diff --git a/.vscode/settings.json b/.vscode/settings.json deleted file mode 100644 index 23fd35f0e..000000000 --- a/.vscode/settings.json +++ /dev/null @@ -1,3 +0,0 @@ -{ - "editor.formatOnSave": true -} \ No newline at end of file diff --git a/src/plugins/chat/__init__.py b/src/plugins/chat/__init__.py index 11c059c1c..ec3d4f01d 100644 --- a/src/plugins/chat/__init__.py +++ b/src/plugins/chat/__init__.py @@ -16,6 +16,7 @@ from .config import global_config from .emoji_manager import emoji_manager from .relationship_manager import relationship_manager from .willing_manager import willing_manager +from .chat_stream import chat_manager from ..memory_system.memory import hippocampus, memory_graph from .bot import ChatBot from .message_sender import message_manager, message_sender @@ -98,6 +99,8 @@ async def _(bot: Bot): asyncio.create_task(emoji_manager._periodic_scan(interval_MINS=global_config.EMOJI_REGISTER_INTERVAL)) logger.success("-----------开始偷表情包！-----------") + asyncio.create_task(chat_manager._initialize()) + asyncio.create_task(chat_manager._auto_save_task()) @group_msg.handle() diff --git a/src/plugins/chat/bot.py b/src/plugins/chat/bot.py index 490b171b5..81361d81b 100644 --- a/src/plugins/chat/bot.py +++ b/src/plugins/chat/bot.py @@ -1,28 +1,28 @@ import re import time from random import random - from loguru import logger from nonebot.adapters.onebot.v11 import Bot, GroupMessageEvent from ..memory_system.memory import hippocampus from ..moods.moods import MoodManager # 导入情绪管理器 from .config import global_config -from .cq_code import CQCode # 导入CQCode模块 +from .cq_code import CQCode,cq_code_tool # 导入CQCode模块 from .emoji_manager import emoji_manager # 导入表情包管理器 from .llm_generator import ResponseGenerator -from .message import ( - Message, - Message_Sending, - Message_Thinking, # 导入 Message_Thinking 类 - MessageSet, +from .message import MessageSending, MessageRecv, MessageThinking, MessageSet +from .message_cq import ( + MessageRecvCQ, ) +from .chat_stream import chat_manager + from .message_sender import message_manager # 导入新的消息管理器 from .relationship_manager import relationship_manager from .storage import MessageStorage -from .utils import calculate_typing_time, is_mentioned_bot_in_txt +from .utils import calculate_typing_time, is_mentioned_bot_in_message +from .utils_image import image_path_to_base64 from .willing_manager import willing_manager # 导入意愿管理器 - +from .message_base import UserInfo, GroupInfo, Seg class ChatBot: def __init__(self): @@ -44,35 +44,61 @@ class ChatBot: async def handle_message(self, event: GroupMessageEvent, bot: Bot) -> None: """处理收到的群消息""" - if event.group_id not in global_config.talk_allowed_groups: - return self.bot = bot # 更新 bot 实例 + # group_info = await bot.get_group_info(group_id=event.group_id) + # sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True) + + # 白名单设定由nontbot侧完成 + if event.group_id: + if event.group_id not in global_config.talk_allowed_groups: + return if event.user_id in global_config.ban_user_id: return - - group_info = await bot.get_group_info(group_id=event.group_id) - sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True) - - await relationship_manager.update_relationship(user_id=event.user_id, data=sender_info) - await relationship_manager.update_relationship_value(user_id=event.user_id, relationship_value=0.5) - - message = Message( - group_id=event.group_id, + + user_info=UserInfo( user_id=event.user_id, - message_id=event.message_id, - user_cardname=sender_info['card'], - raw_message=str(event.original_message), - plain_text=event.get_plaintext(), - reply_message=event.reply, + user_nickname=event.sender.nickname, + user_cardname=event.sender.card or None, + platform='qq' ) - await message.initialize() + group_info=GroupInfo( + group_id=event.group_id, + group_name=None, + platform='qq' + ) + + message_cq=MessageRecvCQ( + message_id=event.message_id, + user_info=user_info, + raw_message=str(event.original_message), + group_info=group_info, + reply_message=event.reply, + platform='qq' + ) + message_json=message_cq.to_dict() + + # 进入maimbot + message=MessageRecv(message_json) + + groupinfo=message.message_info.group_info + userinfo=message.message_info.user_info + messageinfo=message.message_info + + # 消息过滤，涉及到config有待更新 + + chat = await chat_manager.get_or_create_stream(platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo) + message.update_chat_stream(chat) + await relationship_manager.update_relationship(chat_stream=chat,) + await relationship_manager.update_relationship_value(chat_stream=chat, relationship_value = 0.5) + + await message.process() # 过滤词 for word in global_config.ban_words: - if word in message.detailed_plain_text: + if word in message.processed_plain_text: logger.info( - f"[{message.group_name}]{message.user_nickname}:{message.processed_plain_text}") + f"[{groupinfo.group_name}]{userinfo.user_nickname}:{message.processed_plain_text}") logger.info(f"[过滤词识别]消息中含有{word}，filtered") return @@ -83,8 +109,10 @@ class ChatBot: f"[{message.group_name}]{message.user_nickname}:{message.raw_message}") logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered") return + + current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time)) + - current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(message.time)) # topic=await topic_identifier.identify_topic_llm(message.processed_plain_text) topic = '' @@ -93,47 +121,60 @@ class ChatBot: logger.debug(f"对{message.processed_plain_text}" f"的激活度:{interested_rate}") # logger.info(f"\033[1;32m[主题识别]\033[0m 使用{global_config.topic_extract}主题: {topic}") + + await self.storage.store_message(message,chat, topic[0] if topic else None) - await self.storage.store_message(message, topic[0] if topic else None) - - is_mentioned = is_mentioned_bot_in_txt(message.processed_plain_text) - reply_probability = willing_manager.change_reply_willing_received( - event.group_id, - topic[0] if topic else None, - is_mentioned, - global_config, - event.user_id, - message.is_emoji, - interested_rate + is_mentioned = is_mentioned_bot_in_message(message) + reply_probability = await willing_manager.change_reply_willing_received( + chat_stream=chat, + topic=topic[0] if topic else None, + is_mentioned_bot=is_mentioned, + config=global_config, + is_emoji=message.is_emoji, + interested_rate=interested_rate ) - current_willing = willing_manager.get_willing(event.group_id) - + current_willing = willing_manager.get_willing(chat_stream=chat) + logger.info( - f"[{current_time}][{message.group_name}]{message.user_nickname}:" - f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]") - - response = "" + f"[{current_time}][{chat.group_info.group_name}]{chat.user_info.user_nickname}:" + f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]" + ) + response = None + if random() < reply_probability: + bot_user_info=UserInfo( + user_id=global_config.BOT_QQ, + user_nickname=global_config.BOT_NICKNAME, + platform=messageinfo.platform + ) tinking_time_point = round(time.time(), 2) think_id = 'mt' + str(tinking_time_point) - thinking_message = Message_Thinking(message=message, message_id=think_id) - + thinking_message = MessageThinking( + message_id=think_id, + chat_stream=chat, + bot_user_info=bot_user_info, + reply=message + ) + message_manager.add_message(thinking_message) - willing_manager.change_reply_willing_sent(thinking_message.group_id) - - response, raw_content = await self.gpt.generate_response(message) - + willing_manager.change_reply_willing_sent(chat) + + response,raw_content = await self.gpt.generate_response(message) + + # print(f"response: {response}") if response: - container = message_manager.get_container(event.group_id) + # print(f"有response: {response}") + container = message_manager.get_container(chat.stream_id) thinking_message = None # 找到message,删除 + # print(f"开始找思考消息") for msg in container.messages: - if isinstance(msg, Message_Thinking) and msg.message_id == think_id: + if isinstance(msg, MessageThinking) and msg.message_info.message_id == think_id: + # print(f"找到思考消息: {msg}") thinking_message = msg container.messages.remove(msg) - # print(f"\033[1;32m[思考消息删除]\033[0m 已找到思考消息对象，开始删除") break # 如果找不到思考消息，直接返回 @@ -143,41 +184,38 @@ class ChatBot: # 记录开始思考的时间，避免从思考到回复的时间太久 thinking_start_time = thinking_message.thinking_start_time - message_set = MessageSet(event.group_id, global_config.BOT_QQ, - think_id) # 发送消息的id和产生发送消息的message_thinking是一致的 - # 计算打字时间，1是为了模拟打字，2是避免多条回复乱序 + message_set = MessageSet(chat, think_id) + #计算打字时间，1是为了模拟打字，2是避免多条回复乱序 accu_typing_time = 0 - - # print(f"\033[1;32m[开始回复]\033[0m 开始将回复1载入发送容器") + mark_head = False for msg in response: # print(f"\033[1;32m[回复内容]\033[0m {msg}") # 通过时间改变时间戳 typing_time = calculate_typing_time(msg) + print(f"typing_time: {typing_time}") accu_typing_time += typing_time timepoint = tinking_time_point + accu_typing_time - - bot_message = Message_Sending( - group_id=event.group_id, - user_id=global_config.BOT_QQ, + message_segment = Seg(type='text', data=msg) + print(f"message_segment: {message_segment}") + bot_message = MessageSending( message_id=think_id, - raw_message=msg, - plain_text=msg, - processed_plain_text=msg, - user_nickname=global_config.BOT_NICKNAME, - group_name=message.group_name, - time=timepoint, # 记录了回复生成的时间 - thinking_start_time=thinking_start_time, # 记录了思考开始的时间 - reply_message_id=message.message_id + chat_stream=chat, + bot_user_info=bot_user_info, + message_segment=message_segment, + reply=message, + is_head=not mark_head, + is_emoji=False ) - await bot_message.initialize() + print(f"bot_message: {bot_message}") if not mark_head: - bot_message.is_head = True mark_head = True + print(f"添加消息到message_set: {bot_message}") message_set.add_message(bot_message) # message_set 可以直接加入 message_manager # print(f"\033[1;32m[回复]\033[0m 将回复载入发送容器") + print(f"添加message_set到message_manager") message_manager.add_message(message_set) bot_response_time = tinking_time_point @@ -189,31 +227,25 @@ class ChatBot: if emoji_raw != None: emoji_path, description = emoji_raw - emoji_cq = CQCode.create_emoji_cq(emoji_path) - + emoji_cq = image_path_to_base64(emoji_path) + if random() < 0.5: bot_response_time = tinking_time_point - 1 else: bot_response_time = bot_response_time + 1 - - bot_message = Message_Sending( - group_id=event.group_id, - user_id=global_config.BOT_QQ, - message_id=0, - raw_message=emoji_cq, - plain_text=emoji_cq, - processed_plain_text=emoji_cq, - detailed_plain_text=description, - user_nickname=global_config.BOT_NICKNAME, - group_name=message.group_name, - time=bot_response_time, - is_emoji=True, - translate_cq=False, - thinking_start_time=thinking_start_time, - # reply_message_id=message.message_id + + message_segment = Seg(type='emoji', data=emoji_cq) + bot_message = MessageSending( + message_id=think_id, + chat_stream=chat, + bot_user_info=bot_user_info, + message_segment=message_segment, + reply=message, + is_head=False, + is_emoji=True ) - await bot_message.initialize() message_manager.add_message(bot_message) + emotion = await self.gpt._get_emotion_tags(raw_content) logger.debug(f"为 '{response}' 获取到的情感标签为：{emotion}") valuedict = { @@ -225,12 +257,13 @@ class ChatBot: 'fearful': -0.7, 'neutral': 0.1 } - await relationship_manager.update_relationship_value(message.user_id, - relationship_value=valuedict[emotion[0]]) + await relationship_manager.update_relationship_value(chat_stream=chat, relationship_value=valuedict[emotion[0]]) # 使用情绪管理器更新情绪 self.mood_manager.update_mood_from_emotion(emotion[0], global_config.mood_intensity_factor) - - # willing_manager.change_reply_willing_after_sent(event.group_id) + + # willing_manager.change_reply_willing_after_sent( + # chat_stream=chat + # ) # 创建全局ChatBot实例 diff --git a/src/plugins/chat/chat_stream.py b/src/plugins/chat/chat_stream.py new file mode 100644 index 000000000..bee679173 --- /dev/null +++ b/src/plugins/chat/chat_stream.py @@ -0,0 +1,226 @@ +import asyncio +import hashlib +import time +import copy +from typing import Dict, Optional + +from loguru import logger + +from ...common.database import Database +from .message_base import GroupInfo, UserInfo + + +class ChatStream: + """聊天流对象，存储一个完整的聊天上下文""" + + def __init__( + self, + stream_id: str, + platform: str, + user_info: UserInfo, + group_info: Optional[GroupInfo] = None, + data: dict = None, + ): + self.stream_id = stream_id + self.platform = platform + self.user_info = user_info + self.group_info = group_info + self.create_time = ( + data.get("create_time", int(time.time())) if data else int(time.time()) + ) + self.last_active_time = ( + data.get("last_active_time", self.create_time) if data else self.create_time + ) + self.saved = False + + def to_dict(self) -> dict: + """转换为字典格式""" + result = { + "stream_id": self.stream_id, + "platform": self.platform, + "user_info": self.user_info.to_dict() if self.user_info else None, + "group_info": self.group_info.to_dict() if self.group_info else None, + "create_time": self.create_time, + "last_active_time": self.last_active_time, + } + return result + + @classmethod + def from_dict(cls, data: dict) -> "ChatStream": + """从字典创建实例""" + user_info = ( + UserInfo(**data.get("user_info", {})) if data.get("user_info") else None + ) + group_info = ( + GroupInfo(**data.get("group_info", {})) if data.get("group_info") else None + ) + + return cls( + stream_id=data["stream_id"], + platform=data["platform"], + user_info=user_info, + group_info=group_info, + data=data, + ) + + def update_active_time(self): + """更新最后活跃时间""" + self.last_active_time = int(time.time()) + self.saved = False + + +class ChatManager: + """聊天管理器，管理所有聊天流""" + + _instance = None + _initialized = False + + def __new__(cls): + if cls._instance is None: + cls._instance = super().__new__(cls) + return cls._instance + + def __init__(self): + if not self._initialized: + self.streams: Dict[str, ChatStream] = {} # stream_id -> ChatStream + self.db = Database.get_instance() + self._ensure_collection() + self._initialized = True + # 在事件循环中启动初始化 + # asyncio.create_task(self._initialize()) + # # 启动自动保存任务 + # asyncio.create_task(self._auto_save_task()) + + async def _initialize(self): + """异步初始化""" + try: + await self.load_all_streams() + logger.success(f"聊天管理器已启动，已加载 {len(self.streams)} 个聊天流") + except Exception as e: + logger.error(f"聊天管理器启动失败: {str(e)}") + + async def _auto_save_task(self): + """定期自动保存所有聊天流""" + while True: + await asyncio.sleep(300) # 每5分钟保存一次 + try: + await self._save_all_streams() + logger.info("聊天流自动保存完成") + except Exception as e: + logger.error(f"聊天流自动保存失败: {str(e)}") + + def _ensure_collection(self): + """确保数据库集合存在并创建索引""" + if "chat_streams" not in self.db.db.list_collection_names(): + self.db.db.create_collection("chat_streams") + # 创建索引 + self.db.db.chat_streams.create_index([("stream_id", 1)], unique=True) + self.db.db.chat_streams.create_index( + [("platform", 1), ("user_info.user_id", 1), ("group_info.group_id", 1)] + ) + + def _generate_stream_id( + self, platform: str, user_info: UserInfo, group_info: Optional[GroupInfo] = None + ) -> str: + """生成聊天流唯一ID""" + if group_info: + # 组合关键信息 + components = [ + platform, + str(group_info.group_id) + ] + else: + components = [ + platform, + str(user_info.user_id), + "private" + ] + + # 使用MD5生成唯一ID + key = "_".join(components) + return hashlib.md5(key.encode()).hexdigest() + + async def get_or_create_stream( + self, platform: str, user_info: UserInfo, group_info: Optional[GroupInfo] = None + ) -> ChatStream: + """获取或创建聊天流 + + Args: + platform: 平台标识 + user_info: 用户信息 + group_info: 群组信息（可选） + + Returns: + ChatStream: 聊天流对象 + """ + # 生成stream_id + stream_id = self._generate_stream_id(platform, user_info, group_info) + + # 检查内存中是否存在 + if stream_id in self.streams: + stream = self.streams[stream_id] + # 更新用户信息和群组信息 + stream.update_active_time() + stream=copy.deepcopy(stream) + stream.user_info = user_info + if group_info: + stream.group_info = group_info + return stream + + # 检查数据库中是否存在 + data = self.db.db.chat_streams.find_one({"stream_id": stream_id}) + if data: + stream = ChatStream.from_dict(data) + # 更新用户信息和群组信息 + stream.user_info = user_info + if group_info: + stream.group_info = group_info + stream.update_active_time() + else: + # 创建新的聊天流 + stream = ChatStream( + stream_id=stream_id, + platform=platform, + user_info=user_info, + group_info=group_info, + ) + + # 保存到内存和数据库 + self.streams[stream_id] = stream + await self._save_stream(stream) + return copy.deepcopy(stream) + + def get_stream(self, stream_id: str) -> Optional[ChatStream]: + """通过stream_id获取聊天流""" + return self.streams.get(stream_id) + + def get_stream_by_info( + self, platform: str, user_info: UserInfo, group_info: Optional[GroupInfo] = None + ) -> Optional[ChatStream]: + """通过信息获取聊天流""" + stream_id = self._generate_stream_id(platform, user_info, group_info) + return self.streams.get(stream_id) + + async def _save_stream(self, stream: ChatStream): + """保存聊天流到数据库""" + if not stream.saved: + self.db.db.chat_streams.update_one( + {"stream_id": stream.stream_id}, {"$set": stream.to_dict()}, upsert=True + ) + stream.saved = True + + async def _save_all_streams(self): + """保存所有聊天流""" + for stream in self.streams.values(): + await self._save_stream(stream) + + async def load_all_streams(self): + """从数据库加载所有聊天流""" + all_streams = self.db.db.chat_streams.find({}) + for data in all_streams: + stream = ChatStream.from_dict(data) + self.streams[stream.stream_id] = stream + + +# 创建全局单例 +chat_manager = ChatManager() diff --git a/src/plugins/chat/cq_code.py b/src/plugins/chat/cq_code.py index 710d5cd6c..185e98edf 100644 --- a/src/plugins/chat/cq_code.py +++ b/src/plugins/chat/cq_code.py @@ -2,22 +2,23 @@ import base64 import html import time from dataclasses import dataclass -from typing import Dict, Optional -from loguru import logger +from typing import Dict, List, Optional, Union import requests # 解析各种CQ码 # 包含CQ码类 import urllib3 +from loguru import logger from nonebot import get_driver from urllib3.util import create_urllib3_context from ..models.utils_model import LLM_request from .config import global_config from .mapper import emojimapper -from .utils_image import image_path_to_base64, storage_emoji, storage_image -from .utils_user import get_user_nickname +from .message_base import Seg +from .utils_user import get_user_nickname,get_groupname +from .message_base import GroupInfo, UserInfo driver = get_driver() config = driver.config @@ -35,65 +36,80 @@ class TencentSSLAdapter(requests.adapters.HTTPAdapter): def init_poolmanager(self, connections, maxsize, block=False): self.poolmanager = urllib3.poolmanager.PoolManager( - num_pools=connections, maxsize=maxsize, - block=block, ssl_context=self.ssl_context) + num_pools=connections, + maxsize=maxsize, + block=block, + ssl_context=self.ssl_context, + ) @dataclass class CQCode: """ CQ码数据类，用于存储和处理CQ码 - + 属性: type: CQ码类型（如'image', 'at', 'face'等） params: CQ码的参数字典 raw_code: 原始CQ码字符串 - translated_plain_text: 经过处理（如AI翻译）后的文本表示 + translated_segments: 经过处理后的Seg对象列表 """ + type: str params: Dict[str, str] - # raw_code: str - group_id: int - user_id: int - group_name: str = "" - user_nickname: str = "" - translated_plain_text: Optional[str] = None + group_info: Optional[GroupInfo] = None + user_info: Optional[UserInfo] = None + translated_segments: Optional[Union[Seg, List[Seg]]] = None reply_message: Dict = None # 存储回复消息 image_base64: Optional[str] = None _llm: Optional[LLM_request] = None def __post_init__(self): """初始化LLM实例""" - self._llm = LLM_request(model=global_config.vlm, temperature=0.4, max_tokens=300) + pass - async def translate(self): - """根据CQ码类型进行相应的翻译处理""" - if self.type == 'text': - self.translated_plain_text = self.params.get('text', '') - elif self.type == 'image': - if self.params.get('sub_type') == '0': - self.translated_plain_text = await self.translate_image() + def translate(self): + """根据CQ码类型进行相应的翻译处理，转换为Seg对象""" + if self.type == "text": + self.translated_segments = Seg( + type="text", data=self.params.get("text", "") + ) + elif self.type == "image": + base64_data = self.translate_image() + if base64_data: + if self.params.get("sub_type") == "0": + self.translated_segments = Seg(type="image", data=base64_data) + else: + self.translated_segments = Seg(type="emoji", data=base64_data) else: - self.translated_plain_text = await self.translate_emoji() - elif self.type == 'at': - user_nickname = get_user_nickname(self.params.get('qq', '')) - if user_nickname: - self.translated_plain_text = f"[@{user_nickname}]" + self.translated_segments = Seg(type="text", data="[图片]") + elif self.type == "at": + user_nickname = get_user_nickname(self.params.get("qq", "")) + self.translated_segments = Seg( + type="text", data=f"[@{user_nickname or '某人'}]" + ) + elif self.type == "reply": + reply_segments = self.translate_reply() + if reply_segments: + self.translated_segments = Seg(type="seglist", data=reply_segments) else: - self.translated_plain_text = "@某人" - elif self.type == 'reply': - self.translated_plain_text = await self.translate_reply() - elif self.type == 'face': - face_id = self.params.get('id', '') - # self.translated_plain_text = f"[表情{face_id}]" - self.translated_plain_text = f"[{emojimapper.get(int(face_id), '表情')}]" - elif self.type == 'forward': - self.translated_plain_text = await self.translate_forward() + self.translated_segments = Seg(type="text", data="[回复某人消息]") + elif self.type == "face": + face_id = self.params.get("id", "") + self.translated_segments = Seg( + type="text", data=f"[{emojimapper.get(int(face_id), '表情')}]" + ) + elif self.type == "forward": + forward_segments = self.translate_forward() + if forward_segments: + self.translated_segments = Seg(type="seglist", data=forward_segments) + else: + self.translated_segments = Seg(type="text", data="[转发消息]") else: - self.translated_plain_text = f"[{self.type}]" + self.translated_segments = Seg(type="text", data=f"[{self.type}]") def get_img(self): - ''' + """ headers = { 'User-Agent': 'QQ/8.9.68.11565 CFNetwork/1220.1 Darwin/20.3.0', 'Accept': 'image/*;q=0.8', @@ -102,18 +118,18 @@ class CQCode: 'Cache-Control': 'no-cache', 'Pragma': 'no-cache' } - ''' + """ # 腾讯专用请求头配置 headers = { - 'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.87 Safari/537.36', - 'Accept': 'text/html, application/xhtml xml, */*', - 'Accept-Encoding': 'gbk, GB2312', - 'Accept-Language': 'zh-cn', - 'Content-Type': 'application/x-www-form-urlencoded', - 'Cache-Control': 'no-cache' + "User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.87 Safari/537.36", + "Accept": "text/html, application/xhtml xml, */*", + "Accept-Encoding": "gbk, GB2312", + "Accept-Language": "zh-cn", + "Content-Type": "application/x-www-form-urlencoded", + "Cache-Control": "no-cache", } - url = html.unescape(self.params['url']) - if not url.startswith(('http://', 'https://')): + url = html.unescape(self.params["url"]) + if not url.startswith(("http://", "https://")): return None # 创建专用会话 @@ -129,30 +145,30 @@ class CQCode: headers=headers, timeout=15, allow_redirects=True, - stream=True # 流式传输避免大内存问题 + stream=True, # 流式传输避免大内存问题 ) # 腾讯服务器特殊状态码处理 - if response.status_code == 400 and 'multimedia.nt.qq.com.cn' in url: + if response.status_code == 400 and "multimedia.nt.qq.com.cn" in url: return None if response.status_code != 200: raise requests.exceptions.HTTPError(f"HTTP {response.status_code}") # 验证内容类型 - content_type = response.headers.get('Content-Type', '') - if not content_type.startswith('image/'): + content_type = response.headers.get("Content-Type", "") + if not content_type.startswith("image/"): raise ValueError(f"非图片内容类型: {content_type}") # 转换为Base64 - image_base64 = base64.b64encode(response.content).decode('utf-8') + image_base64 = base64.b64encode(response.content).decode("utf-8") self.image_base64 = image_base64 return image_base64 except (requests.exceptions.SSLError, requests.exceptions.HTTPError) as e: if retry == max_retries - 1: logger.error(f"最终请求失败: {str(e)}") - time.sleep(1.5 ** retry) # 指数退避 + time.sleep(1.5**retry) # 指数退避 except Exception: logger.exception("[未知错误]") @@ -160,211 +176,181 @@ class CQCode: return None - async def translate_emoji(self) -> str: - """处理表情包类型的CQ码""" - if 'url' not in self.params: - return '[表情包]' - base64_str = self.get_img() - if base64_str: - # 将 base64 字符串转换为字节类型 - image_bytes = base64.b64decode(base64_str) - storage_emoji(image_bytes) - return await self.get_emoji_description(base64_str) - else: - return '[表情包]' + def translate_image(self) -> Optional[str]: + """处理图片类型的CQ码，返回base64字符串""" + if "url" not in self.params: + return None + return self.get_img() - async def translate_image(self) -> str: - """处理图片类型的CQ码，区分普通图片和表情包""" - # 没有url，直接返回默认文本 - if 'url' not in self.params: - return '[图片]' - base64_str = self.get_img() - if base64_str: - image_bytes = base64.b64decode(base64_str) - storage_image(image_bytes) - return await self.get_image_description(base64_str) - else: - return '[图片]' - - async def get_emoji_description(self, image_base64: str) -> str: - """调用AI接口获取表情包描述""" + def translate_forward(self) -> Optional[List[Seg]]: + """处理转发消息，返回Seg列表""" try: - prompt = "这是一个表情包，请用简短的中文描述这个表情包传达的情感和含义。最多20个字。" - # description, _ = self._llm.generate_response_for_image_sync(prompt, image_base64) - description, _ = await self._llm.generate_response_for_image(prompt, image_base64) - return f"[表情包：{description}]" - except Exception as e: - logger.exception(f"AI接口调用失败: {str(e)}") - return "[表情包]" + if "content" not in self.params: + return None - async def get_image_description(self, image_base64: str) -> str: - """调用AI接口获取普通图片描述""" - try: - prompt = "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。" - # description, _ = self._llm.generate_response_for_image_sync(prompt, image_base64) - description, _ = await self._llm.generate_response_for_image(prompt, image_base64) - return f"[图片：{description}]" - except Exception as e: - logger.exception(f"AI接口调用失败: {str(e)}") - return "[图片]" - - async def translate_forward(self) -> str: - """处理转发消息""" - try: - if 'content' not in self.params: - return '[转发消息]' - - # 解析content内容（需要先反转义） - content = self.unescape(self.params['content']) - # print(f"\033[1;34m[调试信息]\033[0m 转发消息内容: {content}") - # 将字符串形式的列表转换为Python对象 + content = self.unescape(self.params["content"]) import ast + try: messages = ast.literal_eval(content) except ValueError as e: logger.error(f"解析转发消息内容失败: {str(e)}") - return '[转发消息]' + return None - # 处理每条消息 - formatted_messages = [] + formatted_segments = [] for msg in messages: - sender = msg.get('sender', {}) - nickname = sender.get('card') or sender.get('nickname', '未知用户') - - # 获取消息内容并使用Message类处理 - raw_message = msg.get('raw_message', '') - message_array = msg.get('message', []) + sender = msg.get("sender", {}) + nickname = sender.get("card") or sender.get("nickname", "未知用户") + raw_message = msg.get("raw_message", "") + message_array = msg.get("message", []) if message_array and isinstance(message_array, list): - # 检查是否包含嵌套的转发消息 for message_part in message_array: - if message_part.get('type') == 'forward': - content = '[转发消息]' + if message_part.get("type") == "forward": + content_seg = Seg(type="text", data="[转发消息]") break - else: - # 处理普通消息 - if raw_message: - from .message import Message - message_obj = Message( - user_id=msg.get('user_id', 0), - message_id=msg.get('message_id', 0), - raw_message=raw_message, - plain_text=raw_message, - group_id=msg.get('group_id', 0) - ) - await message_obj.initialize() - content = message_obj.processed_plain_text else: - content = '[空消息]' + if raw_message: + from .message_cq import MessageRecvCQ + user_info=UserInfo( + platform='qq', + user_id=msg.get("user_id", 0), + user_nickname=nickname, + ) + group_info=GroupInfo( + platform='qq', + group_id=msg.get("group_id", 0), + group_name=get_groupname(msg.get("group_id", 0)) + ) + + message_obj = MessageRecvCQ( + message_id=msg.get("message_id", 0), + user_info=user_info, + raw_message=raw_message, + plain_text=raw_message, + group_info=group_info, + ) + content_seg = Seg( + type="seglist", data=message_obj.message_segment ) + else: + content_seg = Seg(type="text", data="[空消息]") else: - # 处理普通消息 if raw_message: - from .message import Message - message_obj = Message( - user_id=msg.get('user_id', 0), - message_id=msg.get('message_id', 0), + from .message_cq import MessageRecvCQ + + user_info=UserInfo( + platform='qq', + user_id=msg.get("user_id", 0), + user_nickname=nickname, + ) + group_info=GroupInfo( + platform='qq', + group_id=msg.get("group_id", 0), + group_name=get_groupname(msg.get("group_id", 0)) + ) + message_obj = MessageRecvCQ( + message_id=msg.get("message_id", 0), + user_info=user_info, raw_message=raw_message, plain_text=raw_message, - group_id=msg.get('group_id', 0) + group_info=group_info, + ) + content_seg = Seg( + type="seglist", data=message_obj.message_segment ) - await message_obj.initialize() - content = message_obj.processed_plain_text else: - content = '[空消息]' + content_seg = Seg(type="text", data="[空消息]") - formatted_msg = f"{nickname}: {content}" - formatted_messages.append(formatted_msg) + formatted_segments.append(Seg(type="text", data=f"{nickname}: ")) + formatted_segments.append(content_seg) + formatted_segments.append(Seg(type="text", data="\n")) - # 合并所有消息 - combined_messages = '\n'.join(formatted_messages) - logger.debug(f"合并后的转发消息: {combined_messages}") - return f"[转发消息:\n{combined_messages}]" + return formatted_segments - except Exception: - logger.exception("处理转发消息失败") - return '[转发消息]' + except Exception as e: + logger.error(f"处理转发消息失败: {str(e)}") + return None - async def translate_reply(self) -> str: - """处理回复类型的CQ码""" + def translate_reply(self) -> Optional[List[Seg]]: + """处理回复类型的CQ码，返回Seg列表""" + from .message_cq import MessageRecvCQ - # 创建Message对象 - from .message import Message - if self.reply_message == None: - # print(f"\033[1;31m[错误]\033[0m 回复消息为空") - return '[回复某人消息]' + if self.reply_message is None: + return None if self.reply_message.sender.user_id: - message_obj = Message( - user_id=self.reply_message.sender.user_id, + + message_obj = MessageRecvCQ( + user_info=UserInfo(user_id=self.reply_message.sender.user_id,user_nickname=self.reply_message.sender.get("nickname",None)), message_id=self.reply_message.message_id, raw_message=str(self.reply_message.message), - group_id=self.group_id + group_info=GroupInfo(group_id=self.reply_message.group_id), ) - await message_obj.initialize() - if message_obj.user_id == global_config.BOT_QQ: - return f"[回复 {global_config.BOT_NICKNAME} 的消息: {message_obj.processed_plain_text}]" - else: - return f"[回复 {self.reply_message.sender.nickname} 的消息: {message_obj.processed_plain_text}]" + segments = [] + if message_obj.message_info.user_info.user_id == global_config.BOT_QQ: + segments.append( + Seg( + type="text", data=f"[回复 {global_config.BOT_NICKNAME} 的消息: " + ) + ) + else: + segments.append( + Seg( + type="text", + data=f"[回复 {self.reply_message.sender.nickname} 的消息: ", + ) + ) + + segments.append(Seg(type="seglist", data=message_obj.message_segment)) + segments.append(Seg(type="text", data="]")) + return segments else: - logger.error("回复消息的sender.user_id为空") - return '[回复某人消息]' + return None @staticmethod def unescape(text: str) -> str: """反转义CQ码中的特殊字符""" - return text.replace(',', ',') \ - .replace('[', '[') \ - .replace(']', ']') \ - .replace('&', '&') - - @staticmethod - def create_emoji_cq(file_path: str) -> str: - """ - 创建表情包CQ码 - Args: - file_path: 本地表情包文件路径 - Returns: - 表情包CQ码字符串 - """ - base64_content = image_path_to_base64(file_path) - - # 生成CQ码，设置sub_type=1表示这是表情包 - return f"[CQ:image,file=base64://{base64_content},sub_type=1]" - + return ( + text.replace(",", ",") + .replace("[", "[") + .replace("]", "]") + .replace("&", "&") + ) class CQCode_tool: @staticmethod - async def cq_from_dict_to_class(cq_code: Dict, reply: Optional[Dict] = None) -> CQCode: + def cq_from_dict_to_class(cq_code: Dict,msg ,reply: Optional[Dict] = None) -> CQCode: """ 将CQ码字典转换为CQCode对象 - + Args: cq_code: CQ码字典 + msg: MessageCQ对象 reply: 回复消息的字典（可选） - + Returns: CQCode对象 """ # 处理字典形式的CQ码 # 从cq_code字典中获取type字段的值,如果不存在则默认为'text' - cq_type = cq_code.get('type', 'text') + cq_type = cq_code.get("type", "text") params = {} - if cq_type == 'text': - params['text'] = cq_code.get('data', {}).get('text', '') + if cq_type == "text": + params["text"] = cq_code.get("data", {}).get("text", "") else: - params = cq_code.get('data', {}) + params = cq_code.get("data", {}) instance = CQCode( type=cq_type, params=params, - group_id=0, - user_id=0, + group_info=msg.message_info.group_info, + user_info=msg.message_info.user_info, reply_message=reply ) # 进行翻译处理 - await instance.translate() + instance.translate() return instance @staticmethod @@ -378,5 +364,64 @@ class CQCode_tool: """ return f"[CQ:reply,id={message_id}]" + @staticmethod + def create_emoji_cq(file_path: str) -> str: + """ + 创建表情包CQ码 + Args: + file_path: 本地表情包文件路径 + Returns: + 表情包CQ码字符串 + """ + # 确保使用绝对路径 + abs_path = os.path.abspath(file_path) + # 转义特殊字符 + escaped_path = ( + abs_path.replace("&", "&") + .replace("[", "[") + .replace("]", "]") + .replace(",", ",") + ) + # 生成CQ码，设置sub_type=1表示这是表情包 + return f"[CQ:image,file=file:///{escaped_path},sub_type=1]" + + @staticmethod + def create_emoji_cq_base64(base64_data: str) -> str: + """ + 创建表情包CQ码 + Args: + base64_data: base64编码的表情包数据 + Returns: + 表情包CQ码字符串 + """ + # 转义base64数据 + escaped_base64 = ( + base64_data.replace("&", "&") + .replace("[", "[") + .replace("]", "]") + .replace(",", ",") + ) + # 生成CQ码，设置sub_type=1表示这是表情包 + return f"[CQ:image,file=base64://{escaped_base64},sub_type=1]" + + @staticmethod + def create_image_cq_base64(base64_data: str) -> str: + """ + 创建表情包CQ码 + Args: + base64_data: base64编码的表情包数据 + Returns: + 表情包CQ码字符串 + """ + # 转义base64数据 + escaped_base64 = ( + base64_data.replace("&", "&") + .replace("[", "[") + .replace("]", "]") + .replace(",", ",") + ) + # 生成CQ码，设置sub_type=1表示这是表情包 + return f"[CQ:image,file=base64://{escaped_base64},sub_type=0]" + cq_code_tool = CQCode_tool() diff --git a/src/plugins/chat/emoji_manager.py b/src/plugins/chat/emoji_manager.py index cec81518a..3adb952d3 100644 --- a/src/plugins/chat/emoji_manager.py +++ b/src/plugins/chat/emoji_manager.py @@ -1,9 +1,11 @@ import asyncio +import base64 +import hashlib import os import random import time import traceback -from typing import Optional +from typing import Optional, Tuple from loguru import logger from nonebot import get_driver @@ -11,11 +13,12 @@ from nonebot import get_driver from ...common.database import Database from ..chat.config import global_config from ..chat.utils import get_embedding -from ..chat.utils_image import image_path_to_base64 +from ..chat.utils_image import ImageManager, image_path_to_base64 from ..models.utils_model import LLM_request driver = get_driver() config = driver.config +image_manager = ImageManager() class EmojiManager: @@ -76,7 +79,6 @@ class EmojiManager: if 'emoji' not in self.db.db.list_collection_names(): self.db.db.create_collection('emoji') self.db.db.emoji.create_index([('embedding', '2dsphere')]) - self.db.db.emoji.create_index([('tags', 1)]) self.db.db.emoji.create_index([('filename', 1)], unique=True) def record_usage(self, emoji_id: str): @@ -87,10 +89,10 @@ class EmojiManager: {'_id': emoji_id}, {'$inc': {'usage_count': 1}} ) - except Exception: - logger.exception("记录表情使用失败") - - async def get_emoji_for_text(self, text: str) -> Optional[str]: + except Exception as e: + logger.error(f"记录表情使用失败: {str(e)}") + + async def get_emoji_for_text(self, text: str) -> Optional[Tuple[str,str]]: """根据文本内容获取相关表情包 Args: text: 输入文本 @@ -144,15 +146,15 @@ class EmojiManager: emoji_similarities.sort(key=lambda x: x[1], reverse=True) # 获取前3个最相似的表情包 - top_3_emojis = emoji_similarities[:3] - - if not top_3_emojis: + top_10_emojis = emoji_similarities[:10 if len(emoji_similarities) > 10 else len(emoji_similarities)] + + if not top_10_emojis: logger.warning("未找到匹配的表情包") return None # 从前3个中随机选择一个 - selected_emoji, similarity = random.choice(top_3_emojis) - + selected_emoji, similarity = random.choice(top_10_emojis) + if selected_emoji and 'path' in selected_emoji: # 更新使用次数 self.db.db.emoji.update_one( @@ -174,15 +176,15 @@ class EmojiManager: logger.error(f"获取表情包失败: {str(e)}") return None - async def _get_emoji_description(self, image_base64: str) -> str: - """获取表情包的标签""" + async def _get_emoji_discription(self, image_base64: str) -> str: + """获取表情包的标签，使用image_manager的描述生成功能""" try: - prompt = '这是一个表情包，使用中文简洁的描述一下表情包的内容和表情包所表达的情感' - - content, _ = await self.vlm.generate_response_for_image(prompt, image_base64) - logger.debug(f"输出描述: {content}") - return content - + # 使用image_manager获取描述，去掉前后的方括号和"表情包："前缀 + description = await image_manager.get_emoji_description(image_base64) + # 去掉[表情包：xxx]的格式，只保留描述内容 + description = description.strip('[]').replace('表情包：', '') + return description + except Exception as e: logger.error(f"获取标签失败: {str(e)}") return None @@ -223,29 +225,66 @@ class EmojiManager: for filename in files_to_process: image_path = os.path.join(emoji_dir, filename) - - # 检查是否已经注册过 - existing_emoji = self.db.db['emoji'].find_one({'filename': filename}) - if existing_emoji: - continue - - # 压缩图片并获取base64编码 + + # 获取图片的base64编码和哈希值 image_base64 = image_path_to_base64(image_path) if image_base64 is None: os.remove(image_path) continue - - # 获取表情包的描述 - description = await self._get_emoji_description(image_base64) + + image_bytes = base64.b64decode(image_base64) + image_hash = hashlib.md5(image_bytes).hexdigest() + + # 检查是否已经注册过 + existing_emoji = self.db.db['emoji'].find_one({'filename': filename}) + description = None + + if existing_emoji: + # 即使表情包已存在，也检查是否需要同步到images集合 + description = existing_emoji.get('discription') + # 检查是否在images集合中存在 + existing_image = image_manager.db.db.images.find_one({'hash': image_hash}) + if not existing_image: + # 同步到images集合 + image_doc = { + 'hash': image_hash, + 'path': image_path, + 'type': 'emoji', + 'description': description, + 'timestamp': int(time.time()) + } + image_manager.db.db.images.update_one( + {'hash': image_hash}, + {'$set': image_doc}, + upsert=True + ) + # 保存描述到image_descriptions集合 + image_manager._save_description_to_db(image_hash, description, 'emoji') + logger.success(f"同步已存在的表情包到images集合: {filename}") + continue + + # 检查是否在images集合中已有描述 + existing_description = image_manager._get_description_from_db(image_hash, 'emoji') + + if existing_description: + description = existing_description + else: + # 获取表情包的描述 + description = await self._get_emoji_discription(image_base64) + if global_config.EMOJI_CHECK: check = await self._check_emoji(image_base64) if '是' not in check: os.remove(image_path) logger.info(f"描述: {description}") + logger.info(f"描述: {description}") logger.info(f"其不满足过滤规则，被剔除 {check}") continue logger.info(f"check通过 {check}") + if description is not None: + embedding = await get_embedding(description) + if description is not None: embedding = await get_embedding(description) # 准备数据库记录 @@ -253,14 +292,32 @@ class EmojiManager: 'filename': filename, 'path': image_path, 'embedding': embedding, - 'description': description, + 'discription': description, + 'hash': image_hash, 'timestamp': int(time.time()) } - - # 保存到数据库 + + # 保存到emoji数据库 self.db.db['emoji'].insert_one(emoji_record) logger.success(f"注册新表情包: {filename}") logger.info(f"描述: {description}") + + # 保存到images数据库 + image_doc = { + 'hash': image_hash, + 'path': image_path, + 'type': 'emoji', + 'description': description, + 'timestamp': int(time.time()) + } + image_manager.db.db.images.update_one( + {'hash': image_hash}, + {'$set': image_doc}, + upsert=True + ) + # 保存描述到image_descriptions集合 + image_manager._save_description_to_db(image_hash, description, 'emoji') + logger.success(f"同步保存到images集合: {filename}") else: logger.warning(f"跳过表情包: {filename}") diff --git a/src/plugins/chat/llm_generator.py b/src/plugins/chat/llm_generator.py index 4e431d9fd..af7334afe 100644 --- a/src/plugins/chat/llm_generator.py +++ b/src/plugins/chat/llm_generator.py @@ -8,7 +8,7 @@ from loguru import logger from ...common.database import Database from ..models.utils_model import LLM_request from .config import global_config -from .message import Message +from .message import MessageRecv, MessageThinking, MessageSending,Message from .prompt_builder import prompt_builder from .relationship_manager import relationship_manager from .utils import process_llm_response @@ -19,58 +19,89 @@ config = driver.config class ResponseGenerator: def __init__(self): - self.model_r1 = LLM_request(model=global_config.llm_reasoning, temperature=0.7,max_tokens=1000,stream=True) - self.model_v3 = LLM_request(model=global_config.llm_normal, temperature=0.7,max_tokens=1000) - self.model_r1_distill = LLM_request(model=global_config.llm_reasoning_minor, temperature=0.7,max_tokens=1000) - self.model_v25 = LLM_request(model=global_config.llm_normal_minor, temperature=0.7,max_tokens=1000) + self.model_r1 = LLM_request( + model=global_config.llm_reasoning, + temperature=0.7, + max_tokens=1000, + stream=True, + ) + self.model_v3 = LLM_request( + model=global_config.llm_normal, temperature=0.7, max_tokens=1000 + ) + self.model_r1_distill = LLM_request( + model=global_config.llm_reasoning_minor, temperature=0.7, max_tokens=1000 + ) + self.model_v25 = LLM_request( + model=global_config.llm_normal_minor, temperature=0.7, max_tokens=1000 + ) self.db = Database.get_instance() - self.current_model_type = 'r1' # 默认使用 R1 + self.current_model_type = "r1" # 默认使用 R1 - async def generate_response(self, message: Message) -> Optional[Union[str, List[str]]]: + async def generate_response( + self, message: MessageThinking + ) -> Optional[Union[str, List[str]]]: """根据当前模型类型选择对应的生成函数""" # 从global_config中获取模型概率值并选择模型 rand = random.random() if rand < global_config.MODEL_R1_PROBABILITY: - self.current_model_type = 'r1' + self.current_model_type = "r1" current_model = self.model_r1 - elif rand < global_config.MODEL_R1_PROBABILITY + global_config.MODEL_V3_PROBABILITY: - self.current_model_type = 'v3' + elif ( + rand + < global_config.MODEL_R1_PROBABILITY + global_config.MODEL_V3_PROBABILITY + ): + self.current_model_type = "v3" current_model = self.model_v3 else: - self.current_model_type = 'r1_distill' + self.current_model_type = "r1_distill" current_model = self.model_r1_distill logger.info(f"{global_config.BOT_NICKNAME}{self.current_model_type}思考中") - - model_response = await self._generate_response_with_model(message, current_model) - raw_content=model_response + + model_response = await self._generate_response_with_model( + message, current_model + ) + raw_content = model_response + + # print(f"raw_content: {raw_content}") + # print(f"model_response: {model_response}") if model_response: logger.info(f'{global_config.BOT_NICKNAME}的回复是：{model_response}') model_response = await self._process_response(model_response) if model_response: + return model_response, raw_content + return None, raw_content - return model_response ,raw_content - return None,raw_content - - async def _generate_response_with_model(self, message: Message, model: LLM_request) -> Optional[str]: + async def _generate_response_with_model( + self, message: MessageThinking, model: LLM_request + ) -> Optional[str]: """使用指定的模型生成回复""" - sender_name = message.user_nickname or f"用户{message.user_id}" - if message.user_cardname: - sender_name=f"[({message.user_id}){message.user_nickname}]{message.user_cardname}" - + sender_name = ( + message.chat_stream.user_info.user_nickname + or f"用户{message.chat_stream.user_info.user_id}" + ) + if message.chat_stream.user_info.user_cardname: + sender_name = f"[({message.chat_stream.user_info.user_id}){message.chat_stream.user_info.user_nickname}]{message.chat_stream.user_info.user_cardname}" + # 获取关系值 - relationship_value = relationship_manager.get_relationship(message.user_id).relationship_value if relationship_manager.get_relationship(message.user_id) else 0.0 + relationship_value = ( + relationship_manager.get_relationship( + message.chat_stream + ).relationship_value + if relationship_manager.get_relationship(message.chat_stream) + else 0.0 + ) if relationship_value != 0.0: # print(f"\033[1;32m[关系管理]\033[0m 回复中_当前关系值: {relationship_value}") pass - + # 构建prompt prompt, prompt_check = await prompt_builder._build_prompt( message_txt=message.processed_plain_text, sender_name=sender_name, relationship_value=relationship_value, - group_id=message.group_id + stream_id=message.chat_stream.stream_id, ) # 读空气模块 简化逻辑，先停用 @@ -96,7 +127,7 @@ class ResponseGenerator: except Exception: logger.exception("生成回复时出错") return None - + # 保存到数据库 self._save_to_db( message=message, @@ -108,54 +139,73 @@ class ResponseGenerator: reasoning_content=reasoning_content, # reasoning_content_check=reasoning_content_check if global_config.enable_kuuki_read else "" ) - + return content # def _save_to_db(self, message: Message, sender_name: str, prompt: str, prompt_check: str, # content: str, content_check: str, reasoning_content: str, reasoning_content_check: str): - def _save_to_db(self, message: Message, sender_name: str, prompt: str, prompt_check: str, - content: str, reasoning_content: str,): + def _save_to_db( + self, + message: MessageRecv, + sender_name: str, + prompt: str, + prompt_check: str, + content: str, + reasoning_content: str, + ): """保存对话记录到数据库""" - self.db.db.reasoning_logs.insert_one({ - 'time': time.time(), - 'group_id': message.group_id, - 'user': sender_name, - 'message': message.processed_plain_text, - 'model': self.current_model_type, - # 'reasoning_check': reasoning_content_check, - # 'response_check': content_check, - 'reasoning': reasoning_content, - 'response': content, - 'prompt': prompt, - 'prompt_check': prompt_check - }) + self.db.db.reasoning_logs.insert_one( + { + "time": time.time(), + "chat_id": message.chat_stream.stream_id, + "user": sender_name, + "message": message.processed_plain_text, + "model": self.current_model_type, + # 'reasoning_check': reasoning_content_check, + # 'response_check': content_check, + "reasoning": reasoning_content, + "response": content, + "prompt": prompt, + "prompt_check": prompt_check, + } + ) async def _get_emotion_tags(self, content: str) -> List[str]: """提取情感标签""" try: - prompt = f'''请从以下内容中，从"happy,angry,sad,surprised,disgusted,fearful,neutral"中选出最匹配的1个情感标签并输出 + prompt = f"""请从以下内容中，从"happy,angry,sad,surprised,disgusted,fearful,neutral"中选出最匹配的1个情感标签并输出 只输出标签就好，不要输出其他内容: 内容：{content} 输出： - ''' + """ content, _ = await self.model_v25.generate_response(prompt) - content=content.strip() - if content in ['happy','angry','sad','surprised','disgusted','fearful','neutral']: + content = content.strip() + if content in [ + "happy", + "angry", + "sad", + "surprised", + "disgusted", + "fearful", + "neutral", + ]: return [content] else: return ["neutral"] - - except Exception: - logger.exception("获取情感标签时出错") + + except Exception as e: + print(f"获取情感标签时出错: {e}") return ["neutral"] - + async def _process_response(self, content: str) -> Tuple[List[str], List[str]]: """处理响应内容，返回处理后的内容和情感标签""" if not content: return None, [] - + processed_response = process_llm_response(content) + # print(f"得到了处理后的llm返回{processed_response}") + return processed_response diff --git a/src/plugins/chat/message.py b/src/plugins/chat/message.py index f1fc5569d..5eb93d700 100644 --- a/src/plugins/chat/message.py +++ b/src/plugins/chat/message.py @@ -1,231 +1,386 @@ import time from dataclasses import dataclass -from typing import Dict, ForwardRef, List, Optional +from typing import Dict, ForwardRef, List, Optional, Union import urllib3 +from loguru import logger -from .cq_code import CQCode, cq_code_tool -from .utils_cq import parse_cq_code -from .utils_user import get_groupname, get_user_cardname, get_user_nickname - -Message = ForwardRef('Message') # 添加这行 +from .utils_image import image_manager +from .message_base import Seg, GroupInfo, UserInfo, BaseMessageInfo, MessageBase +from .chat_stream import ChatStream, chat_manager # 禁用SSL警告 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) #这个类是消息数据类，用于存储和管理消息数据。 #它定义了消息的属性，包括群组ID、用户ID、消息ID、原始消息内容、纯文本内容和时间戳。 #它还定义了两个辅助属性：keywords用于提取消息的关键词，is_plain_text用于判断消息是否为纯文本。 + +@dataclass +class MessageRecv(MessageBase): + """接收消息类，用于处理从MessageCQ序列化的消息""" + + def __init__(self, message_dict: Dict): + """从MessageCQ的字典初始化 + + Args: + message_dict: MessageCQ序列化后的字典 + """ + message_info = BaseMessageInfo.from_dict(message_dict.get('message_info', {})) + message_segment = Seg.from_dict(message_dict.get('message_segment', {})) + raw_message = message_dict.get('raw_message') + + super().__init__( + message_info=message_info, + message_segment=message_segment, + raw_message=raw_message + ) + + # 处理消息内容 + self.processed_plain_text = "" # 初始化为空字符串 + self.detailed_plain_text = "" # 初始化为空字符串 + self.is_emoji=False + def update_chat_stream(self,chat_stream:ChatStream): + self.chat_stream=chat_stream + + async def process(self) -> None: + """处理消息内容，生成纯文本和详细文本 + + 这个方法必须在创建实例后显式调用，因为它包含异步操作。 + """ + self.processed_plain_text = await self._process_message_segments(self.message_segment) + self.detailed_plain_text = self._generate_detailed_text() + async def _process_message_segments(self, segment: Seg) -> str: + """递归处理消息段，转换为文字描述 + + Args: + segment: 要处理的消息段 + + Returns: + str: 处理后的文本 + """ + if segment.type == 'seglist': + # 处理消息段列表 + segments_text = [] + for seg in segment.data: + processed = await self._process_message_segments(seg) + if processed: + segments_text.append(processed) + return ' '.join(segments_text) + else: + # 处理单个消息段 + return await self._process_single_segment(segment) + + async def _process_single_segment(self, seg: Seg) -> str: + """处理单个消息段 + + Args: + seg: 要处理的消息段 + + Returns: + str: 处理后的文本 + """ + try: + if seg.type == 'text': + return seg.data + elif seg.type == 'image': + # 如果是base64图片数据 + if isinstance(seg.data, str): + return await image_manager.get_image_description(seg.data) + return '[图片]' + elif seg.type == 'emoji': + self.is_emoji=True + if isinstance(seg.data, str): + return await image_manager.get_emoji_description(seg.data) + return '[表情]' + else: + return f"[{seg.type}:{str(seg.data)}]" + except Exception as e: + logger.error(f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}") + return f"[处理失败的{seg.type}消息]" + + def _generate_detailed_text(self) -> str: + """生成详细文本，包含时间和用户信息""" + time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.message_info.time)) + user_info = self.message_info.user_info + name = ( + f"{user_info.user_nickname}(ta的昵称:{user_info.user_cardname},ta的id:{user_info.user_id})" + if user_info.user_cardname!='' + else f"{user_info.user_nickname}(ta的id:{user_info.user_id})" + ) + return f"[{time_str}] {name}: {self.processed_plain_text}\n" + +@dataclass +class Message(MessageBase): + chat_stream: ChatStream=None + reply: Optional['Message'] = None + detailed_plain_text: str = "" + processed_plain_text: str = "" + + def __init__( + self, + message_id: str, + time: int, + chat_stream: ChatStream, + user_info: UserInfo, + message_segment: Optional[Seg] = None, + reply: Optional['MessageRecv'] = None, + detailed_plain_text: str = "", + processed_plain_text: str = "", + ): + # 构造基础消息信息 + message_info = BaseMessageInfo( + platform=chat_stream.platform, + message_id=message_id, + time=time, + group_info=chat_stream.group_info, + user_info=user_info + ) + + # 调用父类初始化 + super().__init__( + message_info=message_info, + message_segment=message_segment, + raw_message=None + ) + + self.chat_stream = chat_stream + # 文本处理相关属性 + self.processed_plain_text = detailed_plain_text + self.detailed_plain_text = processed_plain_text + + # 回复消息 + self.reply = reply @dataclass -class Message: - """消息数据类""" - message_id: int = None - time: float = None - - group_id: int = None - group_name: str = None # 群名称 - - user_id: int = None - user_nickname: str = None # 用户昵称 - user_cardname: str = None # 用户群昵称 - - raw_message: str = None # 原始消息，包含未解析的cq码 - plain_text: str = None # 纯文本 - - reply_message: Dict = None # 存储 回复的 源消息 - - # 延迟初始化字段 - _initialized: bool = False - message_segments: List[Dict] = None # 存储解析后的消息片段 - processed_plain_text: str = None # 用于存储处理后的plain_text - detailed_plain_text: str = None # 用于存储详细可读文本 - - # 状态标志 - is_emoji: bool = False - has_emoji: bool = False - translate_cq: bool = True - - async def initialize(self): - """显式异步初始化方法（必须调用）""" - if self._initialized: - return - - # 异步获取补充信息 - self.group_name = self.group_name or get_groupname(self.group_id) - self.user_nickname = self.user_nickname or get_user_nickname(self.user_id) - self.user_cardname = self.user_cardname or get_user_cardname(self.user_id) - - # 消息解析 - if self.raw_message: - if not isinstance(self,Message_Sending): - self.message_segments = await self.parse_message_segments(self.raw_message) - self.processed_plain_text = ' '.join( - seg.translated_plain_text - for seg in self.message_segments - ) - - # 构建详细文本 - if self.time is None: - self.time = int(time.time()) - time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.time)) - name = ( - f"{self.user_nickname}(ta的昵称:{self.user_cardname},ta的id:{self.user_id})" - if self.user_cardname - else f"{self.user_nickname or f'用户{self.user_id}'}" - ) - if isinstance(self,Message_Sending) and self.is_emoji: - self.detailed_plain_text = f"[{time_str}] {name}: {self.detailed_plain_text}\n" - else: - self.detailed_plain_text = f"[{time_str}] {name}: {self.processed_plain_text}\n" - - self._initialized = True +class MessageProcessBase(Message): + """消息处理基类，用于处理中和发送中的消息""" - async def parse_message_segments(self, message: str) -> List[CQCode]: - """ - 将消息解析为片段列表，包括纯文本和CQ码 - 返回的列表中每个元素都是字典，包含： - - cq_code_list:分割出的聊天对象，包括文本和CQ码 - - trans_list:翻译后的对象列表 - """ - # print(f"\033[1;34m[调试信息]\033[0m 正在处理消息: {message}") - cq_code_dict_list = [] - trans_list = [] - - start = 0 - while True: - # 查找下一个CQ码的开始位置 - cq_start = message.find('[CQ:', start) - #如果没有cq码，直接返回文本内容 - if cq_start == -1: - # 如果没有找到更多CQ码，添加剩余文本 - if start < len(message): - text = message[start:].strip() - if text: # 只添加非空文本 - cq_code_dict_list.append(parse_cq_code(text)) - break - # 添加CQ码前的文本 - if cq_start > start: - text = message[start:cq_start].strip() - if text: # 只添加非空文本 - cq_code_dict_list.append(parse_cq_code(text)) - # 查找CQ码的结束位置 - cq_end = message.find(']', cq_start) - if cq_end == -1: - # CQ码未闭合，作为普通文本处理 - text = message[cq_start:].strip() - if text: - cq_code_dict_list.append(parse_cq_code(text)) - break - cq_code = message[cq_start:cq_end + 1] - - #将cq_code解析成字典 - cq_code_dict_list.append(parse_cq_code(cq_code)) - # 更新start位置到当前CQ码之后 - start = cq_end + 1 - - # print(f"\033[1;34m[调试信息]\033[0m 提取的消息对象：列表: {cq_code_dict_list}") - - #判定是否是表情包消息，以及是否含有表情包 - if len(cq_code_dict_list) == 1 and cq_code_dict_list[0]['type'] == 'image': - self.is_emoji = True - self.has_emoji_emoji = True - else: - for segment in cq_code_dict_list: - if segment['type'] == 'image' and segment['data'].get('sub_type') == '1': - self.has_emoji_emoji = True - break - - - #翻译作为字典的CQ码 - for _code_item in cq_code_dict_list: - message_obj = await cq_code_tool.cq_from_dict_to_class(_code_item,reply = self.reply_message) - trans_list.append(message_obj) - return trans_list + def __init__( + self, + message_id: str, + chat_stream: ChatStream, + bot_user_info: UserInfo, + message_segment: Optional[Seg] = None, + reply: Optional['MessageRecv'] = None + ): + # 调用父类初始化 + super().__init__( + message_id=message_id, + time=int(time.time()), + chat_stream=chat_stream, + user_info=bot_user_info, + message_segment=message_segment, + reply=reply + ) -class Message_Thinking: - """消息思考类""" - def __init__(self, message: Message,message_id: str): - # 复制原始消息的基本属性 - self.group_id = message.group_id - self.user_id = message.user_id - self.user_nickname = message.user_nickname - self.user_cardname = message.user_cardname - self.group_name = message.group_name - - self.message_id = message_id - - # 思考状态相关属性 + # 处理状态相关属性 self.thinking_start_time = int(time.time()) self.thinking_time = 0 - self.interupt=False - - def update_thinking_time(self): - self.thinking_time = round(time.time(), 2) - self.thinking_start_time - -@dataclass -class Message_Sending(Message): - """发送中的消息类""" - thinking_start_time: float = None # 思考开始时间 - thinking_time: float = None # 思考时间 - - reply_message_id: int = None # 存储 回复的 源消息ID - - is_head: bool = False # 是否是头部消息 - - def update_thinking_time(self): - self.thinking_time = round(time.time(), 2) - self.thinking_start_time + def update_thinking_time(self) -> float: + """更新思考时间""" + self.thinking_time = round(time.time() - self.thinking_start_time, 2) return self.thinking_time + async def _process_message_segments(self, segment: Seg) -> str: + """递归处理消息段，转换为文字描述 + + Args: + segment: 要处理的消息段 + + Returns: + str: 处理后的文本 + """ + if segment.type == 'seglist': + # 处理消息段列表 + segments_text = [] + for seg in segment.data: + processed = await self._process_message_segments(seg) + if processed: + segments_text.append(processed) + return ' '.join(segments_text) + else: + # 处理单个消息段 + return await self._process_single_segment(segment) - + async def _process_single_segment(self, seg: Seg) -> str: + """处理单个消息段 + + Args: + seg: 要处理的消息段 + + Returns: + str: 处理后的文本 + """ + try: + if seg.type == 'text': + return seg.data + elif seg.type == 'image': + # 如果是base64图片数据 + if isinstance(seg.data, str): + return await image_manager.get_image_description(seg.data) + return '[图片]' + elif seg.type == 'emoji': + if isinstance(seg.data, str): + return await image_manager.get_emoji_description(seg.data) + return '[表情]' + elif seg.type == 'at': + return f"[@{seg.data}]" + elif seg.type == 'reply': + if self.reply and hasattr(self.reply, 'processed_plain_text'): + return f"[回复：{self.reply.processed_plain_text}]" + else: + return f"[{seg.type}:{str(seg.data)}]" + except Exception as e: + logger.error(f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}") + return f"[处理失败的{seg.type}消息]" + + def _generate_detailed_text(self) -> str: + """生成详细文本，包含时间和用户信息""" + time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.message_info.time)) + user_info = self.message_info.user_info + name = ( + f"{user_info.user_nickname}(ta的昵称:{user_info.user_cardname},ta的id:{user_info.user_id})" + if user_info.user_cardname != '' + else f"{user_info.user_nickname}(ta的id:{user_info.user_id})" + ) + return f"[{time_str}] {name}: {self.processed_plain_text}\n" + +@dataclass +class MessageThinking(MessageProcessBase): + """思考状态的消息类""" + + def __init__( + self, + message_id: str, + chat_stream: ChatStream, + bot_user_info: UserInfo, + reply: Optional['MessageRecv'] = None + ): + # 调用父类初始化 + super().__init__( + message_id=message_id, + chat_stream=chat_stream, + bot_user_info=bot_user_info, + message_segment=None, # 思考状态不需要消息段 + reply=reply + ) + + # 思考状态特有属性 + self.interrupt = False + +@dataclass +class MessageSending(MessageProcessBase): + """发送状态的消息类""" + + def __init__( + self, + message_id: str, + chat_stream: ChatStream, + bot_user_info: UserInfo, + message_segment: Seg, + reply: Optional['MessageRecv'] = None, + is_head: bool = False, + is_emoji: bool = False + ): + # 调用父类初始化 + super().__init__( + message_id=message_id, + chat_stream=chat_stream, + bot_user_info=bot_user_info, + message_segment=message_segment, + reply=reply + ) + + # 发送状态特有属性 + self.reply_to_message_id = reply.message_info.message_id if reply else None + self.is_head = is_head + self.is_emoji = is_emoji + + def set_reply(self, reply: Optional['MessageRecv']) -> None: + """设置回复消息""" + if reply: + self.reply = reply + self.reply_to_message_id = self.reply.message_info.message_id + self.message_segment = Seg(type='seglist', data=[ + Seg(type='reply', data=reply.message_info.message_id), + self.message_segment + ]) + + async def process(self) -> None: + """处理消息内容，生成纯文本和详细文本""" + if self.message_segment: + self.processed_plain_text = await self._process_message_segments(self.message_segment) + self.detailed_plain_text = self._generate_detailed_text() + + @classmethod + def from_thinking( + cls, + thinking: MessageThinking, + message_segment: Seg, + is_head: bool = False, + is_emoji: bool = False + ) -> 'MessageSending': + """从思考状态消息创建发送状态消息""" + return cls( + message_id=thinking.message_info.message_id, + chat_stream=thinking.chat_stream, + message_segment=message_segment, + bot_user_info=thinking.message_info.user_info, + reply=thinking.reply, + is_head=is_head, + is_emoji=is_emoji + ) + + def to_dict(self): + ret= super().to_dict() + ret['message_info']['user_info']=self.chat_stream.user_info.to_dict() + return ret + +@dataclass class MessageSet: """消息集合类，可以存储多个发送消息""" - def __init__(self, group_id: int, user_id: int, message_id: str): - self.group_id = group_id - self.user_id = user_id + def __init__(self, chat_stream: ChatStream, message_id: str): + self.chat_stream = chat_stream self.message_id = message_id - self.messages: List[Message_Sending] = [] # 修改类型标注 + self.messages: List[MessageSending] = [] self.time = round(time.time(), 2) - def add_message(self, message: Message_Sending) -> None: - """添加消息到集合，只接受Message_Sending类型""" - if not isinstance(message, Message_Sending): - raise TypeError("MessageSet只能添加Message_Sending类型的消息") + def add_message(self, message: MessageSending) -> None: + """添加消息到集合""" + if not isinstance(message, MessageSending): + raise TypeError("MessageSet只能添加MessageSending类型的消息") self.messages.append(message) - # 按时间排序 - self.messages.sort(key=lambda x: x.time) + self.messages.sort(key=lambda x: x.message_info.time) - def get_message_by_index(self, index: int) -> Optional[Message_Sending]: + def get_message_by_index(self, index: int) -> Optional[MessageSending]: """通过索引获取消息""" if 0 <= index < len(self.messages): return self.messages[index] return None - def get_message_by_time(self, target_time: float) -> Optional[Message_Sending]: + def get_message_by_time(self, target_time: float) -> Optional[MessageSending]: """获取最接近指定时间的消息""" if not self.messages: return None - # 使用二分查找找到最接近的消息 left, right = 0, len(self.messages) - 1 while left < right: mid = (left + right) // 2 - if self.messages[mid].time < target_time: + if self.messages[mid].message_info.time < target_time: left = mid + 1 else: right = mid return self.messages[left] - def clear_messages(self) -> None: """清空所有消息""" self.messages.clear() - def remove_message(self, message: Message_Sending) -> bool: + def remove_message(self, message: MessageSending) -> bool: """移除指定消息""" if message in self.messages: self.messages.remove(message) diff --git a/src/plugins/chat/message_base.py b/src/plugins/chat/message_base.py new file mode 100644 index 000000000..d17c2c357 --- /dev/null +++ b/src/plugins/chat/message_base.py @@ -0,0 +1,186 @@ +from dataclasses import dataclass, asdict +from typing import List, Optional, Union, Any, Dict + +@dataclass +class Seg: + """消息片段类，用于表示消息的不同部分 + + Attributes: + type: 片段类型，可以是 'text'、'image'、'seglist' 等 + data: 片段的具体内容 + - 对于 text 类型，data 是字符串 + - 对于 image 类型，data 是 base64 字符串 + - 对于 seglist 类型，data 是 Seg 列表 + translated_data: 经过翻译处理的数据（可选） + """ + type: str + data: Union[str, List['Seg']] + + + # def __init__(self, type: str, data: Union[str, List['Seg']],): + # """初始化实例，确保字典和属性同步""" + # # 先初始化字典 + # self.type = type + # self.data = data + + @classmethod + def from_dict(cls, data: Dict) -> 'Seg': + """从字典创建Seg实例""" + type=data.get('type') + data=data.get('data') + if type == 'seglist': + data = [Seg.from_dict(seg) for seg in data] + return cls( + type=type, + data=data + ) + + def to_dict(self) -> Dict: + """转换为字典格式""" + result = {'type': self.type} + if self.type == 'seglist': + result['data'] = [seg.to_dict() for seg in self.data] + else: + result['data'] = self.data + return result + +@dataclass +class GroupInfo: + """群组信息类""" + platform: Optional[str] = None + group_id: Optional[int] = None + group_name: Optional[str] = None # 群名称 + + def to_dict(self) -> Dict: + """转换为字典格式""" + return {k: v for k, v in asdict(self).items() if v is not None} + + @classmethod + def from_dict(cls, data: Dict) -> 'GroupInfo': + """从字典创建GroupInfo实例 + + Args: + data: 包含必要字段的字典 + + Returns: + GroupInfo: 新的实例 + """ + return cls( + platform=data.get('platform'), + group_id=data.get('group_id'), + group_name=data.get('group_name',None) + ) + +@dataclass +class UserInfo: + """用户信息类""" + platform: Optional[str] = None + user_id: Optional[int] = None + user_nickname: Optional[str] = None # 用户昵称 + user_cardname: Optional[str] = None # 用户群昵称 + + def to_dict(self) -> Dict: + """转换为字典格式""" + return {k: v for k, v in asdict(self).items() if v is not None} + + @classmethod + def from_dict(cls, data: Dict) -> 'UserInfo': + """从字典创建UserInfo实例 + + Args: + data: 包含必要字段的字典 + + Returns: + UserInfo: 新的实例 + """ + return cls( + platform=data.get('platform'), + user_id=data.get('user_id'), + user_nickname=data.get('user_nickname',None), + user_cardname=data.get('user_cardname',None) + ) + +@dataclass +class BaseMessageInfo: + """消息信息类""" + platform: Optional[str] = None + message_id: Union[str,int,None] = None + time: Optional[int] = None + group_info: Optional[GroupInfo] = None + user_info: Optional[UserInfo] = None + + def to_dict(self) -> Dict: + """转换为字典格式""" + result = {} + for field, value in asdict(self).items(): + if value is not None: + if isinstance(value, (GroupInfo, UserInfo)): + result[field] = value.to_dict() + else: + result[field] = value + return result + @classmethod + def from_dict(cls, data: Dict) -> 'BaseMessageInfo': + """从字典创建BaseMessageInfo实例 + + Args: + data: 包含必要字段的字典 + + Returns: + BaseMessageInfo: 新的实例 + """ + group_info = GroupInfo(**data.get('group_info', {})) + user_info = UserInfo(**data.get('user_info', {})) + return cls( + platform=data.get('platform'), + message_id=data.get('message_id'), + time=data.get('time'), + group_info=group_info, + user_info=user_info + ) + +@dataclass +class MessageBase: + """消息类""" + message_info: BaseMessageInfo + message_segment: Seg + raw_message: Optional[str] = None # 原始消息，包含未解析的cq码 + + def to_dict(self) -> Dict: + """转换为字典格式 + + Returns: + Dict: 包含所有非None字段的字典，其中： + - message_info: 转换为字典格式 + - message_segment: 转换为字典格式 + - raw_message: 如果存在则包含 + """ + result = { + 'message_info': self.message_info.to_dict(), + 'message_segment': self.message_segment.to_dict() + } + if self.raw_message is not None: + result['raw_message'] = self.raw_message + return result + + @classmethod + def from_dict(cls, data: Dict) -> 'MessageBase': + """从字典创建MessageBase实例 + + Args: + data: 包含必要字段的字典 + + Returns: + MessageBase: 新的实例 + """ + message_info = BaseMessageInfo(**data.get('message_info', {})) + message_segment = Seg(**data.get('message_segment', {})) + raw_message = data.get('raw_message',None) + return cls( + message_info=message_info, + message_segment=message_segment, + raw_message=raw_message + ) + + + diff --git a/src/plugins/chat/message_cq.py b/src/plugins/chat/message_cq.py new file mode 100644 index 000000000..6bfa47c3f --- /dev/null +++ b/src/plugins/chat/message_cq.py @@ -0,0 +1,169 @@ +import time +from dataclasses import dataclass +from typing import Dict, ForwardRef, List, Optional, Union + +import urllib3 + +from .cq_code import CQCode, cq_code_tool +from .utils_cq import parse_cq_code +from .utils_user import get_groupname, get_user_cardname, get_user_nickname +from .message_base import Seg, GroupInfo, UserInfo, BaseMessageInfo, MessageBase +# 禁用SSL警告 +urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) + +#这个类是消息数据类，用于存储和管理消息数据。 +#它定义了消息的属性，包括群组ID、用户ID、消息ID、原始消息内容、纯文本内容和时间戳。 +#它还定义了两个辅助属性：keywords用于提取消息的关键词，is_plain_text用于判断消息是否为纯文本。 + +@dataclass +class MessageCQ(MessageBase): + """QQ消息基类，继承自MessageBase + + 最小必要参数: + - message_id: 消息ID + - user_id: 发送者/接收者ID + - platform: 平台标识（默认为"qq"） + """ + def __init__( + self, + message_id: int, + user_info: UserInfo, + group_info: Optional[GroupInfo] = None, + platform: str = "qq" + ): + # 构造基础消息信息 + message_info = BaseMessageInfo( + platform=platform, + message_id=message_id, + time=int(time.time()), + group_info=group_info, + user_info=user_info + ) + # 调用父类初始化，message_segment 由子类设置 + super().__init__( + message_info=message_info, + message_segment=None, + raw_message=None + ) + +@dataclass +class MessageRecvCQ(MessageCQ): + """QQ接收消息类，用于解析raw_message到Seg对象""" + + def __init__( + self, + message_id: int, + user_info: UserInfo, + raw_message: str, + group_info: Optional[GroupInfo] = None, + platform: str = "qq", + reply_message: Optional[Dict] = None, + ): + # 调用父类初始化 + super().__init__(message_id, user_info, group_info, platform) + + if group_info.group_name is None: + group_info.group_name = get_groupname(group_info.group_id) + + # 解析消息段 + self.message_segment = self._parse_message(raw_message, reply_message) + self.raw_message = raw_message + + def _parse_message(self, message: str, reply_message: Optional[Dict] = None) -> Seg: + """解析消息内容为Seg对象""" + cq_code_dict_list = [] + segments = [] + + start = 0 + while True: + cq_start = message.find('[CQ:', start) + if cq_start == -1: + if start < len(message): + text = message[start:].strip() + if text: + cq_code_dict_list.append(parse_cq_code(text)) + break + + if cq_start > start: + text = message[start:cq_start].strip() + if text: + cq_code_dict_list.append(parse_cq_code(text)) + + cq_end = message.find(']', cq_start) + if cq_end == -1: + text = message[cq_start:].strip() + if text: + cq_code_dict_list.append(parse_cq_code(text)) + break + + cq_code = message[cq_start:cq_end + 1] + cq_code_dict_list.append(parse_cq_code(cq_code)) + start = cq_end + 1 + + # 转换CQ码为Seg对象 + for code_item in cq_code_dict_list: + message_obj = cq_code_tool.cq_from_dict_to_class(code_item,msg=self,reply=reply_message) + if message_obj.translated_segments: + segments.append(message_obj.translated_segments) + + # 如果只有一个segment，直接返回 + if len(segments) == 1: + return segments[0] + + # 否则返回seglist类型的Seg + return Seg(type='seglist', data=segments) + + def to_dict(self) -> Dict: + """转换为字典格式，包含所有必要信息""" + base_dict = super().to_dict() + return base_dict + +@dataclass +class MessageSendCQ(MessageCQ): + """QQ发送消息类，用于将Seg对象转换为raw_message""" + + def __init__( + self, + data: Dict + ): + # 调用父类初始化 + message_info = BaseMessageInfo.from_dict(data.get('message_info', {})) + message_segment = Seg.from_dict(data.get('message_segment', {})) + super().__init__( + message_info.message_id, + message_info.user_info, + message_info.group_info if message_info.group_info else None, + message_info.platform + ) + + self.message_segment = message_segment + self.raw_message = self._generate_raw_message() + + def _generate_raw_message(self, ) -> str: + """将Seg对象转换为raw_message""" + segments = [] + + # 处理消息段 + if self.message_segment.type == 'seglist': + for seg in self.message_segment.data: + segments.append(self._seg_to_cq_code(seg)) + else: + segments.append(self._seg_to_cq_code(self.message_segment)) + + return ''.join(segments) + + def _seg_to_cq_code(self, seg: Seg) -> str: + """将单个Seg对象转换为CQ码字符串""" + if seg.type == 'text': + return str(seg.data) + elif seg.type == 'image': + return cq_code_tool.create_image_cq_base64(seg.data) + elif seg.type == 'emoji': + return cq_code_tool.create_emoji_cq_base64(seg.data) + elif seg.type == 'at': + return f"[CQ:at,qq={seg.data}]" + elif seg.type == 'reply': + return cq_code_tool.create_reply_cq(int(seg.data)) + else: + return f"[{seg.data}]" + diff --git a/src/plugins/chat/message_sender.py b/src/plugins/chat/message_sender.py index 0fb40373e..9db74633f 100644 --- a/src/plugins/chat/message_sender.py +++ b/src/plugins/chat/message_sender.py @@ -6,10 +6,11 @@ from loguru import logger from nonebot.adapters.onebot.v11 import Bot from .cq_code import cq_code_tool -from .message import Message, Message_Sending, Message_Thinking, MessageSet +from .message_cq import MessageSendCQ +from .message import MessageSending, MessageThinking, MessageRecv,MessageSet from .storage import MessageStorage -from .utils import calculate_typing_time from .config import global_config +from .chat_stream import chat_manager class Message_Sender: @@ -24,64 +25,57 @@ class Message_Sender: """设置当前bot实例""" self._current_bot = bot - async def send_group_message( + async def send_message( self, - group_id: int, - send_text: str, - auto_escape: bool = False, - reply_message_id: int = None, - at_user_id: int = None + message: MessageSending, ) -> None: - - if not self._current_bot: - raise RuntimeError("Bot未设置，请先调用set_bot方法设置bot实例") - - message = send_text - - # 如果需要回复 - if reply_message_id: - reply_cq = cq_code_tool.create_reply_cq(reply_message_id) - message = reply_cq + message - - # 如果需要at - # if at_user_id: - # at_cq = cq_code_tool.create_at_cq(at_user_id) - # message = at_cq + " " + message - - typing_time = calculate_typing_time(message) - if typing_time > 10: - typing_time = 10 - await asyncio.sleep(typing_time) - - # 发送消息 - try: - await self._current_bot.send_group_msg( - group_id=group_id, - message=message, - auto_escape=auto_escape + """发送消息""" + if isinstance(message, MessageSending): + message_json = message.to_dict() + message_send=MessageSendCQ( + data=message_json ) - logger.debug(f"发送消息{message}成功") - except Exception: - logger.exception(f"发送消息{message}失败") + + if message_send.message_info.group_info: + try: + await self._current_bot.send_group_msg( + group_id=message.message_info.group_info.group_id, + message=message_send.raw_message, + auto_escape=False + ) + logger.success(f"[调试] 发送消息{message.processed_plain_text}成功") + except Exception as e: + logger.error(f"[调试] 发生错误 {e}") + logger.error(f"[调试] 发送消息{message.processed_plain_text}失败") + else: + try: + await self._current_bot.send_private_msg( + user_id=message.message_info.user_info.user_id, + message=message_send.raw_message, + auto_escape=False + ) + logger.success(f"[调试] 发送消息{message.processed_plain_text}成功") + except Exception as e: + logger.error(f"发生错误 {e}") + logger.error(f"[调试] 发送消息{message.processed_plain_text}失败") class MessageContainer: - """单个群的发送/思考消息容器""" - - def __init__(self, group_id: int, max_size: int = 100): - self.group_id = group_id + """单个聊天流的发送/思考消息容器""" + def __init__(self, chat_id: str, max_size: int = 100): + self.chat_id = chat_id self.max_size = max_size self.messages = [] self.last_send_time = 0 self.thinking_timeout = 20 # 思考超时时间（秒） - - def get_timeout_messages(self) -> List[Message_Sending]: + + def get_timeout_messages(self) -> List[MessageSending]: """获取所有超时的Message_Sending对象（思考时间超过30秒），按thinking_start_time排序""" current_time = time.time() timeout_messages = [] for msg in self.messages: - if isinstance(msg, Message_Sending): + if isinstance(msg, MessageSending): if current_time - msg.thinking_start_time > self.thinking_timeout: timeout_messages.append(msg) @@ -89,8 +83,8 @@ class MessageContainer: timeout_messages.sort(key=lambda x: x.thinking_start_time) return timeout_messages - - def get_earliest_message(self) -> Optional[Union[Message_Thinking, Message_Sending]]: + + def get_earliest_message(self) -> Optional[Union[MessageThinking, MessageSending]]: """获取thinking_start_time最早的消息对象""" if not self.messages: return None @@ -102,17 +96,16 @@ class MessageContainer: earliest_time = msg_time earliest_message = msg return earliest_message - - def add_message(self, message: Union[Message_Thinking, Message_Sending]) -> None: + + def add_message(self, message: Union[MessageThinking, MessageSending]) -> None: """添加消息到队列""" - # print(f"\033[1;32m[添加消息]\033[0m 添加消息到对应群") if isinstance(message, MessageSet): for single_message in message.messages: self.messages.append(single_message) else: self.messages.append(message) - - def remove_message(self, message: Union[Message_Thinking, Message_Sending]) -> bool: + + def remove_message(self, message: Union[MessageThinking, MessageSending]) -> bool: """移除消息，如果消息存在则返回True，否则返回False""" try: if message in self.messages: @@ -126,42 +119,40 @@ class MessageContainer: def has_messages(self) -> bool: """检查是否有待发送的消息""" return bool(self.messages) - - def get_all_messages(self) -> List[Union[Message, Message_Thinking]]: + + def get_all_messages(self) -> List[Union[MessageSending, MessageThinking]]: """获取所有消息""" return list(self.messages) class MessageManager: - """管理所有群的消息容器""" - + """管理所有聊天流的消息容器""" def __init__(self): - self.containers: Dict[int, MessageContainer] = {} + self.containers: Dict[str, MessageContainer] = {} # chat_id -> MessageContainer self.storage = MessageStorage() self._running = True - - def get_container(self, group_id: int) -> MessageContainer: - """获取或创建群的消息容器""" - if group_id not in self.containers: - self.containers[group_id] = MessageContainer(group_id) - return self.containers[group_id] - - def add_message(self, message: Union[Message_Thinking, Message_Sending, MessageSet]) -> None: - container = self.get_container(message.group_id) + + def get_container(self, chat_id: str) -> MessageContainer: + """获取或创建聊天流的消息容器""" + if chat_id not in self.containers: + self.containers[chat_id] = MessageContainer(chat_id) + return self.containers[chat_id] + + def add_message(self, message: Union[MessageThinking, MessageSending, MessageSet]) -> None: + chat_stream = message.chat_stream + if not chat_stream: + raise ValueError("无法找到对应的聊天流") + container = self.get_container(chat_stream.stream_id) container.add_message(message) - - async def process_group_messages(self, group_id: int): - """处理群消息""" - # if int(time.time() / 3) == time.time() / 3: - # print(f"\033[1;34m[调试]\033[0m 开始处理群{group_id}的消息") - container = self.get_container(group_id) + + async def process_chat_messages(self, chat_id: str): + """处理聊天流消息""" + container = self.get_container(chat_id) if container.has_messages(): - # 最早的对象，可能是思考消息，也可能是发送消息 - message_earliest = container.get_earliest_message() # 一个message_thinking or message_sending - - # 如果是思考消息 - if isinstance(message_earliest, Message_Thinking): - # 优先等待这条消息 + # print(f"处理有message的容器chat_id: {chat_id}") + message_earliest = container.get_earliest_message() + + if isinstance(message_earliest, MessageThinking): message_earliest.update_thinking_time() thinking_time = message_earliest.thinking_time print(f"消息正在思考中，已思考{int(thinking_time)}秒\r", end='', flush=True) @@ -170,47 +161,38 @@ class MessageManager: if thinking_time > global_config.thinking_timeout: logger.warning(f"消息思考超时({thinking_time}秒)，移除该消息") container.remove_message(message_earliest) - else: # 如果不是message_thinking就只能是message_sending - logger.debug(f"消息'{message_earliest.processed_plain_text}'正在发送中") - # 直接发，等什么呢 + else: + if message_earliest.is_head and message_earliest.update_thinking_time() > 30: - await message_sender.send_group_message(group_id, message_earliest.processed_plain_text, - auto_escape=False, - reply_message_id=message_earliest.reply_message_id) + await message_sender.send_message(message_earliest.set_reply()) else: - await message_sender.send_group_message(group_id, message_earliest.processed_plain_text, - auto_escape=False) - # 移除消息 - if message_earliest.is_emoji: - message_earliest.processed_plain_text = "[表情包]" - await self.storage.store_message(message_earliest, None) - + await message_sender.send_message(message_earliest) + await message_earliest.process() + + print(f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中") + + await self.storage.store_message(message_earliest, message_earliest.chat_stream,None) + container.remove_message(message_earliest) - - # 获取并处理超时消息 - message_timeout = container.get_timeout_messages() # 也许是一堆message_sending + + message_timeout = container.get_timeout_messages() if message_timeout: logger.warning(f"发现{len(message_timeout)}条超时消息") for msg in message_timeout: if msg == message_earliest: - continue # 跳过已经处理过的消息 - + continue + try: - # 发送 if msg.is_head and msg.update_thinking_time() > 30: - await message_sender.send_group_message(group_id, msg.processed_plain_text, - auto_escape=False, - reply_message_id=msg.reply_message_id) + await message_sender.send_message(msg.set_reply()) else: - await message_sender.send_group_message(group_id, msg.processed_plain_text, - auto_escape=False) - - # 如果是表情包，则替换为"[表情包]" - if msg.is_emoji: - msg.processed_plain_text = "[表情包]" - await self.storage.store_message(msg, None) - - # 安全地移除消息 + await message_sender.send_message(msg) + + # if msg.is_emoji: + # msg.processed_plain_text = "[表情包]" + await msg.process() + await self.storage.store_message(msg,msg.chat_stream, None) + if not container.remove_message(msg): logger.warning("尝试删除不存在的消息") except Exception: @@ -222,9 +204,9 @@ class MessageManager: while self._running: await asyncio.sleep(1) tasks = [] - for group_id in self.containers.keys(): - tasks.append(self.process_group_messages(group_id)) - + for chat_id in self.containers.keys(): + tasks.append(self.process_chat_messages(chat_id)) + await asyncio.gather(*tasks) diff --git a/src/plugins/chat/prompt_builder.py b/src/plugins/chat/prompt_builder.py index 0805caa5a..fec6c7926 100644 --- a/src/plugins/chat/prompt_builder.py +++ b/src/plugins/chat/prompt_builder.py @@ -9,6 +9,7 @@ from ..moods.moods import MoodManager from ..schedule.schedule_generator import bot_schedule from .config import global_config from .utils import get_embedding, get_recent_group_detailed_plain_text +from .chat_stream import ChatStream, chat_manager class PromptBuilder: @@ -17,11 +18,13 @@ class PromptBuilder: self.activate_messages = '' self.db = Database.get_instance() - async def _build_prompt(self, - message_txt: str, - sender_name: str = "某人", - relationship_value: float = 0.0, - group_id: Optional[int] = None) -> tuple[str, str]: + + + async def _build_prompt(self, + message_txt: str, + sender_name: str = "某人", + relationship_value: float = 0.0, + stream_id: Optional[int] = None) -> tuple[str, str]: """构建prompt Args: @@ -70,14 +73,20 @@ class PromptBuilder: logger.debug(f"知识检索耗时: {(end_time - start_time):.3f}秒") # 获取聊天上下文 + chat_in_group=True chat_talking_prompt = '' - if group_id: - chat_talking_prompt = get_recent_group_detailed_plain_text(self.db, group_id, - limit=global_config.MAX_CONTEXT_SIZE, - combine=True) - - chat_talking_prompt = f"以下是群里正在聊天的内容：\n{chat_talking_prompt}" - + if stream_id: + chat_talking_prompt = get_recent_group_detailed_plain_text(self.db, stream_id, limit=global_config.MAX_CONTEXT_SIZE,combine = True) + chat_stream=chat_manager.get_stream(stream_id) + if chat_stream.group_info: + chat_talking_prompt = f"以下是群里正在聊天的内容：\n{chat_talking_prompt}" + else: + chat_in_group=False + chat_talking_prompt = f"以下是你正在和{sender_name}私聊的内容：\n{chat_talking_prompt}" + # print(f"\033[1;34m[调试]\033[0m 已从数据库获取群 {group_id} 的消息记录:{chat_talking_prompt}") + + + # 使用新的记忆获取方法 memory_prompt = '' start_time = time.time() @@ -108,15 +117,10 @@ class PromptBuilder: # 激活prompt构建 activate_prompt = '' - activate_prompt = f"以上是群里正在进行的聊天，{memory_prompt} 现在昵称为 '{sender_name}' 的用户说的:{message_txt}。引起了你的注意,你和他{relation_prompt},{mood_prompt},你想要{relation_prompt_2}。" - - # 检测机器人相关词汇，改为关键词检测与反应功能了，提取到全局配置中 - # bot_keywords = ['人机', 'bot', '机器', '入机', 'robot', '机器人'] - # is_bot = any(keyword in message_txt.lower() for keyword in bot_keywords) - # if is_bot: - # is_bot_prompt = '有人说你是人机或者机器人，否定这一事实，攻击或反问他。注意，只有认为你是机器人才回复，否则不要否认' - # else: - # is_bot_prompt = '' + if chat_in_group: + activate_prompt = f"以上是群里正在进行的聊天，{memory_prompt} 现在昵称为 '{sender_name}' 的用户说的:{message_txt}。引起了你的注意,你和ta{relation_prompt},{mood_prompt},你想要{relation_prompt_2}。" + else: + activate_prompt = f"以上是你正在和{sender_name}私聊的内容，{memory_prompt} 现在昵称为 '{sender_name}' 的用户说的:{message_txt}。引起了你的注意,你和ta{relation_prompt},{mood_prompt},你想要{relation_prompt_2}。" # 关键词检测与反应 keywords_reaction_prompt = '' @@ -125,15 +129,19 @@ class PromptBuilder: if any(keyword in message_txt.lower() for keyword in rule.get("keywords", [])): logger.info(f"检测到以下关键词之一：{rule.get('keywords', [])}，触发反应：{rule.get('reaction', '')}") keywords_reaction_prompt += rule.get("reaction", "") + '，' - - # 人格选择 - personality = global_config.PROMPT_PERSONALITY + + #人格选择 + personality=global_config.PROMPT_PERSONALITY probability_1 = global_config.PERSONALITY_1 probability_2 = global_config.PERSONALITY_2 probability_3 = global_config.PERSONALITY_3 prompt_personality = f'{activate_prompt}你的网名叫{global_config.BOT_NICKNAME}，你还有很多别名:{"/".join(global_config.BOT_ALIAS_NAMES)}，' personality_choice = random.random() + if chat_in_group: + prompt_in_group=f"你正在浏览{chat_stream.platform}群" + else: + prompt_in_group=f"你正在{chat_stream.platform}上和{sender_name}私聊" if personality_choice < probability_1: # 第一种人格 prompt_personality += f'''{personality[0]}, 你正在浏览qq群,{promt_info_prompt}, 现在请你给出日常且口语化的回复，平淡一些，尽量简短一些。{keywords_reaction_prompt} diff --git a/src/plugins/chat/relationship_manager.py b/src/plugins/chat/relationship_manager.py index 4d82184c8..9e7cafda0 100644 --- a/src/plugins/chat/relationship_manager.py +++ b/src/plugins/chat/relationship_manager.py @@ -1,9 +1,11 @@ import asyncio +from typing import Optional, Union +from typing import Optional, Union from loguru import logger -from typing import Optional from ...common.database import Database - +from .message_base import UserInfo +from .chat_stream import ChatStream class Impression: traits: str = None @@ -15,92 +17,153 @@ class Impression: class Relationship: user_id: int = None - # impression: Impression = None - # group_id: int = None - # group_name: str = None + platform: str = None gender: str = None age: int = None nickname: str = None relationship_value: float = None saved = False - - def __init__(self, user_id: int, data=None, **kwargs): - if isinstance(data, dict): - # 如果输入是字典，使用字典解析 - self.user_id = data.get('user_id') - self.gender = data.get('gender') - self.age = data.get('age') - self.nickname = data.get('nickname') - self.relationship_value = data.get('relationship_value', 0.0) - self.saved = data.get('saved', False) - else: - # 如果是直接传入属性值 - self.user_id = kwargs.get('user_id') - self.gender = kwargs.get('gender') - self.age = kwargs.get('age') - self.nickname = kwargs.get('nickname') - self.relationship_value = kwargs.get('relationship_value', 0.0) - self.saved = kwargs.get('saved', False) - + + def __init__(self, chat:ChatStream=None,data:dict=None): + self.user_id=chat.user_info.user_id if chat else data.get('user_id',0) + self.platform=chat.platform if chat else data.get('platform','') + self.nickname=chat.user_info.user_nickname if chat else data.get('nickname','') + self.relationship_value=data.get('relationship_value',0) if data else 0 + self.age=data.get('age',0) if data else 0 + self.gender=data.get('gender','') if data else '' + class RelationshipManager: def __init__(self): - self.relationships: dict[int, Relationship] = {} - - async def update_relationship(self, user_id: int, data=None, **kwargs): + self.relationships: dict[tuple[int, str], Relationship] = {} # 修改为使用(user_id, platform)作为键 + + async def update_relationship(self, + chat_stream:ChatStream, + data: dict = None, + **kwargs) -> Optional[Relationship]: + """更新或创建关系 + Args: + chat_stream: 聊天流对象 + data: 字典格式的数据（可选） + **kwargs: 其他参数 + Returns: + Relationship: 关系对象 + """ + # 确定user_id和platform + if chat_stream.user_info is not None: + user_id = chat_stream.user_info.user_id + platform = chat_stream.user_info.platform or 'qq' + else: + platform = platform or 'qq' + + if user_id is None: + raise ValueError("必须提供user_id或user_info") + + # 使用(user_id, platform)作为键 + key = (user_id, platform) + # 检查是否在内存中已存在 - relationship = self.relationships.get(user_id) + relationship = self.relationships.get(key) if relationship: # 如果存在，更新现有对象 if isinstance(data, dict): - for key, value in data.items(): - if hasattr(relationship, key) and value is not None: - setattr(relationship, key, value) - else: - for key, value in kwargs.items(): - if hasattr(relationship, key) and value is not None: - setattr(relationship, key, value) + for k, value in data.items(): + if hasattr(relationship, k) and value is not None: + setattr(relationship, k, value) else: # 如果不存在，创建新对象 - relationship = Relationship(user_id, data=data) if isinstance(data, dict) else Relationship(user_id, - **kwargs) - self.relationships[user_id] = relationship - - # 更新 id_name_nickname_table - # self.id_name_nickname_table[user_id] = [relationship.nickname] # 别称设置为空列表 + if chat_stream.user_info is not None: + relationship = Relationship(chat=chat_stream, **kwargs) + else: + raise ValueError("必须提供user_id或user_info") + self.relationships[key] = relationship # 保存到数据库 await self.storage_relationship(relationship) relationship.saved = True return relationship - - async def update_relationship_value(self, user_id: int, **kwargs): + + async def update_relationship_value(self, + chat_stream:ChatStream, + **kwargs) -> Optional[Relationship]: + """更新关系值 + Args: + user_id: 用户ID（可选，如果提供user_info则不需要） + platform: 平台（可选，如果提供user_info则不需要） + user_info: 用户信息对象（可选） + **kwargs: 其他参数 + Returns: + Relationship: 关系对象 + """ + # 确定user_id和platform + user_info = chat_stream.user_info + if user_info is not None: + user_id = user_info.user_id + platform = user_info.platform or 'qq' + else: + platform = platform or 'qq' + + if user_id is None: + raise ValueError("必须提供user_id或user_info") + + # 使用(user_id, platform)作为键 + key = (user_id, platform) + # 检查是否在内存中已存在 - relationship = self.relationships.get(user_id) + relationship = self.relationships.get(key) if relationship: - for key, value in kwargs.items(): - if key == 'relationship_value': + for k, value in kwargs.items(): + if k == 'relationship_value': relationship.relationship_value += value await self.storage_relationship(relationship) relationship.saved = True return relationship else: - logger.warning(f"用户 {user_id} 不存在，无法更新") + # 如果不存在且提供了user_info，则创建新的关系 + if user_info is not None: + return await self.update_relationship(chat_stream=chat_stream, **kwargs) + logger.warning(f"[关系管理] 用户 {user_id}({platform}) 不存在，无法更新") return None - - def get_relationship(self, user_id: int) -> Optional[Relationship]: - """获取用户关系对象""" - if user_id in self.relationships: - return self.relationships[user_id] + + def get_relationship(self, + chat_stream:ChatStream) -> Optional[Relationship]: + """获取用户关系对象 + Args: + user_id: 用户ID（可选，如果提供user_info则不需要） + platform: 平台（可选，如果提供user_info则不需要） + user_info: 用户信息对象（可选） + Returns: + Relationship: 关系对象 + """ + # 确定user_id和platform + user_info = chat_stream.user_info + platform = chat_stream.user_info.platform or 'qq' + if user_info is not None: + user_id = user_info.user_id + platform = user_info.platform or 'qq' + else: + platform = platform or 'qq' + + if user_id is None: + raise ValueError("必须提供user_id或user_info") + + key = (user_id, platform) + if key in self.relationships: + return self.relationships[key] else: return 0 async def load_relationship(self, data: dict) -> Relationship: """从数据库加载或创建新的关系对象""" - rela = Relationship(user_id=data['user_id'], data=data) + # 确保data中有platform字段，如果没有则默认为'qq' + if 'platform' not in data: + data['platform'] = 'qq' + + rela = Relationship(data=data) rela.saved = True - self.relationships[rela.user_id] = rela + key = (rela.user_id, rela.platform) + self.relationships[key] = rela return rela async def load_all_relationships(self): @@ -117,11 +180,9 @@ class RelationshipManager: all_relationships = db.db.relationships.find({}) # 依次加载每条记录 for data in all_relationships: - user_id = data['user_id'] - relationship = await self.load_relationship(data) - self.relationships[user_id] = relationship - logger.debug(f"已加载 {len(self.relationships)} 条关系记录") - + await self.load_relationship(data) + logger.debug(f"[关系管理] 已加载 {len(self.relationships)} 条关系记录") + while True: logger.debug("正在自动保存关系") await asyncio.sleep(300) # 等待300秒(5分钟) @@ -130,16 +191,15 @@ class RelationshipManager: async def _save_all_relationships(self): """将所有关系数据保存到数据库""" # 保存所有关系数据 - for userid, relationship in self.relationships.items(): + for (userid, platform), relationship in self.relationships.items(): if not relationship.saved: relationship.saved = True await self.storage_relationship(relationship) - + async def storage_relationship(self, relationship: Relationship): - """ - 将关系记录存储到数据库中 - """ + """将关系记录存储到数据库中""" user_id = relationship.user_id + platform = relationship.platform nickname = relationship.nickname relationship_value = relationship.relationship_value gender = relationship.gender @@ -148,8 +208,9 @@ class RelationshipManager: db = Database.get_instance() db.db.relationships.update_one( - {'user_id': user_id}, + {'user_id': user_id, 'platform': platform}, {'$set': { + 'platform': platform, 'nickname': nickname, 'relationship_value': relationship_value, 'gender': gender, @@ -158,13 +219,37 @@ class RelationshipManager: }}, upsert=True ) - - def get_name(self, user_id: int) -> str: + + + def get_name(self, + user_id: int = None, + platform: str = None, + user_info: UserInfo = None) -> str: + """获取用户昵称 + Args: + user_id: 用户ID（可选，如果提供user_info则不需要） + platform: 平台（可选，如果提供user_info则不需要） + user_info: 用户信息对象（可选） + Returns: + str: 用户昵称 + """ + # 确定user_id和platform + if user_info is not None: + user_id = user_info.user_id + platform = user_info.platform or 'qq' + else: + platform = platform or 'qq' + + if user_id is None: + raise ValueError("必须提供user_id或user_info") + # 确保user_id是整数类型 user_id = int(user_id) - if user_id in self.relationships: - - return self.relationships[user_id].nickname + key = (user_id, platform) + if key in self.relationships: + return self.relationships[key].nickname + elif user_info is not None: + return user_info.user_nickname or user_info.user_cardname or "某人" else: return "某人" diff --git a/src/plugins/chat/storage.py b/src/plugins/chat/storage.py index 4081f8984..f403b2c8b 100644 --- a/src/plugins/chat/storage.py +++ b/src/plugins/chat/storage.py @@ -1,48 +1,30 @@ -from typing import Optional +from typing import Optional, Union +from typing import Optional, Union from ...common.database import Database -from .message import Message +from .message_base import MessageBase +from .message import MessageSending, MessageRecv +from .chat_stream import ChatStream from loguru import logger class MessageStorage: def __init__(self): self.db = Database.get_instance() - - async def store_message(self, message: Message, topic: Optional[str] = None) -> None: + + async def store_message(self, message: Union[MessageSending, MessageRecv],chat_stream:ChatStream, topic: Optional[str] = None) -> None: """存储消息到数据库""" try: - if not message.is_emoji: - message_data = { - "group_id": message.group_id, - "user_id": message.user_id, - "message_id": message.message_id, - "raw_message": message.raw_message, - "plain_text": message.plain_text, + message_data = { + "message_id": message.message_info.message_id, + "time": message.message_info.time, + "chat_id":chat_stream.stream_id, + "chat_info": chat_stream.to_dict(), + "user_info": message.message_info.user_info.to_dict(), "processed_plain_text": message.processed_plain_text, - "time": message.time, - "user_nickname": message.user_nickname, - "user_cardname": message.user_cardname, - "group_name": message.group_name, - "topic": topic, "detailed_plain_text": message.detailed_plain_text, - } - else: - message_data = { - "group_id": message.group_id, - "user_id": message.user_id, - "message_id": message.message_id, - "raw_message": message.raw_message, - "plain_text": message.plain_text, - "processed_plain_text": '[表情包]', - "time": message.time, - "user_nickname": message.user_nickname, - "user_cardname": message.user_cardname, - "group_name": message.group_name, "topic": topic, - "detailed_plain_text": message.detailed_plain_text, } - self.db.db.messages.insert_one(message_data) except Exception: logger.exception("存储消息失败") diff --git a/src/plugins/chat/utils.py b/src/plugins/chat/utils.py index 6619f37af..55fb9eb43 100644 --- a/src/plugins/chat/utils.py +++ b/src/plugins/chat/utils.py @@ -12,32 +12,15 @@ from loguru import logger from ..models.utils_model import LLM_request from ..utils.typo_generator import ChineseTypoGenerator from .config import global_config -from .message import Message +from .message import MessageThinking, MessageRecv,MessageSending,MessageProcessBase,Message +from .message_base import MessageBase,BaseMessageInfo,UserInfo,GroupInfo +from .chat_stream import ChatStream from ..moods.moods import MoodManager driver = get_driver() config = driver.config -def combine_messages(messages: List[Message]) -> str: - """将消息列表组合成格式化的字符串 - - Args: - messages: Message对象列表 - - Returns: - str: 格式化后的消息字符串 - """ - result = "" - for message in messages: - time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(message.time)) - name = message.user_nickname or f"用户{message.user_id}" - content = message.processed_plain_text or message.plain_text - - result += f"[{time_str}] {name}: {content}\n" - - return result - def db_message_to_str(message_dict: Dict) -> str: logger.debug(f"message_dict: {message_dict}") @@ -53,14 +36,11 @@ def db_message_to_str(message_dict: Dict) -> str: return result -def is_mentioned_bot_in_txt(message: str) -> bool: +def is_mentioned_bot_in_message(message: MessageRecv) -> bool: """检查消息是否提到了机器人""" - if global_config.BOT_NICKNAME is None: - return True - if global_config.BOT_NICKNAME in message: - return True - for keyword in global_config.BOT_ALIAS_NAMES: - if keyword in message: + keywords = [global_config.BOT_NICKNAME] + for keyword in keywords: + if keyword in message.processed_plain_text: return True return False @@ -93,46 +73,45 @@ def calculate_information_content(text): def get_cloest_chat_from_db(db, length: int, timestamp: str): - """从数据库中获取最接近指定时间戳的聊天记录，并记录读取次数 + """从数据库中获取最接近指定时间戳的聊天记录 + Args: + db: 数据库实例 + length: 要获取的消息数量 + timestamp: 时间戳 + Returns: - list: 消息记录字典列表，每个字典包含消息内容和时间信息 + list: 消息记录列表，每个记录包含时间和文本信息 """ chat_records = [] closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)]) - if closest_record and closest_record.get('memorized', 0) < 4: + if closest_record: closest_time = closest_record['time'] - group_id = closest_record['group_id'] - # 获取该时间戳之后的length条消息，且groupid相同 - records = list(db.db.messages.find( - {"time": {"$gt": closest_time}, "group_id": group_id} + chat_id = closest_record['chat_id'] # 获取chat_id + # 获取该时间戳之后的length条消息，保持相同的chat_id + chat_records = list(db.db.messages.find( + { + "time": {"$gt": closest_time}, + "chat_id": chat_id # 添加chat_id过滤 + } ).sort('time', 1).limit(length)) - # 更新每条消息的memorized属性 - for record in records: - current_memorized = record.get('memorized', 0) - if current_memorized > 3: - print("消息已读取3次，跳过") - return '' - - # 更新memorized值 - db.db.messages.update_one( - {"_id": record["_id"]}, - {"$set": {"memorized": current_memorized + 1}} - ) - - # 添加到记录列表中 - chat_records.append({ - 'text': record["detailed_plain_text"], + # 转换记录格式 + formatted_records = [] + for record in chat_records: + formatted_records.append({ 'time': record["time"], - 'group_id': record["group_id"] + 'chat_id': record["chat_id"], + 'detailed_plain_text': record.get("detailed_plain_text", "") # 添加文本内容 }) - return chat_records + return formatted_records + + return [] -async def get_recent_group_messages(db, group_id: int, limit: int = 12) -> list: +async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list: """从数据库获取群组最近的消息记录 Args: @@ -146,35 +125,28 @@ async def get_recent_group_messages(db, group_id: int, limit: int = 12) -> list: # 从数据库获取最近消息 recent_messages = list(db.db.messages.find( - {"group_id": group_id}, - # { - # "time": 1, - # "user_id": 1, - # "user_nickname": 1, - # "message_id": 1, - # "raw_message": 1, - # "processed_text": 1 - # } + {"chat_id": chat_id}, ).sort("time", -1).limit(limit)) if not recent_messages: return [] # 转换为 Message对象列表 - from .message import Message message_objects = [] for msg_data in recent_messages: try: + chat_info=msg_data.get("chat_info",{}) + chat_stream=ChatStream.from_dict(chat_info) + user_info=msg_data.get("user_info",{}) + user_info=UserInfo.from_dict(user_info) msg = Message( - time=msg_data["time"], - user_id=msg_data["user_id"], - user_nickname=msg_data.get("user_nickname", ""), message_id=msg_data["message_id"], - raw_message=msg_data["raw_message"], + chat_stream=chat_stream, + time=msg_data["time"], + user_info=user_info, processed_plain_text=msg_data.get("processed_text", ""), - group_id=group_id + detailed_plain_text=msg_data.get("detailed_plain_text", "") ) - await msg.initialize() message_objects.append(msg) except KeyError: logger.warning("数据库中存在无效的消息") @@ -185,13 +157,14 @@ async def get_recent_group_messages(db, group_id: int, limit: int = 12) -> list: return message_objects -def get_recent_group_detailed_plain_text(db, group_id: int, limit: int = 12, combine=False): +def get_recent_group_detailed_plain_text(db, chat_stream_id: int, limit: int = 12, combine=False): recent_messages = list(db.db.messages.find( - {"group_id": group_id}, + {"chat_id": chat_stream_id}, { "time": 1, # 返回时间字段 - "user_id": 1, # 返回用户ID字段 - "user_nickname": 1, # 返回用户昵称字段 + "chat_id":1, + "chat_info":1, + "user_info": 1, "message_id": 1, # 返回消息ID字段 "detailed_plain_text": 1 # 返回处理后的文本字段 } diff --git a/src/plugins/chat/utils_image.py b/src/plugins/chat/utils_image.py index 7e57560c9..dc14d4bca 100644 --- a/src/plugins/chat/utils_image.py +++ b/src/plugins/chat/utils_image.py @@ -2,7 +2,11 @@ import base64 import io import os import time -import zlib # 用于 CRC32 +import zlib +import aiohttp +import hashlib +from typing import Optional, Tuple, Union +from urllib.parse import urlparse from loguru import logger from nonebot import get_driver @@ -10,280 +14,353 @@ from PIL import Image from ...common.database import Database from ..chat.config import global_config - +from ..models.utils_model import LLM_request driver = get_driver() config = driver.config - - -def storage_compress_image(base64_data: str, max_size: int = 200) -> str: - """ - 压缩base64格式的图片到指定大小（单位：KB）并在数据库中记录图片信息 - Args: - base64_data: base64编码的图片数据 - max_size: 最大文件大小（KB） - Returns: - str: 压缩后的base64图片数据 - """ - try: - # 将base64转换为字节数据 - image_data = base64.b64decode(base64_data) - - # 使用 CRC32 计算哈希值 - hash_value = format(zlib.crc32(image_data) & 0xFFFFFFFF, 'x') - - # 确保图片目录存在 - images_dir = "data/images" - os.makedirs(images_dir, exist_ok=True) - - # 连接数据库 - db = Database.get_instance() - - # 检查是否已存在相同哈希值的图片 - collection = db.db['images'] - existing_image = collection.find_one({'hash': hash_value}) - - if existing_image: - print(f"\033[1;33m[提示]\033[0m 发现重复图片，使用已存在的文件: {existing_image['path']}") - return base64_data - - # 将字节数据转换为图片对象 - img = Image.open(io.BytesIO(image_data)) - - # 如果是动图，直接返回原图 - if getattr(img, 'is_animated', False): - return base64_data - - # 计算当前大小（KB） - current_size = len(image_data) / 1024 - - # 如果已经小于目标大小，直接使用原图 - if current_size <= max_size: - compressed_data = image_data - else: - # 压缩逻辑 - # 先缩放到50% - new_width = int(img.width * 0.5) - new_height = int(img.height * 0.5) - img = img.resize((new_width, new_height), Image.Resampling.LANCZOS) - - # 如果缩放后的最大边长仍然大于400，继续缩放 - max_dimension = 400 - max_current = max(new_width, new_height) - if max_current > max_dimension: - ratio = max_dimension / max_current - new_width = int(new_width * ratio) - new_height = int(new_height * ratio) - img = img.resize((new_width, new_height), Image.Resampling.LANCZOS) - - # 转换为RGB模式（去除透明通道） - if img.mode in ('RGBA', 'P'): - img = img.convert('RGB') - - # 使用固定质量参数压缩 - output = io.BytesIO() - img.save(output, format='JPEG', quality=85, optimize=True) - compressed_data = output.getvalue() - - # 生成文件名（使用时间戳和哈希值确保唯一性） - timestamp = int(time.time()) - filename = f"{timestamp}_{hash_value}.jpg" - image_path = os.path.join(images_dir, filename) - - # 保存文件 - with open(image_path, "wb") as f: - f.write(compressed_data) - - print(f"\033[1;32m[成功]\033[0m 保存图片到: {image_path}") - - try: - # 准备数据库记录 - image_record = { - 'filename': filename, - 'path': image_path, - 'size': len(compressed_data) / 1024, - 'timestamp': timestamp, - 'width': img.width, - 'height': img.height, - 'description': '', - 'tags': [], - 'type': 'image', - 'hash': hash_value - } - - # 保存记录 - collection.insert_one(image_record) - print("\033[1;32m[成功]\033[0m 保存图片记录到数据库") - - except Exception as db_error: - print(f"\033[1;31m[错误]\033[0m 数据库操作失败: {str(db_error)}") - - # 将压缩后的数据转换为base64 - compressed_base64 = base64.b64encode(compressed_data).decode('utf-8') - return compressed_base64 - - except Exception as e: - print(f"\033[1;31m[错误]\033[0m 压缩图片失败: {str(e)}") - import traceback - print(traceback.format_exc()) - return base64_data - -def storage_emoji(image_data: bytes) -> bytes: - """ - 存储表情包到本地文件夹 - Args: - image_data: 图片字节数据 - group_id: 群组ID（仅用于日志） - user_id: 用户ID（仅用于日志） - Returns: - bytes: 原始图片数据 - """ - if not global_config.EMOJI_SAVE: - return image_data - try: - # 使用 CRC32 计算哈希值 - hash_value = format(zlib.crc32(image_data) & 0xFFFFFFFF, 'x') - - # 确保表情包目录存在 - emoji_dir = "data/emoji" - os.makedirs(emoji_dir, exist_ok=True) - - # 检查是否已存在相同哈希值的文件 - for filename in os.listdir(emoji_dir): - if hash_value in filename: - # print(f"\033[1;33m[提示]\033[0m 发现重复表情包: {filename}") - return image_data - - # 生成文件名 - timestamp = int(time.time()) - filename = f"{timestamp}_{hash_value}.jpg" - emoji_path = os.path.join(emoji_dir, filename) - - # 直接保存原始文件 - with open(emoji_path, "wb") as f: - f.write(image_data) - - print(f"\033[1;32m[成功]\033[0m 保存表情包到: {emoji_path}") - return image_data - - except Exception as e: - print(f"\033[1;31m[错误]\033[0m 保存表情包失败: {str(e)}") - return image_data +class ImageManager: + _instance = None + IMAGE_DIR = "data" # 图像存储根目录 + def __new__(cls): + if cls._instance is None: + cls._instance = super().__new__(cls) + cls._instance.db = None + cls._instance._initialized = False + return cls._instance + + def __init__(self): + if not self._initialized: + self.db = Database.get_instance() + self._ensure_image_collection() + self._ensure_description_collection() + self._ensure_image_dir() + self._initialized = True + self._llm = LLM_request(model=global_config.vlm, temperature=0.4, max_tokens=300) + + def _ensure_image_dir(self): + """确保图像存储目录存在""" + os.makedirs(self.IMAGE_DIR, exist_ok=True) + + def _ensure_image_collection(self): + """确保images集合存在并创建索引""" + if 'images' not in self.db.db.list_collection_names(): + self.db.db.create_collection('images') + # 创建索引 + self.db.db.images.create_index([('hash', 1)], unique=True) + self.db.db.images.create_index([('url', 1)]) + self.db.db.images.create_index([('path', 1)]) -def storage_image(image_data: bytes) -> bytes: - """ - 存储图片到本地文件夹 - Args: - image_data: 图片字节数据 - group_id: 群组ID（仅用于日志） - user_id: 用户ID（仅用于日志） - Returns: - bytes: 原始图片数据 - """ - try: - # 使用 CRC32 计算哈希值 - hash_value = format(zlib.crc32(image_data) & 0xFFFFFFFF, 'x') - - # 确保表情包目录存在 - image_dir = "data/image" - os.makedirs(image_dir, exist_ok=True) - - # 检查是否已存在相同哈希值的文件 - for filename in os.listdir(image_dir): - if hash_value in filename: - # print(f"\033[1;33m[提示]\033[0m 发现重复表情包: {filename}") - return image_data - - # 生成文件名 - timestamp = int(time.time()) - filename = f"{timestamp}_{hash_value}.jpg" - image_path = os.path.join(image_dir, filename) - - # 直接保存原始文件 - with open(image_path, "wb") as f: - f.write(image_data) - - print(f"\033[1;32m[成功]\033[0m 保存图片到: {image_path}") - return image_data - - except Exception as e: - print(f"\033[1;31m[错误]\033[0m 保存图片失败: {str(e)}") - return image_data + def _ensure_description_collection(self): + """确保image_descriptions集合存在并创建索引""" + if 'image_descriptions' not in self.db.db.list_collection_names(): + self.db.db.create_collection('image_descriptions') + # 创建索引 + self.db.db.image_descriptions.create_index([('hash', 1)], unique=True) + self.db.db.image_descriptions.create_index([('type', 1)]) -def compress_base64_image_by_scale(base64_data: str, target_size: int = 0.8 * 1024 * 1024) -> str: - """压缩base64格式的图片到指定大小 - Args: - base64_data: base64编码的图片数据 - target_size: 目标文件大小（字节），默认0.8MB - Returns: - str: 压缩后的base64图片数据 - """ - try: - # 将base64转换为字节数据 - image_data = base64.b64decode(base64_data) + def _get_description_from_db(self, image_hash: str, description_type: str) -> Optional[str]: + """从数据库获取图片描述 - # 如果已经小于目标大小，直接返回原图 - if len(image_data) <= 2*1024*1024: - return base64_data + Args: + image_hash: 图片哈希值 + description_type: 描述类型 ('emoji' 或 'image') - # 将字节数据转换为图片对象 - img = Image.open(io.BytesIO(image_data)) + Returns: + Optional[str]: 描述文本，如果不存在则返回None + """ + result= self.db.db.image_descriptions.find_one({ + 'hash': image_hash, + 'type': description_type + }) + return result['description'] if result else None + + def _save_description_to_db(self, image_hash: str, description: str, description_type: str) -> None: + """保存图片描述到数据库 - # 获取原始尺寸 - original_width, original_height = img.size - - # 计算缩放比例 - scale = min(1.0, (target_size / len(image_data)) ** 0.5) - - # 计算新的尺寸 - new_width = int(original_width * scale) - new_height = int(original_height * scale) - - # 创建内存缓冲区 - output_buffer = io.BytesIO() - - # 如果是GIF，处理所有帧 - if getattr(img, "is_animated", False): - frames = [] - for frame_idx in range(img.n_frames): - img.seek(frame_idx) - new_frame = img.copy() - new_frame = new_frame.resize((new_width//2, new_height//2), Image.Resampling.LANCZOS) # 动图折上折 - frames.append(new_frame) - - # 保存到缓冲区 - frames[0].save( - output_buffer, - format='GIF', - save_all=True, - append_images=frames[1:], - optimize=True, - duration=img.info.get('duration', 100), - loop=img.info.get('loop', 0) - ) - else: - # 处理静态图片 - resized_img = img.resize((new_width, new_height), Image.Resampling.LANCZOS) - - # 保存到缓冲区，保持原始格式 - if img.format == 'PNG' and img.mode in ('RGBA', 'LA'): - resized_img.save(output_buffer, format='PNG', optimize=True) + Args: + image_hash: 图片哈希值 + description: 描述文本 + description_type: 描述类型 ('emoji' 或 'image') + """ + self.db.db.image_descriptions.update_one( + {'hash': image_hash, 'type': description_type}, + { + '$set': { + 'description': description, + 'timestamp': int(time.time()) + } + }, + upsert=True + ) + + async def save_image(self, + image_data: Union[str, bytes], + url: str = None, + description: str = None, + is_base64: bool = False) -> Optional[str]: + """保存图像 + Args: + image_data: 图像数据(base64字符串或字节) + url: 图像URL + description: 图像描述 + is_base64: image_data是否为base64格式 + Returns: + str: 保存后的文件路径,失败返回None + """ + try: + # 转换为字节格式 + if is_base64: + if isinstance(image_data, str): + image_bytes = base64.b64decode(image_data) + else: + return None else: - resized_img.save(output_buffer, format='JPEG', quality=95, optimize=True) + if isinstance(image_data, bytes): + image_bytes = image_data + else: + return None + + # 计算哈希值 + image_hash = hashlib.md5(image_bytes).hexdigest() + + # 查重 + existing = self.db.db.images.find_one({'hash': image_hash}) + if existing: + return existing['path'] + + # 生成文件名和路径 + timestamp = int(time.time()) + filename = f"{timestamp}_{image_hash[:8]}.jpg" + file_path = os.path.join(self.IMAGE_DIR, filename) + + # 保存文件 + with open(file_path, "wb") as f: + f.write(image_bytes) + + # 保存到数据库 + image_doc = { + 'hash': image_hash, + 'path': file_path, + 'url': url, + 'description': description, + 'timestamp': timestamp + } + self.db.db.images.insert_one(image_doc) + + return file_path + + except Exception as e: + logger.error(f"保存图像失败: {str(e)}") + return None + + async def get_image_by_url(self, url: str) -> Optional[str]: + """根据URL获取图像路径(带查重) + Args: + url: 图像URL + Returns: + str: 本地文件路径,不存在返回None + """ + try: + # 先查找是否已存在 + existing = self.db.db.images.find_one({'url': url}) + if existing: + return existing['path'] + + # 下载图像 + async with aiohttp.ClientSession() as session: + async with session.get(url) as resp: + if resp.status == 200: + image_bytes = await resp.read() + return await self.save_image(image_bytes, url=url) + return None + + except Exception as e: + logger.error(f"获取图像失败: {str(e)}") + return None + + async def get_base64_by_url(self, url: str) -> Optional[str]: + """根据URL获取base64(带查重) + Args: + url: 图像URL + Returns: + str: base64字符串,失败返回None + """ + try: + image_path = await self.get_image_by_url(url) + if not image_path: + return None + + with open(image_path, 'rb') as f: + image_bytes = f.read() + return base64.b64encode(image_bytes).decode('utf-8') + + except Exception as e: + logger.error(f"获取base64失败: {str(e)}") + return None + + async def save_base64_image(self, base64_str: str, description: str = None) -> Optional[str]: + """保存base64图像(带查重) + Args: + base64_str: base64字符串 + description: 图像描述 + Returns: + str: 保存路径,失败返回None + """ + return await self.save_image(base64_str, description=description, is_base64=True) - # 获取压缩后的数据并转换为base64 - compressed_data = output_buffer.getvalue() - logger.success(f"压缩图片: {original_width}x{original_height} -> {new_width}x{new_height}") - logger.info(f"压缩前大小: {len(image_data)/1024:.1f}KB, 压缩后大小: {len(compressed_data)/1024:.1f}KB") + def check_url_exists(self, url: str) -> bool: + """检查URL是否已存在 + Args: + url: 图像URL + Returns: + bool: 是否存在 + """ + return self.db.db.images.find_one({'url': url}) is not None - return base64.b64encode(compressed_data).decode('utf-8') + def check_hash_exists(self, image_data: Union[str, bytes], is_base64: bool = False) -> bool: + """检查图像是否已存在 + Args: + image_data: 图像数据(base64或字节) + is_base64: 是否为base64格式 + Returns: + bool: 是否存在 + """ + try: + if is_base64: + if isinstance(image_data, str): + image_bytes = base64.b64decode(image_data) + else: + return False + else: + if isinstance(image_data, bytes): + image_bytes = image_data + else: + return False + + image_hash = hashlib.md5(image_bytes).hexdigest() + return self.db.db.images.find_one({'hash': image_hash}) is not None + + except Exception as e: + logger.error(f"检查哈希失败: {str(e)}") + return False - except Exception as e: - logger.error(f"压缩图片失败: {str(e)}") - import traceback - logger.error(traceback.format_exc()) - return base64_data + async def get_emoji_description(self, image_base64: str) -> str: + """获取表情包描述，带查重和保存功能""" + try: + # 计算图片哈希 + image_bytes = base64.b64decode(image_base64) + image_hash = hashlib.md5(image_bytes).hexdigest() + + # 查询缓存的描述 + cached_description = self._get_description_from_db(image_hash, 'emoji') + if cached_description: + logger.info(f"缓存表情包描述: {cached_description}") + return f"[表情包：{cached_description}]" + + # 调用AI获取描述 + prompt = "这是一个表情包，使用中文简洁的描述一下表情包的内容和表情包所表达的情感" + description, _ = await self._llm.generate_response_for_image(prompt, image_base64) + + # 根据配置决定是否保存图片 + if global_config.EMOJI_SAVE: + # 生成文件名和路径 + timestamp = int(time.time()) + filename = f"emoji_{timestamp}_{image_hash[:8]}.jpg" + file_path = os.path.join(self.IMAGE_DIR, filename) + + try: + # 保存文件 + with open(file_path, "wb") as f: + f.write(image_bytes) + + # 保存到数据库 + image_doc = { + 'hash': image_hash, + 'path': file_path, + 'type': 'emoji', + 'description': description, + 'timestamp': timestamp + } + self.db.db.images.update_one( + {'hash': image_hash}, + {'$set': image_doc}, + upsert=True + ) + logger.success(f"保存表情包: {file_path}") + except Exception as e: + logger.error(f"保存表情包文件失败: {str(e)}") + + # 保存描述到数据库 + self._save_description_to_db(image_hash, description, 'emoji') + + return f"[表情包：{description}]" + except Exception as e: + logger.error(f"获取表情包描述失败: {str(e)}") + return "[表情包]" + + async def get_image_description(self, image_base64: str) -> str: + """获取普通图片描述，带查重和保存功能""" + try: + # 计算图片哈希 + image_bytes = base64.b64decode(image_base64) + image_hash = hashlib.md5(image_bytes).hexdigest() + + # 查询缓存的描述 + cached_description = self._get_description_from_db(image_hash, 'image') + if cached_description: + return f"[图片：{cached_description}]" + + # 调用AI获取描述 + prompt = "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。" + description, _ = await self._llm.generate_response_for_image(prompt, image_base64) + + if description is None: + logger.warning("AI未能生成图片描述") + return "[图片]" + + # 根据配置决定是否保存图片 + if global_config.EMOJI_SAVE: + # 生成文件名和路径 + timestamp = int(time.time()) + filename = f"image_{timestamp}_{image_hash[:8]}.jpg" + file_path = os.path.join(self.IMAGE_DIR, filename) + + try: + # 保存文件 + with open(file_path, "wb") as f: + f.write(image_bytes) + + # 保存到数据库 + image_doc = { + 'hash': image_hash, + 'path': file_path, + 'type': 'image', + 'description': description, + 'timestamp': timestamp + } + self.db.db.images.update_one( + {'hash': image_hash}, + {'$set': image_doc}, + upsert=True + ) + logger.success(f"保存图片: {file_path}") + except Exception as e: + logger.error(f"保存图片文件失败: {str(e)}") + + # 保存描述到数据库 + self._save_description_to_db(image_hash, description, 'image') + + return f"[图片：{description}]" + except Exception as e: + logger.error(f"获取图片描述失败: {str(e)}") + return "[图片]" + + + +# 创建全局单例 +image_manager = ImageManager() + def image_path_to_base64(image_path: str) -> str: """将图片路径转换为base64编码 diff --git a/src/plugins/chat/willing_manager.py b/src/plugins/chat/willing_manager.py index 116ee3f87..39083f0b8 100644 --- a/src/plugins/chat/willing_manager.py +++ b/src/plugins/chat/willing_manager.py @@ -1,107 +1,109 @@ import asyncio +from typing import Dict from loguru import logger + +from typing import Dict +from loguru import logger + from .config import global_config +from .message_base import UserInfo, GroupInfo +from .chat_stream import chat_manager,ChatStream class WillingManager: def __init__(self): - self.group_reply_willing = {} # 存储每个群的回复意愿 + self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿 + self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿 self._decay_task = None self._started = False - self.min_reply_willing = 0.01 - self.attenuation_coefficient = 0.75 - + async def _decay_reply_willing(self): """定期衰减回复意愿""" while True: await asyncio.sleep(5) - for group_id in self.group_reply_willing: - self.group_reply_willing[group_id] = max( - self.min_reply_willing, - self.group_reply_willing[group_id] * self.attenuation_coefficient - ) - - def get_willing(self, group_id: int) -> float: - """获取指定群组的回复意愿""" - return self.group_reply_willing.get(group_id, 0) - - def set_willing(self, group_id: int, willing: float): - """设置指定群组的回复意愿""" - self.group_reply_willing[group_id] = willing - - def change_reply_willing_received(self, group_id: int, topic: str, is_mentioned_bot: bool, config, - user_id: int = None, is_emoji: bool = False, interested_rate: float = 0) -> float: - - # 若非目标回复群组，则直接return - if group_id not in config.talk_allowed_groups: - reply_probability = 0 - return reply_probability - - current_willing = self.group_reply_willing.get(group_id, 0) - - logger.debug(f"[{group_id}]的初始回复意愿: {current_willing}") - - # 根据消息类型（被cue/表情包）调控 - if is_mentioned_bot: - current_willing = min( - 3.0, - current_willing + 0.9 - ) - logger.debug(f"被提及, 当前意愿: {current_willing}") - + for chat_id in self.chat_reply_willing: + self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.6) + for chat_id in self.chat_reply_willing: + self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.6) + + def get_willing(self,chat_stream:ChatStream) -> float: + """获取指定聊天流的回复意愿""" + stream = chat_stream + if stream: + return self.chat_reply_willing.get(stream.stream_id, 0) + return 0 + + def set_willing(self, chat_id: str, willing: float): + """设置指定聊天流的回复意愿""" + self.chat_reply_willing[chat_id] = willing + def set_willing(self, chat_id: str, willing: float): + """设置指定聊天流的回复意愿""" + self.chat_reply_willing[chat_id] = willing + + async def change_reply_willing_received(self, + chat_stream:ChatStream, + topic: str = None, + is_mentioned_bot: bool = False, + config = None, + is_emoji: bool = False, + interested_rate: float = 0) -> float: + """改变指定聊天流的回复意愿并返回回复概率""" + # 获取或创建聊天流 + stream = chat_stream + chat_id = stream.stream_id + + current_willing = self.chat_reply_willing.get(chat_id, 0) + + # print(f"初始意愿: {current_willing}") + if is_mentioned_bot and current_willing < 1.0: + current_willing += 0.9 + print(f"被提及, 当前意愿: {current_willing}") + elif is_mentioned_bot: + current_willing += 0.05 + print(f"被重复提及, 当前意愿: {current_willing}") + if is_emoji: current_willing *= 0.1 - logger.debug(f"表情包, 当前意愿: {current_willing}") - - # 兴趣放大系数，若兴趣 > 0.4则增加回复概率 - interested_rate_amplifier = global_config.response_interested_rate_amplifier - logger.debug(f"放大系数_interested_rate: {interested_rate_amplifier}") - interested_rate *= interested_rate_amplifier - - current_willing += max( - 0.0, - interested_rate - 0.4 - ) - - # 回复意愿系数调控，独立乘区 - willing_amplifier = max( - global_config.response_willing_amplifier, - self.min_reply_willing - ) - current_willing *= willing_amplifier - logger.debug(f"放大系数_willing: {global_config.response_willing_amplifier}, 当前意愿: {current_willing}") - - # 回复概率迭代，保底0.01回复概率 - reply_probability = max( - (current_willing - 0.45) * 2, - self.min_reply_willing - ) - - # 降低目标低频群组回复概率 - down_frequency_rate = max( - 1.0, - global_config.down_frequency_rate - ) - if group_id in config.talk_frequency_down_groups: - reply_probability = reply_probability / down_frequency_rate + print(f"表情包, 当前意愿: {current_willing}") + + print(f"放大系数_interested_rate: {global_config.response_interested_rate_amplifier}") + interested_rate *= global_config.response_interested_rate_amplifier #放大回复兴趣度 + if interested_rate > 0.4: + # print(f"兴趣度: {interested_rate}, 当前意愿: {current_willing}") + current_willing += interested_rate-0.4 + + current_willing *= global_config.response_willing_amplifier #放大回复意愿 + # print(f"放大系数_willing: {global_config.response_willing_amplifier}, 当前意愿: {current_willing}") + + reply_probability = max((current_willing - 0.45) * 2, 0) + + # 检查群组权限（如果是群聊） + if chat_stream.group_info: + if chat_stream.group_info.group_id in config.talk_frequency_down_groups: + reply_probability = reply_probability / global_config.down_frequency_rate reply_probability = min(reply_probability, 1) - - self.group_reply_willing[group_id] = min(current_willing, 3.0) - logger.debug(f"当前群组{group_id}回复概率：{reply_probability}") + if reply_probability < 0: + reply_probability = 0 + + self.chat_reply_willing[chat_id] = min(current_willing, 3.0) return reply_probability - - def change_reply_willing_sent(self, group_id: int): - """开始思考后降低群组的回复意愿""" - current_willing = self.group_reply_willing.get(group_id, 0) - self.group_reply_willing[group_id] = max(0, current_willing - 2) - - def change_reply_willing_after_sent(self, group_id: int): - """发送消息后提高群组的回复意愿""" - current_willing = self.group_reply_willing.get(group_id, 0) - if current_willing < 1: - self.group_reply_willing[group_id] = min(1, current_willing + 0.2) - + + def change_reply_willing_sent(self, chat_stream:ChatStream): + """开始思考后降低聊天流的回复意愿""" + stream = chat_stream + if stream: + current_willing = self.chat_reply_willing.get(stream.stream_id, 0) + self.chat_reply_willing[stream.stream_id] = max(0, current_willing - 2) + + def change_reply_willing_after_sent(self,chat_stream:ChatStream): + """发送消息后提高聊天流的回复意愿""" + stream = chat_stream + if stream: + current_willing = self.chat_reply_willing.get(stream.stream_id, 0) + if current_willing < 1: + self.chat_reply_willing[stream.stream_id] = min(1, current_willing + 0.2) + async def ensure_started(self): """确保衰减任务已启动""" if not self._started: @@ -109,6 +111,5 @@ class WillingManager: self._decay_task = asyncio.create_task(self._decay_reply_willing()) self._started = True - # 创建全局实例 -willing_manager = WillingManager() +willing_manager = WillingManager() \ No newline at end of file diff --git a/src/plugins/memory_system/memory.py b/src/plugins/memory_system/memory.py index 2884b6dae..c0b551b58 100644 --- a/src/plugins/memory_system/memory.py +++ b/src/plugins/memory_system/memory.py @@ -239,7 +239,7 @@ class Hippocampus: time_info += f"是从 {earliest_str} 到 {latest_str} 的对话:\n" for msg in messages: - input_text += f"{msg['text']}\n" + input_text += f"{msg['detailed_plain_text']}\n" logger.debug(input_text) diff --git a/src/plugins/models/utils_model.py b/src/plugins/models/utils_model.py index ac567600a..c6ed6b619 100644 --- a/src/plugins/models/utils_model.py +++ b/src/plugins/models/utils_model.py @@ -7,10 +7,11 @@ from typing import Tuple, Union import aiohttp from loguru import logger from nonebot import get_driver - +import base64 +from PIL import Image +import io from ...common.database import Database from ..chat.config import global_config -from ..chat.utils_image import compress_base64_image_by_scale driver = get_driver() config = driver.config @@ -432,3 +433,78 @@ class LLM_request: response_handler=embedding_handler ) return embedding + +def compress_base64_image_by_scale(base64_data: str, target_size: int = 0.8 * 1024 * 1024) -> str: + """压缩base64格式的图片到指定大小 + Args: + base64_data: base64编码的图片数据 + target_size: 目标文件大小（字节），默认0.8MB + Returns: + str: 压缩后的base64图片数据 + """ + try: + # 将base64转换为字节数据 + image_data = base64.b64decode(base64_data) + + # 如果已经小于目标大小，直接返回原图 + if len(image_data) <= 2*1024*1024: + return base64_data + + # 将字节数据转换为图片对象 + img = Image.open(io.BytesIO(image_data)) + + # 获取原始尺寸 + original_width, original_height = img.size + + # 计算缩放比例 + scale = min(1.0, (target_size / len(image_data)) ** 0.5) + + # 计算新的尺寸 + new_width = int(original_width * scale) + new_height = int(original_height * scale) + + # 创建内存缓冲区 + output_buffer = io.BytesIO() + + # 如果是GIF，处理所有帧 + if getattr(img, "is_animated", False): + frames = [] + for frame_idx in range(img.n_frames): + img.seek(frame_idx) + new_frame = img.copy() + new_frame = new_frame.resize((new_width//2, new_height//2), Image.Resampling.LANCZOS) # 动图折上折 + frames.append(new_frame) + + # 保存到缓冲区 + frames[0].save( + output_buffer, + format='GIF', + save_all=True, + append_images=frames[1:], + optimize=True, + duration=img.info.get('duration', 100), + loop=img.info.get('loop', 0) + ) + else: + # 处理静态图片 + resized_img = img.resize((new_width, new_height), Image.Resampling.LANCZOS) + + # 保存到缓冲区，保持原始格式 + if img.format == 'PNG' and img.mode in ('RGBA', 'LA'): + resized_img.save(output_buffer, format='PNG', optimize=True) + else: + resized_img.save(output_buffer, format='JPEG', quality=95, optimize=True) + + # 获取压缩后的数据并转换为base64 + compressed_data = output_buffer.getvalue() + logger.success(f"压缩图片: {original_width}x{original_height} -> {new_width}x{new_height}") + logger.info(f"压缩前大小: {len(image_data)/1024:.1f}KB, 压缩后大小: {len(compressed_data)/1024:.1f}KB") + + return base64.b64encode(compressed_data).decode('utf-8') + + except Exception as e: + logger.error(f"压缩图片失败: {str(e)}") + import traceback + logger.error(traceback.format_exc()) + return base64_data +