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| from pydantic import BaseModel, Field | |
| from typing import List | |
| from toolbox import update_ui_lastest_msg, disable_auto_promotion | |
| from request_llms.bridge_all import predict_no_ui_long_connection | |
| from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError | |
| import copy, json, pickle, os, sys, time | |
| def read_avail_plugin_enum(): | |
| from crazy_functional import get_crazy_functions | |
| plugin_arr = get_crazy_functions() | |
| # remove plugins with out explaination | |
| plugin_arr = {k:v for k, v in plugin_arr.items() if 'Info' in v} | |
| plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)} | |
| plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)} | |
| plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)} | |
| plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)}) | |
| prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2) | |
| prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt | |
| return prompt, plugin_arr_dict, plugin_arr_dict_parse | |
| def wrap_code(txt): | |
| txt = txt.replace('```','') | |
| return f"\n```\n{txt}\n```\n" | |
| def have_any_recent_upload_files(chatbot): | |
| _5min = 5 * 60 | |
| if not chatbot: return False # chatbot is None | |
| most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None) | |
| if not most_recent_uploaded: return False # most_recent_uploaded is None | |
| if time.time() - most_recent_uploaded["time"] < _5min: return True # most_recent_uploaded is new | |
| else: return False # most_recent_uploaded is too old | |
| def get_recent_file_prompt_support(chatbot): | |
| most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None) | |
| path = most_recent_uploaded['path'] | |
| prompt = "\nAdditional Information:\n" | |
| prompt = "In case that this plugin requires a path or a file as argument," | |
| prompt += f"it is important for you to know that the user has recently uploaded a file, located at: `{path}`" | |
| prompt += f"Only use it when necessary, otherwise, you can ignore this file." | |
| return prompt | |
| def get_inputs_show_user(inputs, plugin_arr_enum_prompt): | |
| # remove plugin_arr_enum_prompt from inputs string | |
| inputs_show_user = inputs.replace(plugin_arr_enum_prompt, "") | |
| inputs_show_user += plugin_arr_enum_prompt[:200] + '...' | |
| inputs_show_user += '\n...\n' | |
| inputs_show_user += '...\n' | |
| inputs_show_user += '...}' | |
| return inputs_show_user | |
| def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention): | |
| plugin_arr_enum_prompt, plugin_arr_dict, plugin_arr_dict_parse = read_avail_plugin_enum() | |
| class Plugin(BaseModel): | |
| plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000") | |
| reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most") | |
| # ⭐ ⭐ ⭐ 选择插件 | |
| yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0) | |
| gpt_json_io = GptJsonIO(Plugin) | |
| gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n" | |
| gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n""" | |
| gpt_json_io.format_instructions += "The plugins you are authorized to use are listed below:\n" | |
| gpt_json_io.format_instructions += plugin_arr_enum_prompt | |
| inputs = "Choose the correct plugin according to user requirements, the user requirement is: \n\n" + \ | |
| ">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + gpt_json_io.format_instructions | |
| run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection( | |
| inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[]) | |
| try: | |
| gpt_reply = run_gpt_fn(inputs, "") | |
| plugin_sel = gpt_json_io.generate_output_auto_repair(gpt_reply, run_gpt_fn) | |
| except JsonStringError: | |
| msg = f"抱歉, {llm_kwargs['llm_model']}无法理解您的需求。" | |
| msg += "请求的Prompt为：\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt)) | |
| msg += "语言模型回复为：\n" + wrap_code(gpt_reply) | |
| msg += "\n但您可以尝试再试一次\n" | |
| yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2) | |
| return | |
| if plugin_sel.plugin_selection not in plugin_arr_dict_parse: | |
| msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。" | |
| msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件：\n" + wrap_code(gpt_reply) | |
| msg += "\n但您可以尝试再试一次\n" | |
| yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2) | |
| return | |
| # ⭐ ⭐ ⭐ 确认插件参数 | |
| if not have_any_recent_upload_files(chatbot): | |
| appendix_info = "" | |
| else: | |
| appendix_info = get_recent_file_prompt_support(chatbot) | |
| plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection] | |
| yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0) | |
| class PluginExplicit(BaseModel): | |
| plugin_selection: str = plugin_sel.plugin_selection | |
| plugin_arg: str = Field(description="The argument of the plugin.", default="") | |
| gpt_json_io = GptJsonIO(PluginExplicit) | |
| gpt_json_io.format_instructions += "The information about this plugin is:" + plugin["Info"] | |
| inputs = f"A plugin named {plugin_sel.plugin_selection} is selected, " + \ | |
| "you should extract plugin_arg from the user requirement, the user requirement is: \n\n" + \ | |
| ">> " + (txt + appendix_info).rstrip('\n').replace('\n','\n>> ') + '\n\n' + \ | |
| gpt_json_io.format_instructions | |
| run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection( | |
| inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[]) | |
| plugin_sel = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn) | |
| # ⭐ ⭐ ⭐ 执行插件 | |
| fn = plugin['Function'] | |
| fn_name = fn.__name__ | |
| msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。' | |
| yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2) | |
| yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1) | |
| return |