import os import json import uuid import httpx import base64 import mimetypes from typing import Any, Optional from nonebot.log import logger import nonebot_plugin_localstore as store from nonebot_plugin_alconna import ( Text as TextMsg, Image as ImageMsg, UniMessage, ) # from zhDateTime import DateTime from azure.ai.inference.aio import ChatCompletionsClient from azure.ai.inference.models import SystemMessage from .config import config from .constants import * from .deal_latex import ConvertLatex nickname_json = None # 记录昵称 praises_json = None # 记录夸赞名单 loaded_target_list = [] # 记录已恢复备份的上下文的列表 # noinspection LongLine chromium_headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36" } async def get_image_raw_and_type( url: str, timeout: int = 10 ) -> Optional[tuple[bytes, str]]: """ 获取图片的二进制数据 参数: url: str 图片链接 timeout: int 超时时间 秒 return: tuple[bytes, str]: 图片二进制数据, 图片MIME格式 """ async with httpx.AsyncClient() as client: response = await client.get(url, headers=chromium_headers, timeout=timeout) if response.status_code == 200: # 获取图片数据 content_type = response.headers.get("Content-Type") if not content_type: content_type = mimetypes.guess_type(url)[0] # image_format = content_type.split("/")[1] if content_type else "jpeg" return response.content, str(content_type) else: return None async def get_image_b64(url: str, timeout: int = 10) -> Optional[str]: """ 获取图片的base64编码 参数: url: 图片链接 timeout: 超时时间 秒 return: 图片base64编码 """ if data_type := await get_image_raw_and_type(url, timeout): # image_format = content_type.split("/")[1] if content_type else "jpeg" base64_image = base64.b64encode(data_type[0]).decode("utf-8") data_url = "data:{};base64,{}".format(data_type[1], base64_image) return data_url else: return None async def make_chat( client: ChatCompletionsClient, msg: list, model_name: str, tools: Optional[list] = None, ): """调用ai获取回复 参数: client: 用于与AI模型进行通信 msg: 消息内容 model_name: 指定AI模型名""" return await client.complete( messages=msg, model=model_name, tools=tools, temperature=config.marshoai_temperature, max_tokens=config.marshoai_max_tokens, top_p=config.marshoai_top_p, ) def get_praises(): global praises_json if praises_json is None: praises_file = store.get_plugin_data_file( "praises.json" ) # 夸赞名单文件使用localstore存储 if not os.path.exists(praises_file): init_data = { "like": [ { "name": "Asankilp", "advantages": "赋予了Marsho猫娘人格,使用vim与vscode为Marsho写了许多代码,使Marsho更加可爱", } ] } with open(praises_file, "w", encoding="utf-8") as f: json.dump(init_data, f, ensure_ascii=False, indent=4) with open(praises_file, "r", encoding="utf-8") as f: data = json.load(f) praises_json = data return praises_json async def refresh_praises_json(): global praises_json praises_file = store.get_plugin_data_file("praises.json") if not os.path.exists(praises_file): init_data = { "like": [ { "name": "Asankilp", "advantages": "赋予了Marsho猫娘人格,使用vim与vscode为Marsho写了许多代码,使Marsho更加可爱", } ] } with open(praises_file, "w", encoding="utf-8") as f: json.dump(init_data, f, ensure_ascii=False, indent=4) with open(praises_file, "r", encoding="utf-8") as f: data = json.load(f) praises_json = data def build_praises(): praises = get_praises() result = ["你喜欢以下几个人物,他们有各自的优点:"] for item in praises["like"]: result.append(f"名字:{item['name']},优点:{item['advantages']}") return "\n".join(result) async def save_context_to_json(name: str, context: Any, path: str): context_dir = store.get_plugin_data_dir() / path os.makedirs(context_dir, exist_ok=True) file_path = os.path.join(context_dir, f"{name}.json") with open(file_path, "w", encoding="utf-8") as json_file: json.dump(context, json_file, ensure_ascii=False, indent=4) async def load_context_from_json(name: str, path: str) -> list: """从指定路径加载历史记录""" context_dir = store.get_plugin_data_dir() / path os.makedirs(context_dir, exist_ok=True) file_path = os.path.join(context_dir, f"{name}.json") try: with open(file_path, "r", encoding="utf-8") as json_file: return json.load(json_file) except FileNotFoundError: return [] async def set_nickname(user_id: str, name: str): global nickname_json filename = store.get_plugin_data_file("nickname.json") if not os.path.exists(filename): data = {} else: with open(filename, "r", encoding="utf-8") as f: data = json.load(f) data[user_id] = name if name == "" and user_id in data: del data[user_id] with open(filename, "w", encoding="utf-8") as f: json.dump(data, f, ensure_ascii=False, indent=4) nickname_json = data # noinspection PyBroadException async def get_nicknames(): """获取nickname_json, 优先来源于全局变量""" global nickname_json if nickname_json is None: filename = store.get_plugin_data_file("nickname.json") try: with open(filename, "r", encoding="utf-8") as f: nickname_json = json.load(f) except Exception: nickname_json = {} return nickname_json async def refresh_nickname_json(): """强制刷新nickname_json, 刷新全局变量""" global nickname_json filename = store.get_plugin_data_file("nickname.json") # noinspection PyBroadException try: with open(filename, "r", encoding="utf-8") as f: nickname_json = json.load(f) except Exception: logger.error("Error loading nickname.json") def get_prompt(): """获取系统提示词""" prompts = "" prompts += config.marshoai_additional_prompt if config.marshoai_enable_praises: praises_prompt = build_praises() prompts += praises_prompt marsho_prompt = config.marshoai_prompt spell = SystemMessage(content=marsho_prompt + prompts).as_dict() return spell def suggest_solution(errinfo: str) -> str: # noinspection LongLine suggestions = { "content_filter": "消息已被内容过滤器过滤。请调整聊天内容后重试。", "RateLimitReached": "模型达到调用速率限制。请稍等一段时间或联系Bot管理员。", "tokens_limit_reached": "请求token达到上限。请重置上下文。", "content_length_limit": "请求体过大。请重置上下文。", "unauthorized": "访问token无效。请联系Bot管理员。", "invalid type: parameter messages.content is of type array but should be of type string.": "聊天请求体包含此模型不支持的数据类型。请重置上下文。", "At most 1 image(s) may be provided in one request.": "此模型只能在上下文中包含1张图片。如果此前的聊天已经发送过图片,请重置上下文。", } for key, suggestion in suggestions.items(): if key in errinfo: return f"\n{suggestion}" return "" async def get_backup_context(target_id: str, target_private: bool) -> list: """获取历史上下文""" global loaded_target_list if target_private: target_uid = f"private_{target_id}" else: target_uid = f"group_{target_id}" if target_uid not in loaded_target_list: loaded_target_list.append(target_uid) return await load_context_from_json( f"back_up_context_{target_uid}", "contexts/backup" ) return [] """ 以下函数依照 Mulan PSL v2 协议授权 函数: parse_markdown, get_uuid_back2codeblock 版权所有 © 2024 金羿ELS Copyright (R) 2024 Eilles(EillesWan@outlook.com) Licensed under Mulan PSL v2. You can use this software according to the terms and conditions of the Mulan PSL v2. You may obtain a copy of Mulan PSL v2 at: http://license.coscl.org.cn/MulanPSL2 THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE. See the Mulan PSL v2 for more details. """ if config.marshoai_enable_richtext_parse: latex_convert = ConvertLatex() # 开启一个转换实例 async def get_uuid_back2codeblock( msg: str, code_blank_uuid_map: list[tuple[str, str]] ): for torep, rep in code_blank_uuid_map: msg = msg.replace(torep, rep) return msg async def parse_richtext(msg: str) -> UniMessage: """ 人工智能给出的回答一般不会包含 HTML 嵌入其中,但是包含图片或者 LaTeX 公式、代码块,都很正常。 这个函数会把这些都以图片形式嵌入消息体。 """ if not IMG_LATEX_PATTERN.search(msg): # 没有图片和LaTeX标签 return UniMessage(msg) result_msg = UniMessage() code_blank_uuid_map = [ (uuid.uuid4().hex, cbp.group()) for cbp in CODE_BLOCK_PATTERN.finditer(msg) ] last_tag_index = 0 # 代码块渲染麻烦,先不处理 for rep, torep in code_blank_uuid_map: msg = msg.replace(torep, rep) # for to_rep in CODE_SINGLE_PATTERN.finditer(msg): # code_blank_uuid_map.append((rep := uuid.uuid4().hex, to_rep.group())) # msg = msg.replace(to_rep.group(), rep) # print("#####################\n", msg, "\n\n") # 插入图片 for each_find_tag in IMG_LATEX_PATTERN.finditer(msg): tag_found = await get_uuid_back2codeblock( each_find_tag.group(), code_blank_uuid_map ) result_msg.append( TextMsg( await get_uuid_back2codeblock( msg[last_tag_index : msg.find(tag_found)], code_blank_uuid_map ) ) ) last_tag_index = msg.find(tag_found) + len(tag_found) if each_find_tag.group(1): # 图形一定要优先考虑 # 别忘了有些图形的地址就是 LaTeX,所以要优先判断 image_description = tag_found[2 : tag_found.find("]")] image_url = tag_found[tag_found.find("(") + 1 : -1] if image_ := await get_image_raw_and_type(image_url): result_msg.append( ImageMsg( raw=image_[0], mimetype=image_[1], name=image_description + ".png", ) ) result_msg.append(TextMsg("({})".format(image_description))) else: result_msg.append(TextMsg(tag_found)) elif each_find_tag.group(2): latex_exp = await get_uuid_back2codeblock( each_find_tag.group() .replace("$", "") .replace("\\(", "") .replace("\\)", "") .replace("\\[", "") .replace("\\]", ""), code_blank_uuid_map, ) latex_generate_ok, latex_generate_result = ( await latex_convert.generate_png( latex_exp, dpi=300, foreground_colour=config.marshoai_main_colour, ) ) if latex_generate_ok: result_msg.append( ImageMsg( raw=latex_generate_result, mimetype="image/png", name="latex.png", ) ) else: result_msg.append(TextMsg(latex_exp + "(公式解析失败)")) if isinstance(latex_generate_result, str): result_msg.append(TextMsg(latex_generate_result)) else: result_msg.append( ImageMsg( raw=latex_generate_result, mimetype="image/png", name="latex_error.png", ) ) else: result_msg.append(TextMsg(tag_found + "(未知内容解析失败)")) result_msg.append( TextMsg( await get_uuid_back2codeblock(msg[last_tag_index:], code_blank_uuid_map) ) ) return result_msg """ Mulan PSL v2 协议授权部分结束 """