, analyze_res_cot_01])

--- a/crazy_functions/gen_fns/gen_fns_shared.py
+++ b/crazy_functions/gen_fns/gen_fns_shared.py
@@ -41,11 +41,11 @@ def is_function_successfully_generated(fn_path, class_name, return_dict):
        # Now you can create an instance of the class
        instance = some_class()
        return_dict['success'] = True
-        return 
+        return
    except:
        return_dict['traceback'] = trimmed_format_exc()
        return
-    
+
 def subprocess_worker(code, file_path, return_dict):
    return_dict['result'] = None
    return_dict['success'] = False
--- a/crazy_functions/ipc_fns/mp.py
+++ b/crazy_functions/ipc_fns/mp.py
@@ -1,4 +1,4 @@
-import platform 
+import platform
 import pickle
 import multiprocessing

--- a/crazy_functions/json_fns/pydantic_io.py
+++ b/crazy_functions/json_fns/pydantic_io.py
@@ -89,7 +89,7 @@ class GptJsonIO():
                 error + "\n\n" + \
                "Now, fix this json string. \n\n"
        return prompt
-    
+
    def generate_output_auto_repair(self, response, gpt_gen_fn):
        """
        response: string containing canidate json
--- a/crazy_functions/latex_fns/latex_actions.py
+++ b/crazy_functions/latex_fns/latex_actions.py
@@ -90,16 +90,16 @@ class LatexPaperSplit():
            "版权归原文作者所有。翻译内容可靠性无保障，请仔细鉴别并以原文为准。" + \
            "项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
        # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加REAME中的QQ联系开发者）
-        self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\" 
+        self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\"
        self.title = "unknown"
        self.abstract = "unknown"

    def read_title_and_abstract(self, txt):
        try:
            title, abstract = find_title_and_abs(txt)
-            if title is not None: 
+            if title is not None:
                self.title = title.replace('\n', ' ').replace('\\\\', ' ').replace('  ', '').replace('  ', '')
-            if abstract is not None: 
+            if abstract is not None:
                self.abstract = abstract.replace('\n', ' ').replace('\\\\', ' ').replace('  ', '').replace('  ', '')
        except:
            pass
@@ -111,7 +111,7 @@ class LatexPaperSplit():
        result_string = ""
        node_cnt = 0
        line_cnt = 0
-        
+
        for node in self.nodes:
            if node.preserve:
                line_cnt += node.string.count('\n')
@@ -144,7 +144,7 @@ class LatexPaperSplit():
        return result_string


-    def split(self, txt, project_folder, opts): 
+    def split(self, txt, project_folder, opts):
        """
        break down latex file to a linked list,
        each node use a preserve flag to indicate whether it should
@@ -155,7 +155,7 @@ class LatexPaperSplit():
        manager = multiprocessing.Manager()
        return_dict = manager.dict()
        p = multiprocessing.Process(
-            target=split_subprocess, 
+            target=split_subprocess,
            args=(txt, project_folder, return_dict, opts))
        p.start()
        p.join()
@@ -217,13 +217,13 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
    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 ----------> 
+    #  <-------- 寻找主tex文件 ---------->
    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)

-    #  <-------- 读取Latex文件, 将多文件tex工程融合为一个巨型tex ----------> 
+    #  <-------- 读取Latex文件, 将多文件tex工程融合为一个巨型tex ---------->
    main_tex_basename = os.path.basename(maintex)
    assert main_tex_basename.endswith('.tex')
    main_tex_basename_bare = main_tex_basename[:-4]
@@ -240,13 +240,13 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
    with open(project_folder + '/merge.tex', 'w', encoding='utf-8', errors='replace') as f:
        f.write(merged_content)

-    #  <-------- 精细切分latex文件 ----------> 
+    #  <-------- 精细切分latex文件 ---------->
    chatbot.append((f"Latex文件融合完成", f'[Local Message] 正在精细切分latex文件，这需要一段时间计算，文档越长耗时越长，请耐心等待。'))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
    lps = LatexPaperSplit()
    lps.read_title_and_abstract(merged_content)
    res = lps.split(merged_content, project_folder, opts) # 消耗时间的函数
-    #  <-------- 拆分过长的latex片段 ----------> 
+    #  <-------- 拆分过长的latex片段 ---------->
    pfg = LatexPaperFileGroup()
    for index, r in enumerate(res):
        pfg.file_paths.append('segment-' + str(index))
@@ -255,17 +255,17 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
    pfg.run_file_split(max_token_limit=1024)
    n_split = len(pfg.sp_file_contents)

-    #  <-------- 根据需要切换prompt ----------> 
+    #  <-------- 根据需要切换prompt ---------->
    inputs_array, sys_prompt_array = switch_prompt(pfg, mode)
    inputs_show_user_array = [f"{mode} {f}" for f in pfg.sp_file_tag]

    if os.path.exists(pj(project_folder,'temp.pkl')):

-        #  <-------- 【仅调试】如果存在调试缓存文件，则跳过GPT请求环节 ----------> 
+        #  <-------- 【仅调试】如果存在调试缓存文件，则跳过GPT请求环节 ---------->
        pfg = objload(file=pj(project_folder,'temp.pkl'))

    else:
-        #  <-------- gpt 多线程请求 ----------> 
+        #  <-------- gpt 多线程请求 ---------->
        history_array = [[""] for _ in range(n_split)]
        # LATEX_EXPERIMENTAL, = get_conf('LATEX_EXPERIMENTAL')
        # if LATEX_EXPERIMENTAL:
@@ -284,32 +284,32 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
            scroller_max_len = 40
        )

-        #  <-------- 文本碎片重组为完整的tex片段 ----------> 
+        #  <-------- 文本碎片重组为完整的tex片段 ---------->
        pfg.sp_file_result = []
        for i_say, gpt_say, orig_content in zip(gpt_response_collection[0::2], gpt_response_collection[1::2], pfg.sp_file_contents):
            pfg.sp_file_result.append(gpt_say)
        pfg.merge_result()

-        # <-------- 临时存储用于调试 ----------> 
+        # <-------- 临时存储用于调试 ---------->
        pfg.get_token_num = None
        objdump(pfg, file=pj(project_folder,'temp.pkl'))

    write_html(pfg.sp_file_contents, pfg.sp_file_result, chatbot=chatbot, project_folder=project_folder)

-    #  <-------- 写出文件 ----------> 
+    #  <-------- 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 ----------> 
+
+    #  <-------- 整理结果, 退出 ---------->
    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 ----------> 
+    #  <-------- 返回 ---------->
    return project_folder + f'/merge_{mode}.tex'


@@ -362,7 +362,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f

        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
-        
+
        if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
            # 只有第二步成功，才能继续下面的步骤
            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
@@ -393,9 +393,9 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
        original_pdf_success = os.path.exists(pj(work_folder_original, f'{main_file_original}.pdf'))
        modified_pdf_success = os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf'))
        diff_pdf_success     = os.path.exists(pj(work_folder, f'merge_diff.pdf'))
-        results_ += f"原始PDF编译是否成功: {original_pdf_success};" 
-        results_ += f"转化PDF编译是否成功: {modified_pdf_success};" 
-        results_ += f"对比PDF编译是否成功: {diff_pdf_success};" 
+        results_ += f"原始PDF编译是否成功: {original_pdf_success};"
+        results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
+        results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
        yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面

        if diff_pdf_success:
@@ -409,7 +409,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                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: 
+            if original_pdf_success:
                try:
                    from .latex_toolbox import merge_pdfs
                    concat_pdf = pj(work_folder_modified, f'comparison.pdf')
@@ -425,7 +425,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
            if n_fix>=max_try: break
            n_fix += 1
            can_retry, main_file_modified, buggy_lines = remove_buggy_lines(
-                file_path=pj(work_folder_modified, f'{main_file_modified}.tex'), 
+                file_path=pj(work_folder_modified, f'{main_file_modified}.tex'),
                log_path=pj(work_folder_modified, f'{main_file_modified}.log'),
                tex_name=f'{main_file_modified}.tex',
                tex_name_pure=f'{main_file_modified}',
@@ -445,14 +445,14 @@ def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):
        import shutil
        from crazy_functions.pdf_fns.report_gen_html import construct_html
        from toolbox import gen_time_str
-        ch = construct_html() 
+        ch = construct_html()
        orig = ""
        trans = ""
        final = []
-        for c,r in zip(sp_file_contents, sp_file_result): 
+        for c,r in zip(sp_file_contents, sp_file_result):
            final.append(c)
            final.append(r)
-        for i, k in enumerate(final): 
+        for i, k in enumerate(final):
            if i%2==0:
                orig = k
            if i%2==1:
--- a/crazy_functions/live_audio/aliyunASR.py
+++ b/crazy_functions/live_audio/aliyunASR.py
@@ -85,8 +85,8 @@ def write_numpy_to_wave(filename, rate, data, add_header=False):

 def is_speaker_speaking(vad, data, sample_rate):
    # Function to detect if the speaker is speaking
-    # The WebRTC VAD only accepts 16-bit mono PCM audio, 
-    # sampled at 8000, 16000, 32000 or 48000 Hz. 
+    # The WebRTC VAD only accepts 16-bit mono PCM audio,
+    # sampled at 8000, 16000, 32000 or 48000 Hz.
    # A frame must be either 10, 20, or 30 ms in duration:
    frame_duration = 30
    n_bit_each = int(sample_rate * frame_duration / 1000)*2 # x2 because audio is 16 bit (2 bytes)
@@ -94,7 +94,7 @@ def is_speaker_speaking(vad, data, sample_rate):
    for t in range(len(data)):
        if t!=0 and t % n_bit_each == 0:
            res_list.append(vad.is_speech(data[t-n_bit_each:t], sample_rate))
-    
+
    info = ''.join(['^' if r else '.' for r in res_list])
    info = info[:10]
    if any(res_list):
@@ -186,10 +186,10 @@ class AliyunASR():
        keep_alive_last_send_time = time.time()
        while not self.stop:
            # time.sleep(self.capture_interval)
-            audio = rad.read(uuid.hex) 
+            audio = rad.read(uuid.hex)
            if audio is not None:
                # convert to pcm file
-                temp_file = f'{temp_folder}/{uuid.hex}.pcm' # 
+                temp_file = f'{temp_folder}/{uuid.hex}.pcm' #
                dsdata = change_sample_rate(audio, rad.rate, NEW_SAMPLERATE) # 48000 --> 16000
                write_numpy_to_wave(temp_file, NEW_SAMPLERATE, dsdata)
                # read pcm binary
--- a/crazy_functions/live_audio/audio_io.py
+++ b/crazy_functions/live_audio/audio_io.py
@@ -3,12 +3,12 @@ from scipy import interpolate

 def Singleton(cls):
    _instance = {}
- 
+
    def _singleton(*args, **kargs):
        if cls not in _instance:
            _instance[cls] = cls(*args, **kargs)
        return _instance[cls]
- 
+
    return _singleton


@@ -39,7 +39,7 @@ class RealtimeAudioDistribution():
        else:
            res = None
        return res
-    
+
 def change_sample_rate(audio, old_sr, new_sr):
    duration = audio.shape[0] / old_sr

--- a/crazy_functions/multi_stage/multi_stage_utils.py
+++ b/crazy_functions/multi_stage/multi_stage_utils.py
@@ -40,7 +40,7 @@ class GptAcademicState():

 class GptAcademicGameBaseState():
    """
-    1. first init: __init__ -> 
+    1. first init: __init__ ->
    """
    def init_game(self, chatbot, lock_plugin):
        self.plugin_name = None
@@ -53,7 +53,7 @@ class GptAcademicGameBaseState():
            raise ValueError("callback_fn is None")
        chatbot._cookies['lock_plugin'] = self.callback_fn
        self.dump_state(chatbot)
-        
+
    def get_plugin_name(self):
        if self.plugin_name is None:
            raise ValueError("plugin_name is None")
@@ -71,7 +71,7 @@ class GptAcademicGameBaseState():
        state = chatbot._cookies.get(f'plugin_state/{plugin_name}', None)
        if state is not None:
            state = pickle.loads(state)
-        else: 
+        else:
            state = cls()
            state.init_game(chatbot, lock_plugin)
        state.plugin_name = plugin_name
@@ -79,7 +79,7 @@ class GptAcademicGameBaseState():
        state.chatbot = chatbot
        state.callback_fn = callback_fn
        return state
-    
+
    def continue_game(self, prompt, chatbot, history):
        # 游戏主体
        yield from self.step(prompt, chatbot, history)
--- a/crazy_functions/pdf_fns/breakdown_txt.py
+++ b/crazy_functions/pdf_fns/breakdown_txt.py
@@ -35,7 +35,7 @@ def cut(limit, get_token_fn, txt_tocut, must_break_at_empty_line, break_anyway=F
    remain_txt_to_cut_storage = ""
    # 为了加速计算，我们采样一个特殊的手段。当 remain_txt_to_cut > `_max` 时， 我们把 _max 后的文字转存至 remain_txt_to_cut_storage
    remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
-    
+
    while True:
        if get_token_fn(remain_txt_to_cut) <= limit:
            # 如果剩余文本的token数小于限制，那么就不用切了
--- a/crazy_functions/pdf_fns/parse_pdf.py
+++ b/crazy_functions/pdf_fns/parse_pdf.py
@@ -64,8 +64,8 @@ def produce_report_markdown(gpt_response_collection, meta, paper_meta_info, chat
            # 再做一个小修改：重新修改当前part的标题，默认用英文的
            cur_value += value
            translated_res_array.append(cur_value)
-    res_path = write_history_to_file(meta +  ["# Meta Translation" , paper_meta_info] + translated_res_array, 
-                                     file_basename = f"{gen_time_str()}-translated_only.md", 
+    res_path = write_history_to_file(meta +  ["# Meta Translation" , paper_meta_info] + translated_res_array,
+                                     file_basename = f"{gen_time_str()}-translated_only.md",
                                     file_fullname = None,
                                     auto_caption = False)
    promote_file_to_downloadzone(res_path, rename_file=os.path.basename(res_path)+'.md', chatbot=chatbot)
@@ -144,11 +144,11 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
    produce_report_markdown(gpt_response_collection, meta, paper_meta_info, chatbot, fp, generated_conclusion_files)

    # -=-=-=-=-=-=-=-= 写出HTML文件 -=-=-=-=-=-=-=-=
-    ch = construct_html() 
+    ch = construct_html()
    orig = ""
    trans = ""
    gpt_response_collection_html = copy.deepcopy(gpt_response_collection)
-    for i,k in enumerate(gpt_response_collection_html): 
+    for i,k in enumerate(gpt_response_collection_html):
        if i%2==0:
            gpt_response_collection_html[i] = inputs_show_user_array[i//2]
        else:
@@ -159,7 +159,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi

    final = ["", "", "一、论文概况",  "", "Abstract", paper_meta_info,  "二、论文翻译",  ""]
    final.extend(gpt_response_collection_html)
-    for i, k in enumerate(final): 
+    for i, k in enumerate(final):
        if i%2==0:
            orig = k
        if i%2==1:
--- a/crazy_functions/pdf_fns/parse_word.py
+++ b/crazy_functions/pdf_fns/parse_word.py
@@ -22,10 +22,10 @@ def extract_text_from_files(txt, chatbot, history):
    file_manifest = []
    excption = ""

-    if txt == "": 
+    if txt == "":
        final_result.append(txt)
        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
-    
+
    #查找输入区内容中的文件
    file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
    file_md,md_manifest,folder_md = get_files_from_everything(txt, '.md')
@@ -35,12 +35,12 @@ def extract_text_from_files(txt, chatbot, history):
    if file_doc:
        excption = "word"
        return False, final_result, page_one, file_manifest, excption
-    
+
    file_num = len(pdf_manifest) + len(md_manifest) + len(word_manifest)
    if file_num == 0:
        final_result.append(txt)
        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
-    
+
    if file_pdf:
        try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
            import fitz
@@ -61,7 +61,7 @@ def extract_text_from_files(txt, chatbot, history):
                file_content = f.read()
            file_content = file_content.encode('utf-8', 'ignore').decode()
            headers = re.findall(r'^#\s(.*)$', file_content, re.MULTILINE)  #接下来提取md中的一级/二级标题作为摘要
-            if len(headers) > 0: 
+            if len(headers) > 0:
                page_one.append("\n".join(headers)) #合并所有的标题,以换行符分割
            else:
                page_one.append("")
@@ -81,5 +81,5 @@ def extract_text_from_files(txt, chatbot, history):
            page_one.append(file_content[:200])
            final_result.append(file_content)
            file_manifest.append(os.path.relpath(fp, folder_word))
-            
+
    return True, final_result, page_one, file_manifest, excption
--- a/crazy_functions/vector_fns/vector_database.py
+++ b/crazy_functions/vector_fns/vector_database.py
@@ -28,7 +28,7 @@ EMBEDDING_DEVICE = "cpu"

 # 基于上下文的prompt模版，请务必保留"{question}"和"{context}"
 PROMPT_TEMPLATE = """已知信息：
-{context} 
+{context}

 根据上述已知信息，简洁和专业的来回答用户的问题。如果无法从中得到答案，请说 “根据已知信息无法回答该问题” 或 “没有提供足够的相关信息”，不允许在答案中添加编造成分，答案请使用中文。 问题是：{question}"""

@@ -58,7 +58,7 @@ OPEN_CROSS_DOMAIN = False
 def similarity_search_with_score_by_vector(
        self, embedding: List[float], k: int = 4
 ) -> List[Tuple[Document, float]]:
-    
+
    def seperate_list(ls: List[int]) -> List[List[int]]:
        lists = []
        ls1 = [ls[0]]
@@ -200,7 +200,7 @@ class LocalDocQA:
            return vs_path, loaded_files
        else:
            raise RuntimeError("文件加载失败，请检查文件格式是否正确")
-        
+
    def get_loaded_file(self, vs_path):
        ds = self.vector_store.docstore
        return set([ds._dict[k].metadata['source'].split(vs_path)[-1] for k in ds._dict])
@@ -290,10 +290,10 @@ class knowledge_archive_interface():
        self.threadLock.acquire()
        # import uuid
        self.current_id = id
-        self.qa_handle, self.kai_path = construct_vector_store(   
-            vs_id=self.current_id, 
+        self.qa_handle, self.kai_path = construct_vector_store(
+            vs_id=self.current_id,
            vs_path=vs_path,
-            files=file_manifest, 
+            files=file_manifest,
            sentence_size=100,
            history=[],
            one_conent="",
@@ -304,7 +304,7 @@ class knowledge_archive_interface():

    def get_current_archive_id(self):
        return self.current_id
-    
+
    def get_loaded_file(self, vs_path):
        return self.qa_handle.get_loaded_file(vs_path)

@@ -312,10 +312,10 @@ class knowledge_archive_interface():
        self.threadLock.acquire()
        if not self.current_id == id:
            self.current_id = id
-            self.qa_handle, self.kai_path = construct_vector_store(   
-                vs_id=self.current_id, 
+            self.qa_handle, self.kai_path = construct_vector_store(
+                vs_id=self.current_id,
                vs_path=vs_path,
-                files=[], 
+                files=[],
                sentence_size=100,
                history=[],
                one_conent="",
@@ -329,7 +329,7 @@ class knowledge_archive_interface():
            query = txt,
            vs_path = self.kai_path,
            score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
-            vector_search_top_k=VECTOR_SEARCH_TOP_K, 
+            vector_search_top_k=VECTOR_SEARCH_TOP_K,
            chunk_conent=True,
            chunk_size=CHUNK_SIZE,
            text2vec = self.get_chinese_text2vec(),
--- a/crazy_functions/vt_fns/vt_call_plugin.py
+++ b/crazy_functions/vt_fns/vt_call_plugin.py
@@ -35,9 +35,9 @@ def get_recent_file_prompt_support(chatbot):
    most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
    path = most_recent_uploaded['path']
    prompt =   "\nAdditional Information:\n"
-    prompt =   "In case that this plugin requires a path or a file as argument," 
-    prompt += f"it is important for you to know that the user has recently uploaded a file, located at: `{path}`" 
-    prompt += f"Only use it when necessary, otherwise, you can ignore this file." 
+    prompt =   "In case that this plugin requires a path or a file as argument,"
+    prompt += f"it is important for you to know that the user has recently uploaded a file, located at: `{path}`"
+    prompt += f"Only use it when necessary, otherwise, you can ignore this file."
    return prompt

 def get_inputs_show_user(inputs, plugin_arr_enum_prompt):
@@ -82,7 +82,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
        msg += "\n但您可以尝试再试一次\n"
        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
        return
-    
+
    # ⭐ ⭐ ⭐ 确认插件参数
    if not have_any_recent_upload_files(chatbot):
        appendix_info = ""
@@ -99,7 +99,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
    inputs = f"A plugin named {plugin_sel.plugin_selection} is selected, " + \
             "you should extract plugin_arg from the user requirement, the user requirement is: \n\n" + \
             ">> " + (txt + appendix_info).rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
-             gpt_json_io.format_instructions 
+             gpt_json_io.format_instructions
    run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
        inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
    plugin_sel = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn)
--- a/crazy_functions/vt_fns/vt_modify_config.py
+++ b/crazy_functions/vt_fns/vt_modify_config.py
@@ -10,7 +10,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
    ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
    if not ALLOW_RESET_CONFIG:
        yield from update_ui_lastest_msg(
-            lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。", 
+            lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
            chatbot=chatbot, history=history, delay=2
        )
        return
@@ -35,7 +35,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
    inputs = "Analyze how to change configuration according to following user input, answer me with json: \n\n" + \
             ">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
             gpt_json_io.format_instructions
-    
+
    run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
        inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
    user_intention = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn)
@@ -45,11 +45,11 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
    ok = (explicit_conf in txt)
    if ok:
        yield from update_ui_lastest_msg(
-            lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}", 
+            lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}",
            chatbot=chatbot, history=history, delay=1
        )
        yield from update_ui_lastest_msg(
-            lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中", 
+            lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中",
            chatbot=chatbot, history=history, delay=2
        )

@@ -69,7 +69,7 @@ def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history
    ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
    if not ALLOW_RESET_CONFIG:
        yield from update_ui_lastest_msg(
-            lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。", 
+            lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
            chatbot=chatbot, history=history, delay=2
        )
        return
--- a/crazy_functions/vt_fns/vt_state.py
+++ b/crazy_functions/vt_fns/vt_state.py
@@ -6,7 +6,7 @@ class VoidTerminalState():

    def reset_state(self):
        self.has_provided_explaination = False
- 
+
    def lock_plugin(self, chatbot):
        chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'
        chatbot._cookies['plugin_state'] = pickle.dumps(self)
--- a/crazy_functions/下载arxiv论文翻译摘要.py
+++ b/crazy_functions/下载arxiv论文翻译摘要.py
@@ -144,8 +144,8 @@ def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, hi
    try:
        import bs4
    except:
-        report_exception(chatbot, history, 
-            a = f"解析项目: {txt}", 
+        report_exception(chatbot, history,
+            a = f"解析项目: {txt}",
            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade beautifulsoup4```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
@@ -157,12 +157,12 @@ def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, hi
    try:
        pdf_path, info = download_arxiv_(txt)
    except:
-        report_exception(chatbot, history, 
-            a = f"解析项目: {txt}", 
+        report_exception(chatbot, history,
+            a = f"解析项目: {txt}",
            b = f"下载pdf文件未成功")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
-    
+
    # 翻译摘要等
    i_say =            f"请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。材料如下：{str(info)}"
    i_say_show_user =  f'请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。论文：{pdf_path}'
--- a/crazy_functions/互动小游戏.py
+++ b/crazy_functions/互动小游戏.py
@@ -12,9 +12,9 @@ def 随机小游戏(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_
    # 选择游戏
    cls = MiniGame_ResumeStory
    # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化
-    state = cls.sync_state(chatbot, 
-                           llm_kwargs, 
-                           cls, 
+    state = cls.sync_state(chatbot,
+                           llm_kwargs,
+                           cls,
                           plugin_name='MiniGame_ResumeStory',
                           callback_fn='crazy_functions.互动小游戏->随机小游戏',
                           lock_plugin=True
@@ -30,9 +30,9 @@ def 随机小游戏1(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system
    # 选择游戏
    cls = MiniGame_ASCII_Art
    # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化
-    state = cls.sync_state(chatbot, 
-                           llm_kwargs, 
-                           cls, 
+    state = cls.sync_state(chatbot,
+                           llm_kwargs,
+                           cls,
                           plugin_name='MiniGame_ASCII_Art',
                           callback_fn='crazy_functions.互动小游戏->随机小游戏1',
                           lock_plugin=True
--- a/crazy_functions/交互功能函数模板.py
+++ b/crazy_functions/交互功能函数模板.py
@@ -38,7 +38,7 @@ def 交互功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
        inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}"
        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
            inputs=inputs, inputs_show_user=inputs_show_user,
-            llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+            llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
            sys_prompt="When you want to show an image, use markdown format. e.g. ![image_description](image_url). If there are no image url provided, answer 'no image url provided'"
        )
        chatbot[-1] = [chatbot[-1][0], gpt_say]
--- a/crazy_functions/函数动态生成.py
+++ b/crazy_functions/函数动态生成.py
@@ -6,10 +6,10 @@
    - 将图像转为灰度图像
    - 将csv文件转excel表格

-Testing: 
-    - Crop the image, keeping the bottom half. 
-    - Swap the blue channel and red channel of the image. 
-    - Convert the image to grayscale. 
+Testing:
+    - Crop the image, keeping the bottom half.
+    - Swap the blue channel and red channel of the image.
+    - Convert the image to grayscale.
    - Convert the CSV file to an Excel spreadsheet.
 """

@@ -29,12 +29,12 @@ import multiprocessing

 templete = """
 ```python
-import ...  # Put dependencies here, e.g. import numpy as np. 
+import ...  # Put dependencies here, e.g. import numpy as np.

 class TerminalFunction(object): # Do not change the name of the class, The name of the class must be `TerminalFunction`

    def run(self, path):    # The name of the function must be `run`, it takes only a positional argument.
-        # rewrite the function you have just written here 
+        # rewrite the function you have just written here
        ...
        return generated_file_path
 ```
@@ -48,7 +48,7 @@ def get_code_block(reply):
    import re
    pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
    matches = re.findall(pattern, reply) # find all code blocks in text
-    if len(matches) == 1: 
+    if len(matches) == 1:
        return matches[0].strip('python') #  code block
    for match in matches:
        if 'class TerminalFunction' in match:
@@ -68,8 +68,8 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):

    # 第一步
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=i_say, inputs_show_user=i_say, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=demo, 
+        inputs=i_say, inputs_show_user=i_say,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=demo,
        sys_prompt= r"You are a world-class programmer."
    )
    history.extend([i_say, gpt_say])
@@ -82,33 +82,33 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
    ]
    i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. "
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=i_say, inputs_show_user=inputs_show_user, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 
+        inputs=i_say, inputs_show_user=inputs_show_user,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
        sys_prompt= r"You are a programmer. You need to replace `...` with valid packages, do not give `...` in your answer!"
    )
    code_to_return = gpt_say
    history.extend([i_say, gpt_say])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
-    
+
    # # 第三步
    # i_say = "Please list to packages to install to run the code above. Then show me how to use `try_install_deps` function to install them."
    # i_say += 'For instance. `try_install_deps(["opencv-python", "scipy", "numpy"])`'
    # installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive(
-    #     inputs=i_say, inputs_show_user=inputs_show_user, 
-    #     llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 
+    #     inputs=i_say, inputs_show_user=inputs_show_user,
+    #     llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
    #     sys_prompt= r"You are a programmer."
    # )

-    # # # 第三步  
+    # # # 第三步
    # i_say = "Show me how to use `pip` to install packages to run the code above. "
    # i_say += 'For instance. `pip install -r opencv-python scipy numpy`'
    # installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive(
-    #     inputs=i_say, inputs_show_user=i_say, 
-    #     llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 
+    #     inputs=i_say, inputs_show_user=i_say,
+    #     llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
    #     sys_prompt= r"You are a programmer."
    # )
    installation_advance = ""
-    
+
    return code_to_return, installation_advance, txt, file_type, llm_kwargs, chatbot, history


@@ -117,7 +117,7 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
 def for_immediate_show_off_when_possible(file_type, fp, chatbot):
    if file_type in ['png', 'jpg']:
        image_path = os.path.abspath(fp)
-        chatbot.append(['这是一张图片, 展示如下:',  
+        chatbot.append(['这是一张图片, 展示如下:',
            f'本地文件地址: <br/>`{image_path}`<br/>'+
            f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
        ])
@@ -177,7 +177,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
        chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
        return  # 2. 如果没有文件
-    
+
    # 读取文件
    file_type = file_list[0].split('.')[-1]

@@ -185,7 +185,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
    if is_the_upload_folder(txt):
        yield from update_ui_lastest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
        return
-    
+
    # 开始干正事
    MAX_TRY = 3
    for j in range(MAX_TRY):  # 最多重试5次
@@ -238,7 +238,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
            # chatbot.append(["如果是缺乏依赖，请参考以下建议", installation_advance])
            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
            return
-        
+
        # 顺利完成，收尾
        res = str(res)
        if os.path.exists(res):
@@ -248,5 +248,5 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
        else:
            chatbot.append(["执行成功了，结果是一个字符串", "结果：" + res])
-            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新   
+            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新

--- a/crazy_functions/命令行助手.py
+++ b/crazy_functions/命令行助手.py
@@ -21,8 +21,8 @@ def 命令行助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
    i_say = "请写bash命令实现以下功能：" + txt
    # 开始
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=i_say, inputs_show_user=txt, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        inputs=i_say, inputs_show_user=txt,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
        sys_prompt="你是一个Linux大师级用户。注意，当我要求你写bash命令时，尽可能地仅用一行命令解决我的要求。"
    )
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
--- a/crazy_functions/图片生成.py
+++ b/crazy_functions/图片生成.py
@@ -7,7 +7,7 @@ def gen_image(llm_kwargs, prompt, resolution="1024x1024", model="dall-e-2", qual
    from request_llms.bridge_all import model_info

    proxies = get_conf('proxies')
-    # Set up OpenAI API key and model 
+    # Set up OpenAI API key and model
    api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
    chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
    # 'https://api.openai.com/v1/chat/completions'
@@ -113,7 +113,7 @@ def 图片生成_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, sys
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    resolution = plugin_kwargs.get("advanced_arg", '1024x1024')
    image_url, image_path = gen_image(llm_kwargs, prompt, resolution)
-    chatbot.append([prompt,  
+    chatbot.append([prompt,
        f'图像中转网址: <br/>`{image_url}`<br/>'+
        f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
        f'本地文件地址: <br/>`{image_path}`<br/>'+
@@ -144,7 +144,7 @@ def 图片生成_DALLE3(prompt, llm_kwargs, plugin_kwargs, chatbot, history, sys
        elif part in ['vivid', 'natural']:
            style = part
    image_url, image_path = gen_image(llm_kwargs, prompt, resolution, model="dall-e-3", quality=quality, style=style)
-    chatbot.append([prompt,  
+    chatbot.append([prompt,
        f'图像中转网址: <br/>`{image_url}`<br/>'+
        f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
        f'本地文件地址: <br/>`{image_path}`<br/>'+
@@ -164,7 +164,7 @@ class ImageEditState(GptAcademicState):
        confirm = (len(file_manifest) >= 1 and file_manifest[0].endswith('.png') and os.path.exists(file_manifest[0]))
        file = None if not confirm else file_manifest[0]
        return confirm, file
-    
+
    def lock_plugin(self, chatbot):
        chatbot._cookies['lock_plugin'] = 'crazy_functions.图片生成->图片修改_DALLE2'
        self.dump_state(chatbot)
--- a/crazy_functions/多智能体.py
+++ b/crazy_functions/多智能体.py
@@ -57,11 +57,11 @@ def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
        if get_conf("AUTOGEN_USE_DOCKER"):
            import docker
    except:
-        chatbot.append([ f"处理任务: {txt}", 
+        chatbot.append([ f"处理任务: {txt}",
            f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pyautogen docker```。"])
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
-    
+
    # 尝试导入依赖，如果缺少依赖，则给出安装建议
    try:
        import autogen
@@ -72,7 +72,7 @@ def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
        chatbot.append([f"处理任务: {txt}", f"缺少docker运行环境！"])
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
-    
+
    # 解锁插件
    chatbot.get_cookies()['lock_plugin'] = None
    persistent_class_multi_user_manager = GradioMultiuserManagerForPersistentClasses()
--- a/crazy_functions/对话历史存档.py
+++ b/crazy_functions/对话历史存档.py
@@ -66,7 +66,7 @@ def read_file_to_chat(chatbot, history, file_name):
        i_say, gpt_say = h.split('<hr style="border-top: dotted 3px #ccc;">')
        chatbot.append([i_say, gpt_say])
    chatbot.append([f"存档文件详情？", f"[Local Message] 载入对话{len(html)}条，上下文{len(history)}条。"])
-    return chatbot, history    
+    return chatbot, history

@CatchException
 def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
@@ -80,7 +80,7 @@ def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
    user_request    当前用户的请求信息（IP地址等）
    """

-    chatbot.append(("保存当前对话", 
+    chatbot.append(("保存当前对话",
        f"[Local Message] {write_chat_to_file(chatbot, history)}，您可以调用下拉菜单中的“载入对话历史存档”还原当下的对话。"))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新

@@ -108,9 +108,9 @@ def 载入对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
        if txt == "": txt = '空空如也的输入栏'
        import glob
        local_history = "<br/>".join([
-            "`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`" 
+            "`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`"
            for f in glob.glob(
-                f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html', 
+                f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html',
                recursive=True
            )])
        chatbot.append([f"正在查找对话历史文件（html格式）: {txt}", f"找不到任何html文件: {txt}。但本地存储了以下历史文件，您可以将任意一个文件路径粘贴到输入区，然后重试：<br/>{local_history}"])
@@ -139,7 +139,7 @@ def 删除所有本地对话历史记录(txt, llm_kwargs, plugin_kwargs, chatbot

    import glob, os
    local_history = "<br/>".join([
-        "`"+hide_cwd(f)+"`" 
+        "`"+hide_cwd(f)+"`"
        for f in glob.glob(
            f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html', recursive=True
        )])
--- a/crazy_functions/总结word文档.py
+++ b/crazy_functions/总结word文档.py
@@ -40,10 +40,10 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
            i_say = f'请对下面的文章片段用中文做概述，文件名是{os.path.relpath(fp, project_folder)}，文章内容是 ```{paper_frag}```'
            i_say_show_user = f'请对下面的文章片段做概述: {os.path.abspath(fp)}的第{i+1}/{len(paper_fragments)}个片段。'
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs=i_say, 
-                inputs_show_user=i_say_show_user, 
+                inputs=i_say,
+                inputs_show_user=i_say_show_user,
                llm_kwargs=llm_kwargs,
-                chatbot=chatbot, 
+                chatbot=chatbot,
                history=[],
                sys_prompt="总结文章。"
            )
@@ -56,10 +56,10 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
        if len(paper_fragments) > 1:
            i_say = f"根据以上的对话，总结文章{os.path.abspath(fp)}的主要内容。"
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs=i_say, 
-                inputs_show_user=i_say, 
+                inputs=i_say,
+                inputs_show_user=i_say,
                llm_kwargs=llm_kwargs,
-                chatbot=chatbot, 
+                chatbot=chatbot,
                history=this_paper_history,
                sys_prompt="总结文章。"
            )
--- a/crazy_functions/批量Markdown翻译.py
+++ b/crazy_functions/批量Markdown翻译.py
@@ -53,7 +53,7 @@ class PaperFileGroup():
 def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'):
    from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency

-    #  <-------- 读取Markdown文件，删除其中的所有注释 ----------> 
+    #  <-------- 读取Markdown文件，删除其中的所有注释 ---------->
    pfg = PaperFileGroup()

    for index, fp in enumerate(file_manifest):
@@ -63,23 +63,23 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
            pfg.file_paths.append(fp)
            pfg.file_contents.append(file_content)

-    #  <-------- 拆分过长的Markdown文件 ----------> 
+    #  <-------- 拆分过长的Markdown文件 ---------->
    pfg.run_file_split(max_token_limit=1500)
    n_split = len(pfg.sp_file_contents)

-    #  <-------- 多线程翻译开始 ----------> 
+    #  <-------- 多线程翻译开始 ---------->
    if language == 'en->zh':
-        inputs_array = ["This is a Markdown file, translate it into Chinese, do not modify any existing Markdown commands:" + 
+        inputs_array = ["This is a Markdown file, translate it into Chinese, do not modify any existing Markdown commands:" +
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
    elif language == 'zh->en':
-        inputs_array = [f"This is a Markdown file, translate it into English, do not modify any existing Markdown commands:" + 
+        inputs_array = [f"This is a Markdown file, translate it into English, do not modify any existing Markdown commands:" +
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
    else:
-        inputs_array = [f"This is a Markdown file, translate it into {language}, do not modify any existing Markdown commands, only answer me with translated results:" + 
+        inputs_array = [f"This is a Markdown file, translate it into {language}, do not modify any existing Markdown commands, only answer me with translated results:" +
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
        sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
@@ -103,7 +103,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
    except:
        logging.error(trimmed_format_exc())

-    #  <-------- 整理结果，退出 ----------> 
+    #  <-------- 整理结果，退出 ---------->
    create_report_file_name = gen_time_str() + f"-chatgpt.md"
    res = write_history_to_file(gpt_response_collection, file_basename=create_report_file_name)
    promote_file_to_downloadzone(res, chatbot=chatbot)
@@ -255,7 +255,7 @@ def Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history,
        report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
-    
+
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    language = plugin_kwargs.get("advanced_arg", 'Chinese')
    yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language=language)
--- a/crazy_functions/批量总结PDF文档.py
+++ b/crazy_functions/批量总结PDF文档.py
@@ -17,7 +17,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
        file_content, page_one = read_and_clean_pdf_text(file_name) # （尝试）按照章节切割PDF
        file_content = file_content.encode('utf-8', 'ignore').decode()   # avoid reading non-utf8 chars
        page_one = str(page_one).encode('utf-8', 'ignore').decode()  # avoid reading non-utf8 chars
-        
+
        TOKEN_LIMIT_PER_FRAGMENT = 2500

        from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
@@ -25,7 +25,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
        page_one_fragments = breakdown_text_to_satisfy_token_limit(txt=str(page_one), limit=TOKEN_LIMIT_PER_FRAGMENT//4, llm_model=llm_kwargs['llm_model'])
        # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
        paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
-        
+
        ############################## <第 1 步，从摘要中提取高价值信息，放到history中> ##################################
        final_results = []
        final_results.append(paper_meta)
@@ -44,10 +44,10 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
            i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} Chinese characters: {paper_fragments[i]}"
            i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} Chinese characters: {paper_fragments[i][:200]}"
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user,  # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
-                                                                                llm_kwargs, chatbot, 
+                                                                                llm_kwargs, chatbot,
                                                                                history=["The main idea of the previous section is?", last_iteration_result], # 迭代上一次的结果
                                                                                sys_prompt="Extract the main idea of this section with Chinese."  # 提示
-                                                                                ) 
+                                                                                )
            iteration_results.append(gpt_say)
            last_iteration_result = gpt_say

@@ -67,15 +67,15 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
    - (2):What are the past methods? What are the problems with them? Is the approach well motivated?
    - (3):What is the research methodology proposed in this paper?
    - (4):On what task and what performance is achieved by the methods in this paper? Can the performance support their goals?
-Follow the format of the output that follows:                  
+Follow the format of the output that follows:
 1. Title: xxx\n\n
 2. Authors: xxx\n\n
 3. Affiliation: xxx\n\n
 4. Keywords: xxx\n\n
 5. Urls: xxx or xxx , xxx \n\n
 6. Summary: \n\n
-    - (1):xxx;\n 
-    - (2):xxx;\n 
+    - (1):xxx;\n
+    - (2):xxx;\n
    - (3):xxx;\n
    - (4):xxx.\n\n
 Be sure to use Chinese answers (proper nouns need to be marked in English), statements as concise and academic as possible,
@@ -85,8 +85,8 @@ do not have too much repetitive information, numerical values using the original
        file_write_buffer.extend(final_results)
        i_say, final_results = input_clipping(i_say, final_results, max_token_limit=2000)
        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-            inputs=i_say, inputs_show_user='开始最终总结', 
-            llm_kwargs=llm_kwargs, chatbot=chatbot, history=final_results, 
+            inputs=i_say, inputs_show_user='开始最终总结',
+            llm_kwargs=llm_kwargs, chatbot=chatbot, history=final_results,
            sys_prompt= f"Extract the main idea of this paper with less than {NUM_OF_WORD} Chinese characters"
        )
        final_results.append(gpt_say)
@@ -114,8 +114,8 @@ def 批量总结PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
    try:
        import fitz
    except:
-        report_exception(chatbot, history, 
-            a = f"解析项目: {txt}", 
+        report_exception(chatbot, history,
+            a = f"解析项目: {txt}",
            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
@@ -134,7 +134,7 @@ def 批量总结PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst

    # 搜索需要处理的文件清单
    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.pdf', recursive=True)]
-    
+
    # 如果没找到任何文件
    if len(file_manifest) == 0:
        report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或.pdf文件: {txt}")
--- a/crazy_functions/批量总结PDF文档pdfminer.py
+++ b/crazy_functions/批量总结PDF文档pdfminer.py
@@ -85,10 +85,10 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
            msg = '正常'
            # ** gpt request **
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-                inputs=i_say, 
-                inputs_show_user=i_say_show_user, 
+                inputs=i_say,
+                inputs_show_user=i_say_show_user,
                llm_kwargs=llm_kwargs,
-                chatbot=chatbot, 
+                chatbot=chatbot,
                history=[],
                sys_prompt="总结文章。"
            )  # 带超时倒计时
@@ -106,10 +106,10 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
        msg = '正常'
        # ** gpt request **
        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-            inputs=i_say, 
-            inputs_show_user=i_say, 
+            inputs=i_say,
+            inputs_show_user=i_say,
            llm_kwargs=llm_kwargs,
-            chatbot=chatbot, 
+            chatbot=chatbot,
            history=history,
            sys_prompt="总结文章。"
        )  # 带超时倒计时
@@ -138,8 +138,8 @@ def 批量总结PDF文档pdfminer(txt, llm_kwargs, plugin_kwargs, chatbot, histo
    try:
        import pdfminer, bs4
    except:
-        report_exception(chatbot, history, 
-            a = f"解析项目: {txt}", 
+        report_exception(chatbot, history,
+            a = f"解析项目: {txt}",
            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pdfminer beautifulsoup4```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
--- a/crazy_functions/批量翻译PDF文档_NOUGAT.py
+++ b/crazy_functions/批量翻译PDF文档_NOUGAT.py
@@ -76,8 +76,8 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
    success_mmd, file_manifest_mmd, _ = get_files_from_everything(txt, type='.mmd')
    success = success or success_mmd
    file_manifest += file_manifest_mmd
-    chatbot.append(["文件列表：", ", ".join([e.split('/')[-1] for e in file_manifest])]); 
-    yield from update_ui(      chatbot=chatbot, history=history) 
+    chatbot.append(["文件列表：", ", ".join([e.split('/')[-1] for e in file_manifest])]);
+    yield from update_ui(      chatbot=chatbot, history=history)
    # 检测输入参数，如没有给定输入参数，直接退出
    if not success:
        if txt == "": txt = '空空如也的输入栏'
--- a/crazy_functions/批量翻译PDF文档_多线程.py
+++ b/crazy_functions/批量翻译PDF文档_多线程.py
@@ -68,7 +68,7 @@ def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwa
        with open(grobid_json_res, 'w+', encoding='utf8') as f:
            f.write(json.dumps(article_dict, indent=4, ensure_ascii=False))
        promote_file_to_downloadzone(grobid_json_res, chatbot=chatbot)
-        
+
        if article_dict is None: raise RuntimeError("解析PDF失败，请检查PDF是否损坏。")
        yield from translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG)
    chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
@@ -97,7 +97,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,

        # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
        paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
-        
+
        # 单线，获取文章meta信息
        paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive(
            inputs=f"以下是一篇学术论文的基础信息，请从中提取出“标题”、“收录会议或期刊”、“作者”、“摘要”、“编号”、“作者邮箱”这六个部分。请用markdown格式输出，最后用中文翻译摘要部分。请提取：{paper_meta}",
@@ -121,7 +121,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
        )
        gpt_response_collection_md = copy.deepcopy(gpt_response_collection)
        # 整理报告的格式
-        for i,k in enumerate(gpt_response_collection_md): 
+        for i,k in enumerate(gpt_response_collection_md):
            if i%2==0:
                gpt_response_collection_md[i] = f"\n\n---\n\n ## 原文[{i//2}/{len(gpt_response_collection_md)//2}]： \n\n {paper_fragments[i//2].replace('#', '')}  \n\n---\n\n ## 翻译[{i//2}/{len(gpt_response_collection_md)//2}]：\n "
            else:
@@ -139,18 +139,18 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,

        # write html
        try:
-            ch = construct_html() 
+            ch = construct_html()
            orig = ""
            trans = ""
            gpt_response_collection_html = copy.deepcopy(gpt_response_collection)
-            for i,k in enumerate(gpt_response_collection_html): 
+            for i,k in enumerate(gpt_response_collection_html):
                if i%2==0:
                    gpt_response_collection_html[i] = paper_fragments[i//2].replace('#', '')
                else:
                    gpt_response_collection_html[i] = gpt_response_collection_html[i]
            final = ["论文概况", paper_meta_info.replace('# ', '### '),  "二、论文翻译",  ""]
            final.extend(gpt_response_collection_html)
-            for i, k in enumerate(final): 
+            for i, k in enumerate(final):
                if i%2==0:
                    orig = k
                if i%2==1:
--- a/crazy_functions/数学动画生成manim.py
+++ b/crazy_functions/数学动画生成manim.py
@@ -27,7 +27,7 @@ def eval_manim(code):

    class_name = get_class_name(code)

-    try: 
+    try:
        time_str = gen_time_str()
        subprocess.check_output([sys.executable, '-c', f"from gpt_log.MyAnimation import {class_name}; {class_name}().render()"])
        shutil.move(f'media/videos/1080p60/{class_name}.mp4', f'gpt_log/{class_name}-{time_str}.mp4')
@@ -36,7 +36,7 @@ def eval_manim(code):
        output = e.output.decode()
        print(f"Command returned non-zero exit status {e.returncode}: {output}.")
        return f"Evaluating python script failed: {e.output}."
-    except: 
+    except:
        print('generating mp4 failed')
        return "Generating mp4 failed."

@@ -45,7 +45,7 @@ def get_code_block(reply):
    import re
    pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
    matches = re.findall(pattern, reply) # find all code blocks in text
-    if len(matches) != 1: 
+    if len(matches) != 1:
        raise RuntimeError("GPT is not generating proper code.")
    return matches[0].strip('python') #  code block

@@ -61,7 +61,7 @@ def 动画生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
    user_request    当前用户的请求信息（IP地址等）
    """
    # 清空历史，以免输入溢出
-    history = []    
+    history = []

    # 基本信息：功能、贡献者
    chatbot.append([
@@ -73,24 +73,24 @@ def 动画生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
    # 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 = f'Generate a animation to show: ' + txt
    demo = ["Here is some examples of manim", examples_of_manim()]
    _, demo = input_clipping(inputs="", history=demo, max_token_limit=2560)
    # 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=demo, 
+        inputs=i_say, inputs_show_user=i_say,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=demo,
        sys_prompt=
        r"Write a animation script with 3blue1brown's manim. "+
-        r"Please begin with `from manim import *`. " + 
+        r"Please begin with `from manim import *`. " +
        r"Answer me with a code block wrapped by ```."
    )
    chatbot.append(["开始生成动画", "..."])
    history.extend([i_say, gpt_say])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
-    
+
    # 将代码转为动画
    code = get_code_block(gpt_say)
    res = eval_manim(code)
--- a/crazy_functions/理解PDF文档内容.py
+++ b/crazy_functions/理解PDF文档内容.py
@@ -15,7 +15,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
    file_content, page_one = read_and_clean_pdf_text(file_name) # （尝试）按照章节切割PDF
    file_content = file_content.encode('utf-8', 'ignore').decode()   # avoid reading non-utf8 chars
    page_one = str(page_one).encode('utf-8', 'ignore').decode()  # avoid reading non-utf8 chars
-    
+
    TOKEN_LIMIT_PER_FRAGMENT = 2500

    from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
@@ -23,7 +23,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
    page_one_fragments = breakdown_text_to_satisfy_token_limit(txt=str(page_one), limit=TOKEN_LIMIT_PER_FRAGMENT//4, llm_model=llm_kwargs['llm_model'])
    # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
    paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
-    
+
    ############################## <第 1 步，从摘要中提取高价值信息，放到history中> ##################################
    final_results = []
    final_results.append(paper_meta)
@@ -42,10 +42,10 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
        i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i]}"
        i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i][:200]} ...."
        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user,  # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
-                                                                           llm_kwargs, chatbot, 
+                                                                           llm_kwargs, chatbot,
                                                                           history=["The main idea of the previous section is?", last_iteration_result], # 迭代上一次的结果
                                                                           sys_prompt="Extract the main idea of this section, answer me with Chinese."  # 提示
-                                                                        ) 
+                                                                        )
        iteration_results.append(gpt_say)
        last_iteration_result = gpt_say

@@ -76,8 +76,8 @@ def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chat
    try:
        import fitz
    except:
-        report_exception(chatbot, history, 
-            a = f"解析项目: {txt}", 
+        report_exception(chatbot, history,
+            a = f"解析项目: {txt}",
            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
--- a/crazy_functions/生成函数注释.py
+++ b/crazy_functions/生成函数注释.py
@@ -16,7 +16,7 @@ def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
        chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

-        if not fast_debug: 
+        if not fast_debug:
            msg = '正常'
            # ** gpt request **
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
@@ -27,7 +27,7 @@ def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
            yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
            if not fast_debug: time.sleep(2)

-    if not fast_debug: 
+    if not fast_debug:
        res = write_history_to_file(history)
        promote_file_to_downloadzone(res, chatbot=chatbot)
        chatbot.append(("完成了吗？", res))
--- a/crazy_functions/生成多种Mermaid图表.py
+++ b/crazy_functions/生成多种Mermaid图表.py
@@ -179,15 +179,15 @@ def 解析历史输入(history,llm_kwargs,file_manifest,chatbot,plugin_kwargs):
        i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words in Chinese: {txt[i]}"
        i_say_show_user = f"[{i+1}/{n_txt}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {txt[i][:200]} ...."
        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user,  # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
-                                                                           llm_kwargs, chatbot, 
+                                                                           llm_kwargs, chatbot,
                                                                           history=["The main content of the previous section is?", last_iteration_result], # 迭代上一次的结果
                                                                           sys_prompt="Extracts the main content from the text section where it is located for graphing purposes, answer me with Chinese."  # 提示
-                                                                        ) 
+                                                                        )
        results.append(gpt_say)
        last_iteration_result = gpt_say
    ############################## <第 2 步，根据整理的摘要选择图表类型> ##################################
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
-    gpt_say = plugin_kwargs.get("advanced_arg", "")     #将图表类型参数赋值为插件参数  
+    gpt_say = plugin_kwargs.get("advanced_arg", "")     #将图表类型参数赋值为插件参数
    results_txt = '\n'.join(results)    #合并摘要
    if gpt_say not in ['1','2','3','4','5','6','7','8','9']:    #如插件参数不正确则使用对话模型判断
        i_say_show_user = f'接下来将判断适合的图表类型,如连续3次判断失败将会使用流程图进行绘制'; gpt_say = "[Local Message] 收到。"   # 用户提示
@@ -198,7 +198,7 @@ def 解析历史输入(history,llm_kwargs,file_manifest,chatbot,plugin_kwargs):
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
                inputs=i_say,
                inputs_show_user=i_say_show_user,
-                llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+                llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
                sys_prompt=""
            )
            if gpt_say in ['1','2','3','4','5','6','7','8','9']:     #判断返回是否正确
@@ -228,12 +228,12 @@ def 解析历史输入(history,llm_kwargs,file_manifest,chatbot,plugin_kwargs):
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
        inputs=i_say,
        inputs_show_user=i_say_show_user,
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
        sys_prompt=""
    )
    history.append(gpt_say)
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
-    
+
@CatchException
 def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
    """
@@ -249,11 +249,11 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,

    # 基本信息：功能、贡献者
    chatbot.append([
-        "函数插件功能？", 
+        "函数插件功能？",
        "根据当前聊天历史或指定的路径文件(文件内容优先)绘制多种mermaid图表，将会由对话模型首先判断适合的图表类型，随后绘制图表。\
        \n您也可以使用插件参数指定绘制的图表类型,函数插件贡献者: Menghuan1918"])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-    
+
    if os.path.exists(txt):     #如输入区无内容则直接解析历史记录
        from crazy_functions.pdf_fns.parse_word import extract_text_from_files
        file_exist, final_result, page_one, file_manifest, excption = extract_text_from_files(txt, chatbot, history)
@@ -264,15 +264,15 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,

    if excption != "":
        if excption == "word":
-            report_exception(chatbot, history, 
-                a = f"解析项目: {txt}", 
+            report_exception(chatbot, history,
+                a = f"解析项目: {txt}",
                b = f"找到了.doc文件，但是该文件格式不被支持，请先转化为.docx格式。")
-            
+
        elif excption == "pdf":
-            report_exception(chatbot, history, 
-                a = f"解析项目: {txt}", 
+            report_exception(chatbot, history,
+                a = f"解析项目: {txt}",
                b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。")
-        
+
        elif excption == "word_pip":
                report_exception(chatbot, history,
                    a=f"解析项目: {txt}",
--- a/crazy_functions/知识库问答.py
+++ b/crazy_functions/知识库问答.py
@@ -9,7 +9,7 @@ install_msg ="""

 3. python -m pip install unstructured[all-docs] --upgrade

-4. python -c 'import nltk; nltk.download("punkt")' 
+4. python -c 'import nltk; nltk.download("punkt")'
 """

@CatchException
@@ -56,7 +56,7 @@ def 知识库文件注入(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        chatbot.append(["没有找到任何可读取文件", "当前支持的格式包括: txt, md, docx, pptx, pdf, json等"])
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
-    
+
    # < -------------------预热文本向量化模组--------------- >
    chatbot.append(['<br/>'.join(file_manifest), "正在预热文本向量化模组, 如果是第一次运行, 将消耗较长时间下载中文向量化模型..."])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -109,8 +109,8 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
    chatbot.append((txt, f'[知识库 {kai_id}] ' + prompt))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=prompt, inputs_show_user=txt, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        inputs=prompt, inputs_show_user=txt,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
        sys_prompt=system_prompt
    )
    history.extend((prompt, gpt_say))
--- a/crazy_functions/联网的ChatGPT.py
+++ b/crazy_functions/联网的ChatGPT.py
@@ -40,10 +40,10 @@ def scrape_text(url, proxies) -> str:
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
        'Content-Type': 'text/plain',
    }
-    try: 
+    try:
        response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
        if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
-    except: 
+    except:
        return "无法连接到该网页"
    soup = BeautifulSoup(response.text, "html.parser")
    for script in soup(["script", "style"]):
@@ -66,7 +66,7 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
    user_request    当前用户的请求信息（IP地址等）
    """
    history = []    # 清空历史，以免输入溢出
-    chatbot.append((f"请结合互联网信息回答以下问题：{txt}", 
+    chatbot.append((f"请结合互联网信息回答以下问题：{txt}",
                    "[Local Message] 请注意，您正在调用一个[函数插件]的模板，该模板可以实现ChatGPT联网信息综合。该函数面向希望实现更多有趣功能的开发者，它可以作为创建新功能函数的模板。您若希望分享新的功能模组，请不吝PR！"))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新

@@ -91,13 +91,13 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
    # ------------- < 第3步：ChatGPT综合 > -------------
    i_say = f"从以上搜索结果中抽取信息，然后回答问题：{txt}"
    i_say, history = input_clipping(    # 裁剪输入，从最长的条目开始裁剪，防止爆token
-        inputs=i_say, 
-        history=history, 
+        inputs=i_say,
+        history=history,
        max_token_limit=model_info[llm_kwargs['llm_model']]['max_token']*3//4
    )
    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=history, 
+        inputs=i_say, inputs_show_user=i_say,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
        sys_prompt="请从给定的若干条搜索结果中抽取信息，对最相关的两个搜索结果进行总结，然后回答问题。"
    )
    chatbot[-1] = (i_say, gpt_say)
--- a/crazy_functions/虚空终端.py
+++ b/crazy_functions/虚空终端.py
@@ -33,7 +33,7 @@ explain_msg = """
    - 「请调用插件，解析python源代码项目，代码我刚刚打包拖到上传区了」
    - 「请问Transformer网络的结构是怎样的？」

-2. 您可以打开插件下拉菜单以了解本项目的各种能力。    
+2. 您可以打开插件下拉菜单以了解本项目的各种能力。

 3. 如果您使用「调用插件xxx」、「修改配置xxx」、「请问」等关键词，您的意图可以被识别的更准确。

@@ -67,7 +67,7 @@ class UserIntention(BaseModel):
 def chat(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
        inputs=txt, inputs_show_user=txt,
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
        sys_prompt=system_prompt
    )
    chatbot[-1] = [txt, gpt_say]
@@ -115,7 +115,7 @@ def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
    if is_the_upload_folder(txt):
        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=False)
        appendix_msg = "\n\n**很好，您已经上传了文件**，现在请您描述您的需求。"
-        
+
    if is_certain or (state.has_provided_explaination):
        # 如果意图明确，跳过提示环节
        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
@@ -152,7 +152,7 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        analyze_res = run_gpt_fn(inputs, "")
        try:
            user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
-            lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}", 
+            lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
        except JsonStringError as e:
            yield from update_ui_lastest_msg(
                lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型（{llm_kwargs['llm_model']}）不能理解您的意图", chatbot=chatbot, history=history, delay=0)
@@ -161,7 +161,7 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        pass

    yield from update_ui_lastest_msg(
-        lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}", 
+        lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
        chatbot=chatbot, history=history, delay=0)

    # 用户意图: 修改本项目的配置
--- a/crazy_functions/解析项目源代码.py
+++ b/crazy_functions/解析项目源代码.py
@@ -82,13 +82,13 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
            inputs=inputs, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
            history=this_iteration_history_feed,   # 迭代之前的分析
            sys_prompt="你是一个程序架构分析师，正在分析一个项目的源代码。" + sys_prompt_additional)
-        
+
        diagram_code = make_diagram(this_iteration_files, result, this_iteration_history_feed)
        summary = "请用一句话概括这些文件的整体功能。\n\n" + diagram_code
        summary_result = yield from request_gpt_model_in_new_thread_with_ui_alive(
-            inputs=summary, 
-            inputs_show_user=summary, 
-            llm_kwargs=llm_kwargs, 
+            inputs=summary,
+            inputs_show_user=summary,
+            llm_kwargs=llm_kwargs,
            chatbot=chatbot,
            history=[i_say, result],   # 迭代之前的分析
            sys_prompt="你是一个程序架构分析师，正在分析一个项目的源代码。" + sys_prompt_additional)
--- a/crazy_functions/询问多个大语言模型.py
+++ b/crazy_functions/询问多个大语言模型.py
@@ -20,8 +20,8 @@ def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
    # llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
    llm_kwargs['llm_model'] = MULTI_QUERY_LLM_MODELS # 支持任意数量的llm接口，用&符号分隔
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=txt, inputs_show_user=txt, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 
+        inputs=txt, inputs_show_user=txt,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
        sys_prompt=system_prompt,
        retry_times_at_unknown_error=0
    )
@@ -52,8 +52,8 @@ def 同时问询_指定模型(txt, llm_kwargs, plugin_kwargs, chatbot, history,
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新

    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=txt, inputs_show_user=txt, 
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 
+        inputs=txt, inputs_show_user=txt,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
        sys_prompt=system_prompt,
        retry_times_at_unknown_error=0
    )
--- a/crazy_functions/语音助手.py
+++ b/crazy_functions/语音助手.py
@@ -39,7 +39,7 @@ class AsyncGptTask():
        try:
            MAX_TOKEN_ALLO = 2560
            i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO)
-            gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt, 
+            gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt,
                                                            observe_window=observe_window[index], console_slience=True)
        except ConnectionAbortedError as token_exceed_err:
            print('至少一个线程任务Token溢出而失败', e)
@@ -120,7 +120,7 @@ class InterviewAssistant(AliyunASR):
            yield from update_ui(chatbot=chatbot, history=history)      # 刷新界面
            self.plugin_wd.feed()

-            if self.event_on_result_chg.is_set(): 
+            if self.event_on_result_chg.is_set():
                # called when some words have finished
                self.event_on_result_chg.clear()
                chatbot[-1] = list(chatbot[-1])
@@ -151,7 +151,7 @@ class InterviewAssistant(AliyunASR):
                # add gpt task 创建子线程请求gpt，避免线程阻塞
                history = chatbot2history(chatbot)
                self.agt.add_async_gpt_task(self.buffered_sentence, len(chatbot)-1, llm_kwargs, history, system_prompt)
-                
+
                self.buffered_sentence = ""
                chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
                yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
--- a/crazy_functions/谷歌检索小助手.py
+++ b/crazy_functions/谷歌检索小助手.py
@@ -20,10 +20,10 @@ def get_meta_information(url, chatbot, history):
    proxies = get_conf('proxies')
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
-        'Accept-Encoding': 'gzip, deflate, br', 
+        'Accept-Encoding': 'gzip, deflate, br',
        'Accept-Language': 'en-US,en;q=0.9,zh-CN;q=0.8,zh;q=0.7',
        'Cache-Control':'max-age=0',
-        'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7', 
+        'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
        'Connection': 'keep-alive'
    }
    try:
@@ -95,7 +95,7 @@ def get_meta_information(url, chatbot, history):
        )
        try: paper = next(search.results())
        except: paper = None
-        
+
        is_match = paper is not None and string_similar(title, paper.title) > 0.90

        # 如果在Arxiv上匹配失败，检索文章的历史版本的题目
@@ -146,8 +146,8 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        import math
        from bs4 import BeautifulSoup
    except:
-        report_exception(chatbot, history, 
-            a = f"解析项目: {txt}", 
+        report_exception(chatbot, history,
+            a = f"解析项目: {txt}",
            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade beautifulsoup4 arxiv```。")
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return
@@ -163,7 +163,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        if len(meta_paper_info_list[:batchsize]) > 0:
            i_say = "下面是一些学术文献的数据，提取出以下内容：" + \
            "1、英文题目；2、中文题目翻译；3、作者；4、arxiv公开（is_paper_in_arxiv）；4、引用数量（cite）；5、中文摘要翻译。" + \
-            f"以下是信息源：{str(meta_paper_info_list[:batchsize])}" 
+            f"以下是信息源：{str(meta_paper_info_list[:batchsize])}"

            inputs_show_user = f"请分析此页面中出现的所有文章：{txt}，这是第{batch+1}批"
            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
@@ -175,11 +175,11 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
            history.extend([ f"第{batch+1}批", gpt_say ])
            meta_paper_info_list = meta_paper_info_list[batchsize:]

-    chatbot.append(["状态？", 
+    chatbot.append(["状态？",
        "已经全部完成，您可以试试让AI写一个Related Works，例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."])
    msg = '正常'
    yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
    path = write_history_to_file(history)
    promote_file_to_downloadzone(path, chatbot=chatbot)
-    chatbot.append(("完成了吗？", path)); 
+    chatbot.append(("完成了吗？", path));
    yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
--- a/crazy_functions/高级功能函数模板.py
+++ b/crazy_functions/高级功能函数模板.py
@@ -40,7 +40,7 @@ def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
    """
    history = []    # 清空历史，以免输入溢出
    chatbot.append((
-        "您正在调用插件：历史上的今天", 
+        "您正在调用插件：历史上的今天",
        "[Local Message] 请注意，您正在调用一个[函数插件]的模板，该函数面向希望实现更多有趣功能的开发者，它可以作为创建新功能函数的模板（该函数只有20多行代码）。此外我们也提供可同步处理大量文件的多线程Demo供您参考。您若希望分享新的功能模组，请不吝PR！" + 高阶功能模板函数示意图))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
    for i in range(5):
@@ -48,8 +48,8 @@ def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
        currentDay = (datetime.date.today() + datetime.timedelta(days=i)).day
        i_say = f'历史中哪些事件发生在{currentMonth}月{currentDay}日？列举两条并发送相关图片。发送图片时，请使用Markdown，将Unsplash API中的PUT_YOUR_QUERY_HERE替换成描述该事件的一个最重要的单词。'
        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=[], 
+            inputs=i_say, inputs_show_user=i_say,
+            llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
            sys_prompt="当你想发送一张照片时，请使用Markdown, 并且不要有反斜线, 不要用代码块。使用 Unsplash API (https://source.unsplash.com/1280x720/? < PUT_YOUR_QUERY_HERE >)。"
        )
        chatbot[-1] = (i_say, gpt_say)
@@ -84,15 +84,15 @@ def 测试图表渲染(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
    history = []    # 清空历史，以免输入溢出
    chatbot.append(("这是什么功能？", "一个测试mermaid绘制图表的功能，您可以在输入框中输入一些关键词，然后使用mermaid+llm绘制图表。"))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
-    
+
    if txt == "": txt = "空白的输入栏" # 调皮一下
-    
+
    i_say_show_user = f'请绘制有关“{txt}”的逻辑关系图。'
    i_say = PROMPT.format(subject=txt)
    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
        inputs=i_say,
        inputs_show_user=i_say_show_user,
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
        sys_prompt=""
    )
    history.append(i_say); history.append(gpt_say)