diff --git a/crazy_functional.py b/crazy_functional.py index d8ca9ae..2f0fbaa 100644 --- a/crazy_functional.py +++ b/crazy_functional.py @@ -368,5 +368,19 @@ def get_crazy_functions(): }) except: print('Load function plugin failed') - ###################### 第n组插件 ########################### + + try: + from crazy_functions.虚空终端 import 终端 + function_plugins.update({ + "超级终端": { + "Color": "stop", + "AsButton": False, + # "AdvancedArgs": True, + # "ArgsReminder": "", + "Function": HotReload(终端) + } + }) + except: + print('Load function plugin failed') + return function_plugins diff --git a/crazy_functions/虚空终端.py b/crazy_functions/虚空终端.py new file mode 100644 index 0000000..fe71a46 --- /dev/null +++ b/crazy_functions/虚空终端.py @@ -0,0 +1,131 @@ +from toolbox import CatchException, update_ui, gen_time_str +from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive +from .crazy_utils import input_clipping + + +prompt = """ +I have to achieve some functionalities by calling one of the functions below. +Your job is to find the correct funtion to use to satisfy my requirement, +and then write python code to call this function with correct parameters. + +These are functions you are allowed to choose from: +1. + 功能描述: 总结音视频内容 + 调用函数: ConcludeAudioContent(txt, llm_kwargs) + 参数说明: + txt: 音频文件的路径 + llm_kwargs: 模型参数, 永远给定None +2. + 功能描述: 将每次对话记录写入Markdown格式的文件中 + 调用函数: WriteMarkdown() +3. + 功能描述: 将指定目录下的PDF文件从英文翻译成中文 + 调用函数: BatchTranslatePDFDocuments_MultiThreaded(txt, llm_kwargs) + 参数说明: + txt: PDF文件所在的路径 + llm_kwargs: 模型参数, 永远给定None +4. + 功能描述: 根据文本使用GPT模型生成相应的图像 + 调用函数: ImageGeneration(txt, llm_kwargs) + 参数说明: + txt: 图像生成所用到的提示文本 + llm_kwargs: 模型参数, 永远给定None +5. + 功能描述: 对输入的word文档进行摘要生成 + 调用函数: SummarizingWordDocuments(input_path, output_path) + 参数说明: + input_path: 待处理的word文档路径 + output_path: 摘要生成后的文档路径 + + +You should always anwser with following format: +---------------- +Code: +``` +class AutoAcademic(object): + def __init__(self): + self.selected_function = "FILL_CORRECT_FUNCTION_HERE" # e.g., "GenerateImage" + self.txt = "FILL_MAIN_PARAMETER_HERE" # e.g., "荷叶上的蜻蜓" + self.llm_kwargs = None +``` +Explanation: +只有GenerateImage和生成图像相关, 因此选择GenerateImage函数。 +---------------- + +Now, this is my requirement: + +""" +def get_fn_lib(): + return { + "BatchTranslatePDFDocuments_MultiThreaded": ("crazy_functions.批量翻译PDF文档_多线程", "批量翻译PDF文档"), + "SummarizingWordDocuments": ("crazy_functions.总结word文档", "总结word文档"), + "ImageGeneration": ("crazy_functions.图片生成", "图片生成"), + "TranslateMarkdownFromEnglishToChinese": ("crazy_functions.批量Markdown翻译", "Markdown中译英"), + "SummaryAudioVideo": ("crazy_functions.总结音视频", "总结音视频"), + } + +def inspect_dependency(chatbot, history): + return True + +def eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): + import subprocess, sys, os, shutil, importlib + + with open('gpt_log/void_terminal_runtime.py', 'w', encoding='utf8') as f: + f.write(code) + + try: + AutoAcademic = getattr(importlib.import_module('gpt_log.void_terminal_runtime', 'AutoAcademic'), 'AutoAcademic') + # importlib.reload(AutoAcademic) + auto_dict = AutoAcademic() + selected_function = auto_dict.selected_function + txt = auto_dict.txt + fp, fn = get_fn_lib()[selected_function] + fn_plugin = getattr(importlib.import_module(fp, fn), fn) + yield from fn_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port) + except: + from toolbox import trimmed_format_exc + chatbot.append(["执行错误", f"\n```\n{trimmed_format_exc()}\n```\n"]) + yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 + +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: + raise RuntimeError("GPT is not generating proper code.") + return matches[0].strip('python') # code block + +@CatchException +def 终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): + """ + txt 输入栏用户输入的文本, 例如需要翻译的一段话, 再例如一个包含了待处理文件的路径 + llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行 + plugin_kwargs 插件模型的参数, 暂时没有用武之地 + chatbot 聊天显示框的句柄, 用于显示给用户 + history 聊天历史, 前情提要 + system_prompt 给gpt的静默提醒 + web_port 当前软件运行的端口号 + """ + # 清空历史, 以免输入溢出 + history = [] + + # 基本信息：功能、贡献者 + 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 ..."]) + yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 + + # # 尝试导入依赖, 如果缺少依赖, 则给出安装建议 + # dep_ok = yield from inspect_dependency(chatbot=chatbot, history=history) # 刷新界面 + # if not dep_ok: return + + # 输入 + i_say = prompt + txt + # 开始 + gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( + inputs=i_say, inputs_show_user=txt, + llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], + sys_prompt="" + ) + + # 将代码转为动画 + code = get_code_block(gpt_say) + yield from eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port) diff --git a/toolbox.py b/toolbox.py index 4b0e1dd..4ab1116 100644 --- a/toolbox.py +++ b/toolbox.py @@ -221,16 +221,21 @@ def text_divide_paragraph(text): """ 将文本按照段落分隔符分割开，生成带有段落标签的HTML代码。 """ + pre = '
' + suf = '
' + if text.startswith(pre) and text.endswith(suf): + return text + if '```' in text: # careful input - return text + return pre + text + suf else: # wtf input lines = text.split("\n") for i, line in enumerate(lines): lines[i] = lines[i].replace(" ", " ") text = "
".join(lines) - return text + return pre + text + suf @lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度 def markdown_convertion(txt): @@ -342,8 +347,11 @@ def format_io(self, y): if y is None or y == []: return [] i_ask, gpt_reply = y[-1] - i_ask = text_divide_paragraph(i_ask) # 输入部分太自由，预处理一波 - gpt_reply = close_up_code_segment_during_stream(gpt_reply) # 当代码输出半截的时候，试着补上后个``` + # 输入部分太自由，预处理一波 + if i_ask is not None: i_ask = text_divide_paragraph(i_ask) + # 当代码输出半截的时候，试着补上后个``` + if gpt_reply is not None: gpt_reply = close_up_code_segment_during_stream(gpt_reply) + # process y[-1] = ( None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code', 'tables']), None if gpt_reply is None else markdown_convertion(gpt_reply)