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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 | |
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) | |