from typing import List, Dict, Optional import random from ...common.database import Database import os import json from dataclasses import dataclass import jieba.analyse as jieba_analyse import aiohttp import hashlib from datetime import datetime import base64 import shutil import asyncio import time from nonebot import get_driver from ..chat.config import global_config from ..models.utils_model import LLM_request driver = get_driver() config = driver.config class EmojiManager: _instance = None EMOJI_DIR = "data/emoji" # 表情包存储目录 EMOTION_KEYWORDS = { 'happy': ['开心', '快乐', '高兴', '欢喜', '笑', '喜悦', '兴奋', '愉快', '乐', '好'], 'angry': ['生气', '愤怒', '恼火', '不爽', '火大', '怒', '气愤', '恼怒', '发火', '不满'], 'sad': ['伤心', '难过', '悲伤', '痛苦', '哭', '忧伤', '悲痛', '哀伤', '委屈', '失落'], 'surprised': ['惊讶', '震惊', '吃惊', '意外', '惊', '诧异', '惊奇', '惊喜', '不敢相信', '目瞪口呆'], 'disgusted': ['恶心', '讨厌', '厌恶', '反感', '嫌弃', '恶', '嫌恶', '憎恶', '不喜欢', '烦'], 'fearful': ['害怕', '恐惧', '惊恐', '担心', '怕', '惊吓', '惊慌', '畏惧', '胆怯', '惧'], 'neutral': ['普通', '一般', '还行', '正常', '平静', '平淡', '一般般', '凑合', '还好', '就这样'] } 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): self.db = Database.get_instance() self._scan_task = None self.llm = LLM_request(model=global_config.vlm, temperature=0.3, max_tokens=50) def _ensure_emoji_dir(self): """确保表情存储目录存在""" os.makedirs(self.EMOJI_DIR, exist_ok=True) def initialize(self): """初始化数据库连接和表情目录""" if not self._initialized: try: self.db = Database.get_instance() self._ensure_emoji_collection() self._ensure_emoji_dir() self._initialized = True # 启动时执行一次完整性检查 self.check_emoji_file_integrity() except Exception as e: print(f"\033[1;31m[错误]\033[0m 初始化表情管理器失败: {str(e)}") def _ensure_db(self): """确保数据库已初始化""" if not self._initialized: self.initialize() if not self._initialized: raise RuntimeError("EmojiManager not initialized") def _ensure_emoji_collection(self): """确保emoji集合存在并创建索引""" if 'emoji' not in self.db.db.list_collection_names(): self.db.db.create_collection('emoji') 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): """记录表情使用次数""" try: self._ensure_db() self.db.db.emoji.update_one( {'_id': emoji_id}, {'$inc': {'usage_count': 1}} ) except Exception as e: print(f"\033[1;31m[错误]\033[0m 记录表情使用失败: {str(e)}") async def _get_emotion_from_text(self, text: str) -> List[str]: """从文本中识别情感关键词 Args: text: 输入文本 Returns: List[str]: 匹配到的情感标签列表 """ try: prompt = f'分析这段文本："{text}"，从"happy,angry,sad,surprised,disgusted,fearful,neutral"中选出最匹配的1个情感标签。只需要返回标签，不要输出其他任何内容。' content, _ = await self.llm.generate_response(prompt) emotion = content.strip().lower() if emotion in self.EMOTION_KEYWORDS: print(f"\033[1;32m[成功]\033[0m 识别到的情感: {emotion}") return [emotion] return ['neutral'] except Exception as e: print(f"\033[1;31m[错误]\033[0m 情感分析失败: {str(e)}") return ['neutral'] async def get_emoji_for_emotion(self, emotion_tag: str) -> Optional[str]: try: self._ensure_db() # 构建查询条件：标签匹配任一情感 query = {'tags': {'$in': emotion_tag}} # print(f"\033[1;34m[调试]\033[0m 表情查询条件: {query}") try: # 随机获取一个匹配的表情 emoji = self.db.db.emoji.aggregate([ {'$match': query}, {'$sample': {'size': 1}} ]).next() print(f"\033[1;32m[成功]\033[0m 找到匹配的表情") if emoji and 'path' in emoji: # 更新使用次数 self.db.db.emoji.update_one( {'_id': emoji['_id']}, {'$inc': {'usage_count': 1}} ) return emoji['path'] except StopIteration: # 如果没有匹配的表情，从所有表情中随机选择一个 print(f"\033[1;33m[提示]\033[0m 未找到匹配的表情，随机选择一个") try: emoji = self.db.db.emoji.aggregate([ {'$sample': {'size': 1}} ]).next() if emoji and 'path' in emoji: # 更新使用次数 self.db.db.emoji.update_one( {'_id': emoji['_id']}, {'$inc': {'usage_count': 1}} ) return emoji['path'] except StopIteration: print(f"\033[1;31m[错误]\033[0m 数据库中没有任何表情") return None return None except Exception as e: print(f"\033[1;31m[错误]\033[0m 获取表情包失败: {str(e)}") return None async def get_emoji_for_text(self, text: str) -> Optional[str]: """根据文本内容获取相关表情包 Args: text: 输入文本 Returns: Optional[str]: 表情包文件路径，如果没有找到则返回None """ try: self._ensure_db() # 获取情感标签 emotions = await self._get_emotion_from_text(text) print("为 ‘"+ str(text) + "’ 获取到的情感标签为：" + str(emotions)) if not emotions: return None # 构建查询条件：标签匹配任一情感 query = {'tags': {'$in': emotions}} print(f"\033[1;34m[调试]\033[0m 表情查询条件: {query}") print(f"\033[1;34m[调试]\033[0m 匹配到的情感: {emotions}") try: # 随机获取一个匹配的表情 emoji = self.db.db.emoji.aggregate([ {'$match': query}, {'$sample': {'size': 1}} ]).next() print(f"\033[1;32m[成功]\033[0m 找到匹配的表情") if emoji and 'path' in emoji: # 更新使用次数 self.db.db.emoji.update_one( {'_id': emoji['_id']}, {'$inc': {'usage_count': 1}} ) return emoji['path'] except StopIteration: # 如果没有匹配的表情，从所有表情中随机选择一个 print(f"\033[1;33m[提示]\033[0m 未找到匹配的表情，随机选择一个") try: emoji = self.db.db.emoji.aggregate([ {'$sample': {'size': 1}} ]).next() if emoji and 'path' in emoji: # 更新使用次数 self.db.db.emoji.update_one( {'_id': emoji['_id']}, {'$inc': {'usage_count': 1}} ) return emoji['path'] except StopIteration: print(f"\033[1;31m[错误]\033[0m 数据库中没有任何表情") return None return None except Exception as e: print(f"\033[1;31m[错误]\033[0m 获取表情包失败: {str(e)}") return None async def _get_emoji_tag(self, image_base64: str) -> str: """获取表情包的标签""" try: prompt = '这是一个表情包，请从"happy", "angry", "sad", "surprised", "disgusted", "fearful", "neutral"中选出1个情感标签。只输出标签，不要输出其他任何内容，只输出情感标签就好' content, _ = await self.llm.generate_response_for_image(prompt, image_base64) tag_result = content.strip().lower() valid_tags = ["happy", "angry", "sad", "surprised", "disgusted", "fearful", "neutral"] for tag_match in valid_tags: if tag_match in tag_result or tag_match == tag_result: return tag_match print(f"\033[1;33m[警告]\033[0m 无效的标签: {tag_result}, 跳过") except Exception as e: print(f"\033[1;31m[错误]\033[0m 获取标签失败: {str(e)}") print(f"\033[1;32m[调试信息]\033[0m 使用默认标签: neutral") return "skip" # 默认标签 async def scan_new_emojis(self): """扫描新的表情包""" try: emoji_dir = "data/emoji" os.makedirs(emoji_dir, exist_ok=True) # 获取所有jpg文件 files_to_process = [f for f in os.listdir(emoji_dir) if f.endswith('.jpg')] for filename in files_to_process: # 检查是否已经注册过 existing_emoji = self.db.db['emoji'].find_one({'filename': filename}) if existing_emoji: continue image_path = os.path.join(emoji_dir, filename) # 读取图片数据 with open(image_path, 'rb') as f: image_data = f.read() # 将图片转换为base64 image_base64 = base64.b64encode(image_data).decode('utf-8') # 获取表情包的情感标签 tag = await self._get_emoji_tag(image_base64) if not tag == "skip": # 准备数据库记录 emoji_record = { 'filename': filename, 'path': image_path, 'tags': [tag], 'timestamp': int(time.time()) } # 保存到数据库 self.db.db['emoji'].insert_one(emoji_record) print(f"\033[1;32m[成功]\033[0m 注册新表情包: {filename}") print(f"标签: {tag}") else: print(f"\033[1;33m[警告]\033[0m 跳过表情包: {filename}") except Exception as e: print(f"\033[1;31m[错误]\033[0m 扫描表情包失败: {str(e)}") import traceback print(traceback.format_exc()) async def _periodic_scan(self, interval_MINS: int = 10): """定期扫描新表情包""" while True: print(f"\033[1;36m[表情包]\033[0m 开始扫描新表情包...") await self.scan_new_emojis() await asyncio.sleep(interval_MINS * 60) # 每600秒扫描一次 def check_emoji_file_integrity(self): """检查表情包文件完整性 如果文件已被删除，则从数据库中移除对应记录 """ try: self._ensure_db() # 获取所有表情包记录 all_emojis = list(self.db.db.emoji.find()) removed_count = 0 total_count = len(all_emojis) for emoji in all_emojis: try: if 'path' not in emoji: print(f"\033[1;33m[提示]\033[0m 发现无效记录（缺少path字段），ID: {emoji.get('_id', 'unknown')}") self.db.db.emoji.delete_one({'_id': emoji['_id']}) removed_count += 1 continue # 检查文件是否存在 if not os.path.exists(emoji['path']): print(f"\033[1;33m[提示]\033[0m 表情包文件已被删除: {emoji['path']}") # 从数据库中删除记录 result = self.db.db.emoji.delete_one({'_id': emoji['_id']}) if result.deleted_count > 0: print(f"\033[1;32m[成功]\033[0m 成功删除数据库记录: {emoji['_id']}") removed_count += 1 else: print(f"\033[1;31m[错误]\033[0m 删除数据库记录失败: {emoji['_id']}") except Exception as item_error: print(f"\033[1;31m[错误]\033[0m 处理表情包记录时出错: {str(item_error)}") continue # 验证清理结果 remaining_count = self.db.db.emoji.count_documents({}) if removed_count > 0: print(f"\033[1;32m[成功]\033[0m 已清理 {removed_count} 个失效的表情包记录") print(f"\033[1;34m[统计]\033[0m 清理前总数: {total_count} | 清理后总数: {remaining_count}") # print(f"\033[1;34m[统计]\033[0m 应删除数量: {removed_count} | 实际删除数量: {total_count - remaining_count}") # 执行数据库压缩 try: self.db.db.command({"compact": "emoji"}) print(f"\033[1;32m[成功]\033[0m 数据库集合压缩完成") except Exception as compact_error: print(f"\033[1;31m[错误]\033[0m 数据库压缩失败: {str(compact_error)}") else: print(f"\033[1;36m[表情包]\033[0m 已检查 {total_count} 个表情包记录") except Exception as e: print(f"\033[1;31m[错误]\033[0m 检查表情包完整性失败: {str(e)}") import traceback print(f"\033[1;31m[错误追踪]\033[0m\n{traceback.format_exc()}") async def start_periodic_check(self, interval_MINS: int = 120): while True: self.check_emoji_file_integrity() await asyncio.sleep(interval_MINS * 60) # 创建全局单例 emoji_manager = EmojiManager()