update multi-language module
This commit is contained in:
505030475
@@ -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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