支持自然语言修改项目本身的配置
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qingxu fu
@@ -1,119 +1,108 @@
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from pydantic import BaseModel, Field
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from typing import List
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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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from toolbox import update_ui_lastest_msg
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from request_llm.bridge_all import predict_no_ui_long_connection
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from crazy_functions.crazy_utils import input_clipping
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from crazy_functions.json_fns.pydantic_io import GptJsonIO
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from crazy_functions.vt_fns.vt_modify_config import modify_configuration_hot
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from crazy_functions.vt_fns.vt_modify_config import modify_configuration_reboot
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from enum import Enum
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import copy, json, pickle, os, sys
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def get_fn_lib():
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return {
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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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class IntentionEnum(str, Enum):
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ModifyConfiguration = 'ModifyConfiguration'
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ExecutePlugin = 'ExecutePlugin'
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Chat = 'Chat'
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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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class UserIntention(BaseModel):
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user_prompt: str = Field(description="the content of user input", default="")
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intention_type: IntentionEnum = Field(description="the type of user intention", default=IntentionEnum.Chat)
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user_provide_file: bool = Field(description="whether the user provides a path to a file", default=False)
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user_provide_url: bool = Field(description="whether the user provides a url", default=False)
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def inspect_dependency(chatbot, history):
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return True
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def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
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# 没写完
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pass
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def eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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import importlib
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try:
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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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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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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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def get_code_block(reply):
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import re
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pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
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matches = re.findall(pattern, reply) # find all code blocks in text
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if len(matches) != 1:
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raise RuntimeError("GPT is not generating proper code.")
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return matches[0].strip('python') # code block
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def chat(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=txt, inputs_show_user=txt,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt=system_prompt
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)
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chatbot[-1] = [txt, gpt_say]
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history.extend([txt, gpt_say])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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pass
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@CatchException
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def 终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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def 自动终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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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
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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
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llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
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plugin_kwargs 插件模型的参数, 暂时没有用武之地
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chatbot 聊天显示框的句柄, 用于显示给用户
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history 聊天历史, 前情提要
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plugin_kwargs 插件模型的参数, 如温度和top_p等, 一般原样传递下去就行
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chatbot 聊天显示框的句柄，用于显示给用户
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history 聊天历史，前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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# 清空历史, 以免输入溢出
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history = []
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# 基本信息：功能、贡献者
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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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history = [] # 清空历史，以免输入溢出
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chatbot.append(("自动终端状态: ", f"正在执行任务: {txt}"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# 输入
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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_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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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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# 初始化插件状态
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state = chatbot._cookies.get('plugin_state', None)
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if state is not None: state = pickle.loads(state)
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else: state = {}
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def update_vt_state():
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# 赋予插件锁定 锁定插件回调路径，当下一次用户提交时，会直接转到该函数
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chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->自动终端'
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chatbot._cookies['vt_state'] = pickle.dumps(state)
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# ⭐ ⭐ ⭐ 分析用户意图
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yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
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gpt_json_io = GptJsonIO(UserIntention)
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inputs = "Analyze the intention of the user according to following user input: \n\n" + txt + '\n\n' + gpt_json_io.format_instructions
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run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
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inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
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user_intention = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn)
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# 用户意图: 修改本项目的配置
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if user_intention.intention_type == IntentionEnum.ModifyConfiguration:
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yield from modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
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# 用户意图: 调度插件
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if user_intention.intention_type == IntentionEnum.ExecutePlugin:
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yield from execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
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# 用户意图: 聊天
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if user_intention.intention_type == IntentionEnum.Chat:
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yield from chat(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
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# update_vt_state()
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return
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# # if state == 'wait_user_keyword':
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# # chatbot._cookies['lock_plugin'] = None # 解除插件锁定，避免遗忘导致死锁
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# # chatbot._cookies['plugin_state_0001'] = None # 解除插件状态，避免遗忘导致死锁
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# # # 解除插件锁定
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# # chatbot.append((f"获取关键词：{txt}", ""))
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# # yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# # inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}"
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# # gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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# # inputs=inputs, inputs_show_user=inputs_show_user,
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# # llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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# # sys_prompt="When you want to show an image, use markdown format. e.g. . If there are no image url provided, answer 'no image url provided'"
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# # )
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# # chatbot[-1] = [chatbot[-1][0], gpt_say]
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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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