update multi-language module
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@ -1,87 +1,70 @@
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from toolbox import CatchException, update_ui, gen_time_str
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from .crazy_utils import input_clipping
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import copy, json
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prompt = """
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I have to achieve some functionalities by calling one of the functions below.
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Your job is to find the correct funtion to use to satisfy my requirement,
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and then write python code to call this function with correct parameters.
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These are functions you are allowed to choose from:
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1.
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功能描述: 总结音视频内容
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调用函数: ConcludeAudioContent(txt, llm_kwargs)
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参数说明:
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txt: 音频文件的路径
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llm_kwargs: 模型参数, 永远给定None
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2.
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功能描述: 将每次对话记录写入Markdown格式的文件中
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调用函数: WriteMarkdown()
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3.
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功能描述: 将指定目录下的PDF文件从英文翻译成中文
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调用函数: BatchTranslatePDFDocuments_MultiThreaded(txt, llm_kwargs)
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参数说明:
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txt: PDF文件所在的路径
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llm_kwargs: 模型参数, 永远给定None
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4.
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功能描述: 根据文本使用GPT模型生成相应的图像
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调用函数: ImageGeneration(txt, llm_kwargs)
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参数说明:
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txt: 图像生成所用到的提示文本
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llm_kwargs: 模型参数, 永远给定None
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5.
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功能描述: 对输入的word文档进行摘要生成
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调用函数: SummarizingWordDocuments(input_path, output_path)
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参数说明:
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input_path: 待处理的word文档路径
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output_path: 摘要生成后的文档路径
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You should always anwser with following format:
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----------------
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Code:
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```
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class AutoAcademic(object):
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def __init__(self):
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self.selected_function = "FILL_CORRECT_FUNCTION_HERE" # e.g., "GenerateImage"
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self.txt = "FILL_MAIN_PARAMETER_HERE" # e.g., "荷叶上的蜻蜓"
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self.llm_kwargs = None
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```
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Explanation:
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只有GenerateImage和生成图像相关, 因此选择GenerateImage函数。
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----------------
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Now, this is my requirement:
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"""
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def get_fn_lib():
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return {
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"BatchTranslatePDFDocuments_MultiThreaded": ("crazy_functions.批量翻译PDF文档_多线程", "批量翻译PDF文档"),
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"SummarizingWordDocuments": ("crazy_functions.总结word文档", "总结word文档"),
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"ImageGeneration": ("crazy_functions.图片生成", "图片生成"),
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"TranslateMarkdownFromEnglishToChinese": ("crazy_functions.批量Markdown翻译", "Markdown中译英"),
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"SummaryAudioVideo": ("crazy_functions.总结音视频", "总结音视频"),
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"BatchTranslatePDFDocuments_MultiThreaded": {
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"module": "crazy_functions.批量翻译PDF文档_多线程",
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"function": "批量翻译PDF文档",
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"description": "Translate PDF Documents",
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"arg_1_description": "A path containing pdf files.",
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},
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"SummarizingWordDocuments": {
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"module": "crazy_functions.总结word文档",
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"function": "总结word文档",
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"description": "Summarize Word Documents",
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"arg_1_description": "A path containing Word files.",
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},
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"ImageGeneration": {
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"module": "crazy_functions.图片生成",
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"function": "图片生成",
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"description": "Generate a image that satisfies some description.",
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"arg_1_description": "Descriptions about the image to be generated.",
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},
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"TranslateMarkdownFromEnglishToChinese": {
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"module": "crazy_functions.批量Markdown翻译",
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"function": "Markdown中译英",
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"description": "Translate Markdown Documents from English to Chinese.",
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"arg_1_description": "A path containing Markdown files.",
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},
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"SummaryAudioVideo": {
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"module": "crazy_functions.总结音视频",
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"function": "总结音视频",
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"description": "Get text from a piece of audio and summarize this audio.",
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"arg_1_description": "A path containing audio files.",
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},
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}
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functions = [
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{
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"name": k,
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"description": v['description'],
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"parameters": {
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"type": "object",
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"properties": {
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"plugin_arg_1": {
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"type": "string",
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"description": v['arg_1_description'],
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},
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},
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"required": ["plugin_arg_1"],
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},
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} for k, v in get_fn_lib().items()
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]
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def inspect_dependency(chatbot, history):
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return True
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def eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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import subprocess, sys, os, shutil, importlib
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with open('gpt_log/void_terminal_runtime.py', 'w', encoding='utf8') as f:
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f.write(code)
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import importlib
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try:
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AutoAcademic = getattr(importlib.import_module('gpt_log.void_terminal_runtime', 'AutoAcademic'), 'AutoAcademic')
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# importlib.reload(AutoAcademic)
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auto_dict = AutoAcademic()
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selected_function = auto_dict.selected_function
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txt = auto_dict.txt
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fp, fn = get_fn_lib()[selected_function]
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tmp = get_fn_lib()[code['name']]
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fp, fn = tmp['module'], tmp['function']
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fn_plugin = getattr(importlib.import_module(fp, fn), fn)
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yield from fn_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
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arg = json.loads(code['arguments'])['plugin_arg_1']
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yield from fn_plugin(arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
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except:
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from toolbox import trimmed_format_exc
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chatbot.append(["执行错误", f"\n```\n{trimmed_format_exc()}\n```\n"])
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@ -110,22 +93,27 @@ def 终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_
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history = []
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# 基本信息：功能、贡献者
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chatbot.append(["函数插件功能？", "根据自然语言执行插件命令, 作者: binary-husky, 插件初始化中 ..."])
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chatbot.append(["虚空终端插件的功能？", "根据自然语言的描述, 执行任意插件的命令."])
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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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# dep_ok = yield from inspect_dependency(chatbot=chatbot, history=history) # 刷新界面
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# if not dep_ok: return
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# 输入
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i_say = prompt + txt
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i_say = txt
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# 开始
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llm_kwargs_function_call = copy.deepcopy(llm_kwargs)
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llm_kwargs_function_call['llm_model'] = 'gpt-call-fn' # 修改调用函数
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say, inputs_show_user=txt,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt=""
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llm_kwargs=llm_kwargs_function_call, chatbot=chatbot, history=[],
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sys_prompt=functions
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)
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# 将代码转为动画
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code = get_code_block(gpt_say)
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yield from eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
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res = json.loads(gpt_say)['choices'][0]
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if res['finish_reason'] == 'function_call':
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code = json.loads(gpt_say)['choices'][0]
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yield from eval_code(code['message']['function_call'], llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
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else:
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chatbot.append(["无法调用相关功能", res])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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@ -2146,5 +2146,20 @@
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"的参数！": "parameters!",
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"例如翻译、解释代码、润色等等": "such as translation, code interpretation, polishing, etc.",
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"响应异常": "Response exception",
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"响应中": "Responding"
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"响应中": "Responding",
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"请尝试英文Prompt": "Try English Prompt",
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"在运行过程中动态地修改多个配置": "Dynamically modify multiple configurations during runtime",
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"无法调用相关功能": "Unable to invoke related functions",
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"接驳虚空终端": "Connect to Void Terminal",
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"虚空终端插件的功能": "Functionality of Void Terminal plugin",
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"执行任意插件的命令": "Execute commands of any plugin",
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"修改调用函数": "Modify calling function",
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"获取简单聊天的默认参数": "Get default parameters for simple chat",
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"根据自然语言的描述": "Based on natural language description",
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"获取插件的句柄": "Get handle of plugin",
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"第四部分": "Part Four",
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"在运行过程中动态地修改配置": "Dynamically modify configurations during runtime",
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"请先把模型切换至gpt-*或者api2d-*": "Please switch the model to gpt-* or api2d-* first",
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"获取简单聊天的句柄": "Get handle of simple chat",
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"获取插件的默认参数": "Get default parameters of plugin"
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}
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87
docs/translate_std.json
Normal file
87
docs/translate_std.json
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@ -0,0 +1,87 @@
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{
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"解析JupyterNotebook": "ParsingJupyterNotebook",
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"Latex翻译中文并重新编译PDF": "TranslateChineseToEnglishInLatexAndRecompilePDF",
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"联网的ChatGPT_bing版": "OnlineChatGPT_BingEdition",
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"理解PDF文档内容标准文件输入": "UnderstandPdfDocumentContentStandardFileInput",
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"Latex英文纠错加PDF对比": "CorrectEnglishInLatexWithPDFComparison",
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"下载arxiv论文并翻译摘要": "DownloadArxivPaperAndTranslateAbstract",
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"Markdown翻译指定语言": "TranslateMarkdownToSpecifiedLanguage",
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"批量翻译PDF文档_多线程": "BatchTranslatePDFDocuments_MultiThreaded",
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"下载arxiv论文翻译摘要": "DownloadArxivPaperTranslateAbstract",
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"解析一个Python项目": "ParsePythonProject",
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"解析一个Golang项目": "ParseGolangProject",
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"代码重写为全英文_多线程": "RewriteCodeToEnglish_MultiThreaded",
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"解析一个CSharp项目": "ParsingCSharpProject",
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"删除所有本地对话历史记录": "DeleteAllLocalConversationHistoryRecords",
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"批量Markdown翻译": "BatchTranslateMarkdown",
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"连接bing搜索回答问题": "ConnectBingSearchAnswerQuestion",
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"Langchain知识库": "LangchainKnowledgeBase",
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"Latex输出PDF结果": "OutputPDFFromLatex",
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"把字符太少的块清除为回车": "ClearBlocksWithTooFewCharactersToNewline",
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"Latex精细分解与转化": "DecomposeAndConvertLatex",
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"解析一个C项目的头文件": "ParseCProjectHeaderFiles",
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"Markdown英译中": "TranslateMarkdownFromEnglishToChinese",
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"Markdown中译英": "MarkdownChineseToEnglish",
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"数学动画生成manim": "MathematicalAnimationGenerationManim",
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"chatglm微调工具": "ChatGLMFineTuningTool",
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"解析一个Rust项目": "ParseRustProject",
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"解析一个Java项目": "ParseJavaProject",
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"联网的ChatGPT": "ChatGPTConnectedToNetwork",
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"解析任意code项目": "ParseAnyCodeProject",
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"合并小写开头的段落块": "MergeLowercaseStartingParagraphBlocks",
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"Latex英文润色": "EnglishProofreadingForLatex",
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"Latex全文润色": "FullTextProofreadingForLatex",
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"询问多个大语言模型": "InquiryMultipleLargeLanguageModels",
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"解析一个Lua项目": "ParsingLuaProject",
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"解析ipynb文件": "ParsingIpynbFiles",
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"批量总结PDF文档": "BatchSummarizePDFDocuments",
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"批量翻译PDF文档": "BatchTranslatePDFDocuments",
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"理解PDF文档内容": "UnderstandPdfDocumentContent",
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"Latex中文润色": "LatexChineseProofreading",
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"Latex英文纠错": "LatexEnglishCorrection",
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"Latex全文翻译": "LatexFullTextTranslation",
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"同时问询_指定模型": "InquireSimultaneously_SpecifiedModel",
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"批量生成函数注释": "BatchGenerateFunctionComments",
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"解析一个前端项目": "ParseFrontendProject",
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"高阶功能模板函数": "HighOrderFunctionTemplateFunctions",
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"高级功能函数模板": "AdvancedFunctionTemplate",
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"总结word文档": "SummarizingWordDocuments",
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"载入对话历史存档": "LoadConversationHistoryArchive",
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"Latex中译英": "LatexChineseToEnglish",
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"Latex英译中": "LatexEnglishToChinese",
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"连接网络回答问题": "ConnectToNetworkToAnswerQuestions",
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"交互功能模板函数": "InteractiveFunctionTemplateFunction",
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"交互功能函数模板": "InteractiveFunctionFunctionTemplate",
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"sprint亮靛": "SprintIndigo",
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"print亮黄": "PrintBrightYellow",
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"print亮绿": "PrintBrightGreen",
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"print亮红": "PrintBrightRed",
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"解析项目源代码": "ParseProjectSourceCode",
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"解析一个C项目": "ParseCProject",
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"全项目切换英文": "SwitchToEnglishForTheWholeProject",
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"谷歌检索小助手": "GoogleSearchAssistant",
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"读取知识库作答": "ReadKnowledgeArchiveAnswerQuestions",
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"print亮蓝": "PrintBrightBlue",
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"微调数据集生成": "FineTuneDatasetGeneration",
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"清理多余的空行": "CleanUpExcessBlankLines",
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"编译Latex": "CompileLatex",
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"解析Paper": "ParsePaper",
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"ipynb解释": "IpynbExplanation",
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"读文章写摘要": "ReadArticleWriteSummary",
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"生成函数注释": "GenerateFunctionComments",
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"解析项目本身": "ParseProjectItself",
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"对话历史存档": "ConversationHistoryArchive",
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"专业词汇声明": "ProfessionalTerminologyDeclaration",
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"解析docx": "ParseDocx",
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"解析源代码新": "ParsingSourceCodeNew",
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"总结音视频": "SummaryAudioVideo",
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"知识库问答": "UpdateKnowledgeArchive",
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"多文件润色": "ProofreadMultipleFiles",
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"多文件翻译": "TranslateMultipleFiles",
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"解析PDF": "ParsePDF",
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"同时问询": "SimultaneousInquiry",
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"图片生成": "ImageGeneration",
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"动画生成": "AnimationGeneration",
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"语音助手": "VoiceAssistant",
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"启动微调": "StartFineTuning"
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}
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@ -288,6 +288,7 @@ def trans_json(word_to_translate, language, special=False):
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def step_1_core_key_translate():
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LANG_STD = 'std'
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def extract_chinese_characters(file_path):
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syntax = []
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with open(file_path, 'r', encoding='utf-8') as f:
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@ -327,15 +328,15 @@ def step_1_core_key_translate():
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for d in chinese_core_keys:
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if d not in chinese_core_keys_norepeat: chinese_core_keys_norepeat.append(d)
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need_translate = []
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cached_translation = read_map_from_json(language=LANG)
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cached_translation = read_map_from_json(language=LANG_STD)
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cached_translation_keys = list(cached_translation.keys())
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for d in chinese_core_keys_norepeat:
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if d not in cached_translation_keys:
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need_translate.append(d)
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need_translate_mapping = trans(need_translate, language=LANG, special=True)
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map_to_json(need_translate_mapping, language=LANG)
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cached_translation = read_map_from_json(language=LANG)
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need_translate_mapping = trans(need_translate, language=LANG_STD, special=True)
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map_to_json(need_translate_mapping, language=LANG_STD)
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cached_translation = read_map_from_json(language=LANG_STD)
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cached_translation = dict(sorted(cached_translation.items(), key=lambda x: -len(x[0])))
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chinese_core_keys_norepeat_mapping = {}
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