Latex全文润色
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				@ -72,7 +72,7 @@ def patch_and_restart(path):
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        time.sleep(1)
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					        time.sleep(1)
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        print(i)
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					        print(i)
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    print(' ------------------------------ -----------------------------------')
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					    print(' ------------------------------ -----------------------------------')
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    os.execl(sys.executable, 'python', 'main.py')
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					    os.execl(sys.executable, *sys.argv)
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def get_current_version():
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					def get_current_version():
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@ -31,7 +31,7 @@ CODE_HIGHLIGHT = True
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LAYOUT = "LEFT-RIGHT"  # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布局)
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					LAYOUT = "LEFT-RIGHT"  # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布局)
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# 发送请求到OpenAI后,等待多久判定为超时
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					# 发送请求到OpenAI后,等待多久判定为超时
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TIMEOUT_SECONDS = 25
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					TIMEOUT_SECONDS = 30
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# 网页的端口, -1代表随机端口
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					# 网页的端口, -1代表随机端口
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WEB_PORT = -1
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					WEB_PORT = -1
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@ -76,6 +76,8 @@ def get_crazy_functions():
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    from crazy_functions.谷歌检索小助手 import 谷歌检索小助手
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					    from crazy_functions.谷歌检索小助手 import 谷歌检索小助手
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    from crazy_functions.理解PDF文档内容 import 理解PDF文档内容
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					    from crazy_functions.理解PDF文档内容 import 理解PDF文档内容
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    from crazy_functions.理解PDF文档内容 import 理解PDF文档内容标准文件输入
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					    from crazy_functions.理解PDF文档内容 import 理解PDF文档内容标准文件输入
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					    from crazy_functions.Latex全文润色 import Latex英文润色
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					    from crazy_functions.Latex全文润色 import Latex中文润色
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    function_plugins.update({
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					    function_plugins.update({
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        "批量翻译PDF文档(多线程)": {
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					        "批量翻译PDF文档(多线程)": {
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@ -114,6 +116,18 @@ def get_crazy_functions():
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            "AsButton": False,  # 加入下拉菜单中
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					            "AsButton": False,  # 加入下拉菜单中
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            "Function": HotReload(理解PDF文档内容标准文件输入)
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					            "Function": HotReload(理解PDF文档内容标准文件输入)
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        },
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					        },
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					        "英文Latex项目全文润色(输入路径或上传压缩包)": {
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					            # HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
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					            "Color": "stop",
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					            "AsButton": False,  # 加入下拉菜单中
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					            "Function": HotReload(Latex英文润色)
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					        },
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					        # "中文Latex项目全文润色(输入路径或上传压缩包)": {
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					        #     # HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
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					        #     "Color": "stop",
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					        #     "AsButton": False,  # 加入下拉菜单中
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					        #     "Function": HotReload(Latex中文润色)
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					        # },
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    })
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					    })
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    ###################### 第三组插件 ###########################
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					    ###################### 第三组插件 ###########################
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@ -2,51 +2,125 @@ from toolbox import update_ui
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from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
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					from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
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fast_debug = False
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					fast_debug = False
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					class PaperFileGroup():
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					    def __init__(self):
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					        self.file_paths = []
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					        self.file_contents = []
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					        self.sp_file_contents = []
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					        self.sp_file_index = []
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					        self.sp_file_tag = []
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					        # count_token
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					        import tiktoken
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					        from toolbox import get_conf
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					        enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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					        def get_token_num(txt): return len(enc.encode(txt))
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					        self.get_token_num = get_token_num
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					    def run_file_split(self, max_token_limit=1900):
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					        """
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					        将长文本分离开来
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					        """
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					        for index, file_content in enumerate(self.file_contents):
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					            if self.get_token_num(file_content) < max_token_limit:
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					                self.sp_file_contents.append(file_content)
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					                self.sp_file_index.append(index)
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					                self.sp_file_tag.append(self.file_paths[index])
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					            else:
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					                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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					                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
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					                for j, segment in enumerate(segments):
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					                    self.sp_file_contents.append(segment)
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					                    self.sp_file_index.append(index)
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					                    self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.tex")
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					        print('Segmentation: done')
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					def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'):
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					    import time, os, re
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					    from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
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					    #  <-------- 读取Latex文件,删除其中的所有注释 ----------> 
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					    pfg = PaperFileGroup()
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def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
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    import time, glob, os
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    print('begin analysis on:', file_manifest)
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    for index, fp in enumerate(file_manifest):
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					    for index, fp in enumerate(file_manifest):
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        with open(fp, 'r', encoding='utf-8') as f:
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					        with open(fp, 'r', encoding='utf-8') as f:
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            file_content = f.read()
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					            file_content = f.read()
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					            # 定义注释的正则表达式
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					            comment_pattern = r'%.*'
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					            # 使用正则表达式查找注释,并替换为空字符串
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					            clean_tex_content = re.sub(comment_pattern, '', file_content)
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					            # 记录删除注释后的文本
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					            pfg.file_paths.append(fp)
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					            pfg.file_contents.append(clean_tex_content)
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        prefix = "接下来请你逐文件分析下面的论文文件,概括其内容" if index==0 else ""
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					    #  <-------- 拆分过长的latex文件 ----------> 
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        i_say = prefix + f'请对下面的文章片段用中文做一个概述,文件名是{os.path.relpath(fp, project_folder)},文章内容是 ```{file_content}```'
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					    pfg.run_file_split(max_token_limit=1024)
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        i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}'
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					    n_split = len(pfg.sp_file_contents)
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        chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
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					    #  <-------- 抽取摘要 ----------> 
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					    # if language == 'en':
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					    #     abs_extract_inputs = f"Please write an abstract for this paper"
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					    # # 单线,获取文章meta信息
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					    # paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive(
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					    #     inputs=abs_extract_inputs,
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					    #     inputs_show_user=f"正在抽取摘要信息。",
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					    #     llm_kwargs=llm_kwargs,
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					    #     chatbot=chatbot, history=[],
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					    #     sys_prompt="Your job is to collect information from materials。",
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					    # )
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					    #  <-------- 多线程润色开始(第一次) ----------> 
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					    if language == 'en':
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					        inputs_array = [f"Below is an academic paper, polish the writing to meet the academic style, "+
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					                        f"improve the spelling, grammar, clarity, concision and overall readability. " + 
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					                        f"The paper begins now: \n{frag}" for frag in pfg.sp_file_contents]
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					        inputs_show_user_array = [f"Polish {f}" for f in pfg.sp_file_tag]
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					        sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
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					    elif language == 'zh':
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					        inputs_array = [f"这里有一个使用Latex格式的学术论文,请把写作风格要求的学术风格进行润色,改进拼写、语法、清晰度、简洁度和整体可读性。" + 
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					                        f"论文现在开始:\n{frag}" for frag in pfg.sp_file_contents]
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					        inputs_show_user_array = [f"润色 {f}" for f in pfg.sp_file_tag]
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					        sys_prompt_array=["你是一位专业的学术论文作家。润色以下论文。输出中保留Latex格式。" for _ in range(n_split)]
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					    gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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					        inputs_array=inputs_array,
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					        inputs_show_user_array=inputs_show_user_array,
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					        llm_kwargs=llm_kwargs,
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					        chatbot=chatbot,
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					        history_array=[[""] for _ in range(n_split)],
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					        sys_prompt_array=sys_prompt_array,
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					        max_workers=10,  # OpenAI所允许的最大并行过载
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					        scroller_max_len = 80
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					    )
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					    create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
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					    res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name)
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					    history = gpt_response_collection
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					    chatbot.append((f"{fp}完成了吗?", res))
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    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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					    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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        if not fast_debug: 
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            msg = '正常'
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            # ** gpt request **
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            gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, llm_kwargs, plugin_kwargs, history=[])   # 带超时倒计时
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            chatbot[-1] = (i_say_show_user, gpt_say)
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            history.append(i_say_show_user); history.append(gpt_say)
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            yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg) # 刷新界面
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            if not fast_debug: time.sleep(2)
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    all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
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    i_say = f'根据以上你自己的分析,对全文进行概括,用学术性语言写一段中文摘要,然后再写一段英文摘要(包括{all_file})。'
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    chatbot.append((i_say, "[Local Message] waiting gpt response."))
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    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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    if not fast_debug: 
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        msg = '正常'
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        # ** gpt request **
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        gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, llm_kwargs, plugin_kwargs, history=history)   # 带超时倒计时
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        chatbot[-1] = (i_say, gpt_say)
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        history.append(i_say); history.append(gpt_say)
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        yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg) # 刷新界面
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        res = write_results_to_file(history)
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        chatbot.append(("完成了吗?", res))
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        yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg) # 刷新界面
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@CatchException
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					@CatchException
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def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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					def Latex英文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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					    # 基本信息:功能、贡献者
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					    chatbot.append([
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					        "函数插件功能?",
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					        "对整个Latex项目进行润色。函数插件贡献者: Binary-Husky"])
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					    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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					    # 尝试导入依赖,如果缺少依赖,则给出安装建议
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					    try:
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					        import tiktoken
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					    except:
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					        report_execption(chatbot, history,
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					                         a=f"解析项目: {txt}",
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					                         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 tiktoken```。")
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					        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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					        return
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    history = []    # 清空历史,以免输入溢出
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					    history = []    # 清空历史,以免输入溢出
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    import glob, os
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					    import glob, os
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    if os.path.exists(txt):
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					    if os.path.exists(txt):
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@ -56,11 +130,47 @@ def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
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        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
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					        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
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        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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					        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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        return
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					        return
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    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] # + \
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					    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
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                    # [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
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                    # [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
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    if len(file_manifest) == 0:
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					    if len(file_manifest) == 0:
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        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
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					        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
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        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
					        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
				
			||||||
        return
 | 
					        return
 | 
				
			||||||
    yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
 | 
					    yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en')
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					@CatchException
 | 
				
			||||||
 | 
					def Latex中文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
 | 
				
			||||||
 | 
					    # 基本信息:功能、贡献者
 | 
				
			||||||
 | 
					    chatbot.append([
 | 
				
			||||||
 | 
					        "函数插件功能?",
 | 
				
			||||||
 | 
					        "对整个Latex项目进行润色。函数插件贡献者: Binary-Husky"])
 | 
				
			||||||
 | 
					    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    # 尝试导入依赖,如果缺少依赖,则给出安装建议
 | 
				
			||||||
 | 
					    try:
 | 
				
			||||||
 | 
					        import tiktoken
 | 
				
			||||||
 | 
					    except:
 | 
				
			||||||
 | 
					        report_execption(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 tiktoken```。")
 | 
				
			||||||
 | 
					        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
				
			||||||
 | 
					        return
 | 
				
			||||||
 | 
					    history = []    # 清空历史,以免输入溢出
 | 
				
			||||||
 | 
					    import glob, os
 | 
				
			||||||
 | 
					    if os.path.exists(txt):
 | 
				
			||||||
 | 
					        project_folder = txt
 | 
				
			||||||
 | 
					    else:
 | 
				
			||||||
 | 
					        if txt == "": txt = '空空如也的输入栏'
 | 
				
			||||||
 | 
					        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
 | 
				
			||||||
 | 
					        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
				
			||||||
 | 
					        return
 | 
				
			||||||
 | 
					    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
 | 
				
			||||||
 | 
					    if len(file_manifest) == 0:
 | 
				
			||||||
 | 
					        report_execption(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
 | 
				
			||||||
 | 
					    yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh')
 | 
				
			||||||
@ -80,7 +80,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
 | 
				
			|||||||
                    history=history, sys_prompt=sys_prompt, observe_window=mutable)
 | 
					                    history=history, sys_prompt=sys_prompt, observe_window=mutable)
 | 
				
			||||||
                return result
 | 
					                return result
 | 
				
			||||||
            except ConnectionAbortedError as token_exceeded_error:
 | 
					            except ConnectionAbortedError as token_exceeded_error:
 | 
				
			||||||
                # 【第二种情况】:Token溢出,
 | 
					                # 【第二种情况】:Token溢出
 | 
				
			||||||
                if handle_token_exceed:
 | 
					                if handle_token_exceed:
 | 
				
			||||||
                    exceeded_cnt += 1
 | 
					                    exceeded_cnt += 1
 | 
				
			||||||
                    # 【选择处理】 尝试计算比例,尽可能多地保留文本
 | 
					                    # 【选择处理】 尝试计算比例,尽可能多地保留文本
 | 
				
			||||||
@ -97,7 +97,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
 | 
				
			|||||||
                    mutable[0] += f"[Local Message] 警告,在执行过程中遭遇问题, Traceback:\n\n{tb_str}\n\n"
 | 
					                    mutable[0] += f"[Local Message] 警告,在执行过程中遭遇问题, Traceback:\n\n{tb_str}\n\n"
 | 
				
			||||||
                    return mutable[0] # 放弃
 | 
					                    return mutable[0] # 放弃
 | 
				
			||||||
            except:
 | 
					            except:
 | 
				
			||||||
                # 【第三种情况】:其他错误
 | 
					                # 【第三种情况】:其他错误:重试几次
 | 
				
			||||||
                tb_str = '```\n' + traceback.format_exc() + '```'
 | 
					                tb_str = '```\n' + traceback.format_exc() + '```'
 | 
				
			||||||
                mutable[0] += f"[Local Message] 警告,在执行过程中遭遇问题, Traceback:\n\n{tb_str}\n\n"
 | 
					                mutable[0] += f"[Local Message] 警告,在执行过程中遭遇问题, Traceback:\n\n{tb_str}\n\n"
 | 
				
			||||||
                if retry_op > 0: 
 | 
					                if retry_op > 0: 
 | 
				
			||||||
@ -119,7 +119,11 @@ def request_gpt_model_in_new_thread_with_ui_alive(
 | 
				
			|||||||
            break
 | 
					            break
 | 
				
			||||||
        chatbot[-1] = [chatbot[-1][0], mutable[0]]
 | 
					        chatbot[-1] = [chatbot[-1][0], mutable[0]]
 | 
				
			||||||
        yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
 | 
					        yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
 | 
				
			||||||
    return future.result()
 | 
					
 | 
				
			||||||
 | 
					    final_result = future.result()
 | 
				
			||||||
 | 
					    chatbot[-1] = [chatbot[-1][0], final_result]
 | 
				
			||||||
 | 
					    yield from update_ui(chatbot=chatbot, history=[]) # 如果最后成功了,则删除报错信息
 | 
				
			||||||
 | 
					    return final_result
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
 | 
					def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
 | 
				
			||||||
 | 
				
			|||||||
@ -96,7 +96,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_
 | 
				
			|||||||
    # 基本信息:功能、贡献者
 | 
					    # 基本信息:功能、贡献者
 | 
				
			||||||
    chatbot.append([
 | 
					    chatbot.append([
 | 
				
			||||||
        "函数插件功能?",
 | 
					        "函数插件功能?",
 | 
				
			||||||
        "批量总结PDF文档。函数插件贡献者: Binary-Husky(二进制哈士奇)"])
 | 
					        "批量总结PDF文档。函数插件贡献者: Binary-Husky"])
 | 
				
			||||||
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
					    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 | 
				
			||||||
 | 
					
 | 
				
			||||||
    # 尝试导入依赖,如果缺少依赖,则给出安装建议
 | 
					    # 尝试导入依赖,如果缺少依赖,则给出安装建议
 | 
				
			||||||
@ -185,11 +185,9 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
 | 
				
			|||||||
        final.extend(gpt_response_collection)
 | 
					        final.extend(gpt_response_collection)
 | 
				
			||||||
        create_report_file_name = f"{os.path.basename(fp)}.trans.md"
 | 
					        create_report_file_name = f"{os.path.basename(fp)}.trans.md"
 | 
				
			||||||
        res = write_results_to_file(final, file_name=create_report_file_name)
 | 
					        res = write_results_to_file(final, file_name=create_report_file_name)
 | 
				
			||||||
        generated_conclusion_files.append(
 | 
					        generated_conclusion_files.append(f'./gpt_log/{create_report_file_name}')
 | 
				
			||||||
            f'./gpt_log/{create_report_file_name}')
 | 
					 | 
				
			||||||
        chatbot.append((f"{fp}完成了吗?", res))
 | 
					        chatbot.append((f"{fp}完成了吗?", res))
 | 
				
			||||||
        msg = "完成"
 | 
					        yield from update_ui(chatbot=chatbot, history=chatbot) # 刷新界面
 | 
				
			||||||
        yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg) # 刷新界面
 | 
					 | 
				
			||||||
 | 
					
 | 
				
			||||||
    # 准备文件的下载
 | 
					    # 准备文件的下载
 | 
				
			||||||
    import shutil
 | 
					    import shutil
 | 
				
			||||||
 | 
				
			|||||||
@ -45,6 +45,7 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
 | 
				
			|||||||
    batchsize = 16  # 10个文件为一组
 | 
					    batchsize = 16  # 10个文件为一组
 | 
				
			||||||
    report_part_2 = []
 | 
					    report_part_2 = []
 | 
				
			||||||
    previous_iteration_files = []
 | 
					    previous_iteration_files = []
 | 
				
			||||||
 | 
					    last_iteration_result = ""
 | 
				
			||||||
    while True:
 | 
					    while True:
 | 
				
			||||||
        if len(file_manifest) == 0: break
 | 
					        if len(file_manifest) == 0: break
 | 
				
			||||||
        this_iteration_file_manifest = file_manifest[:batchsize]
 | 
					        this_iteration_file_manifest = file_manifest[:batchsize]
 | 
				
			||||||
@ -59,12 +60,13 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
 | 
				
			|||||||
        i_say = f'根据以上分析,对程序的整体功能和构架重新做出概括。然后用一张markdown表格整理每个文件的功能(包括{previous_iteration_files_string})。'
 | 
					        i_say = f'根据以上分析,对程序的整体功能和构架重新做出概括。然后用一张markdown表格整理每个文件的功能(包括{previous_iteration_files_string})。'
 | 
				
			||||||
        inputs_show_user = f'根据以上分析,对程序的整体功能和构架重新做出概括,由于输入长度限制,可能需要分组处理,本组文件为 {current_iteration_focus} + 已经汇总的文件组。'
 | 
					        inputs_show_user = f'根据以上分析,对程序的整体功能和构架重新做出概括,由于输入长度限制,可能需要分组处理,本组文件为 {current_iteration_focus} + 已经汇总的文件组。'
 | 
				
			||||||
        this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection) 
 | 
					        this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection) 
 | 
				
			||||||
        this_iteration_history.extend(report_part_2)
 | 
					        this_iteration_history.extend(last_iteration_result)
 | 
				
			||||||
        result = yield from request_gpt_model_in_new_thread_with_ui_alive(
 | 
					        result = 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, 
 | 
					            inputs=i_say, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot, 
 | 
				
			||||||
            history=this_iteration_history,   # 迭代之前的分析
 | 
					            history=this_iteration_history,   # 迭代之前的分析
 | 
				
			||||||
            sys_prompt="你是一个程序架构分析师,正在分析一个源代码项目。")
 | 
					            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。")
 | 
				
			||||||
        report_part_2.extend([i_say, result])
 | 
					        report_part_2.extend([i_say, result])
 | 
				
			||||||
 | 
					        last_iteration_result = result
 | 
				
			||||||
 | 
					
 | 
				
			||||||
        file_manifest = file_manifest[batchsize:]
 | 
					        file_manifest = file_manifest[batchsize:]
 | 
				
			||||||
        gpt_response_collection = gpt_response_collection[batchsize*2:]
 | 
					        gpt_response_collection = gpt_response_collection[batchsize*2:]
 | 
				
			||||||
 | 
				
			|||||||
							
								
								
									
										2
									
								
								theme.py
									
									
									
									
									
								
							
							
						
						
									
										2
									
								
								theme.py
									
									
									
									
									
								
							@ -154,10 +154,12 @@ advanced_css = """
 | 
				
			|||||||
    padding: 1em;
 | 
					    padding: 1em;
 | 
				
			||||||
    margin: 1em 2em 1em 0.5em;
 | 
					    margin: 1em 2em 1em 0.5em;
 | 
				
			||||||
}
 | 
					}
 | 
				
			||||||
 | 
					
 | 
				
			||||||
"""
 | 
					"""
 | 
				
			||||||
 | 
					
 | 
				
			||||||
if CODE_HIGHLIGHT:
 | 
					if CODE_HIGHLIGHT:
 | 
				
			||||||
    advanced_css += """
 | 
					    advanced_css += """
 | 
				
			||||||
 | 
					
 | 
				
			||||||
.hll { background-color: #ffffcc }
 | 
					.hll { background-color: #ffffcc }
 | 
				
			||||||
.c { color: #3D7B7B; font-style: italic } /* Comment */
 | 
					.c { color: #3D7B7B; font-style: italic } /* Comment */
 | 
				
			||||||
.err { border: 1px solid #FF0000 } /* Error */
 | 
					.err { border: 1px solid #FF0000 } /* Error */
 | 
				
			||||||
 | 
				
			|||||||
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		Reference in New Issue
	
	Block a user