import base64 import os import time import aiohttp import hashlib from typing import Optional, Union from PIL import Image import io from loguru import logger from nonebot import get_driver from ...common.database import db from ..chat.config import global_config from ..models.utils_model import LLM_request driver = get_driver() config = driver.config 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._initialized = False return cls._instance def __init__(self): if not self._initialized: 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 db.list_collection_names(): db.create_collection("images") # 创建索引 db.images.create_index([("hash", 1)], unique=True) db.images.create_index([("url", 1)]) db.images.create_index([("path", 1)]) def _ensure_description_collection(self): """确保image_descriptions集合存在并创建索引""" if "image_descriptions" not in db.list_collection_names(): db.create_collection("image_descriptions") # 创建索引 db.image_descriptions.create_index([("hash", 1)], unique=True) db.image_descriptions.create_index([("type", 1)]) def _get_description_from_db(self, image_hash: str, description_type: str) -> Optional[str]: """从数据库获取图片描述 Args: image_hash: 图片哈希值 description_type: 描述类型 ('emoji' 或 'image') Returns: Optional[str]: 描述文本，如果不存在则返回None """ result = 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 Args: image_hash: 图片哈希值 description: 描述文本 description_type: 描述类型 ('emoji' 或 'image') """ db.image_descriptions.update_one( {"hash": image_hash, "type": description_type}, {"$set": {"description": description, "timestamp": int(time.time())}}, upsert=True, ) async def get_image_by_url(self, url: str) -> Optional[str]: """根据URL获取图像路径(带查重) Args: url: 图像URL Returns: str: 本地文件路径,不存在返回None """ try: # 先查找是否已存在 existing = db.images.find_one({"url": url}) if existing: return existing["path"] # 下载图像 async with aiohttp.ClientSession() as session: async with session.get(url) as resp: if resp.status == 200: image_bytes = await resp.read() return await self.save_image(image_bytes, url=url) return None except Exception as e: logger.error(f"获取图像失败: {str(e)}") return None async def get_emoji_description(self, image_base64: str) -> str: """获取表情包描述，带查重和保存功能""" try: # 计算图片哈希 image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # 查询缓存的描述 cached_description = self._get_description_from_db(image_hash, "emoji") if cached_description: logger.info(f"缓存表情包描述: {cached_description}") return f"[表情包：{cached_description}]" # 调用AI获取描述 prompt = "这是一个表情包，使用中文简洁的描述一下表情包的内容和表情包所表达的情感" description, _ = await self._llm.generate_response_for_image(prompt, image_base64, image_format) cached_description = self._get_description_from_db(image_hash, "emoji") if cached_description: logger.warning(f"虽然生成了描述，但找到缓存表情包描述: {cached_description}") return f"[表情包：{cached_description}]" # 根据配置决定是否保存图片 if global_config.EMOJI_SAVE: # 生成文件名和路径 timestamp = int(time.time()) filename = f"{timestamp}_{image_hash[:8]}.{image_format}" if not os.path.exists(os.path.join(self.IMAGE_DIR, "emoji")): os.makedirs(os.path.join(self.IMAGE_DIR, "emoji")) file_path = os.path.join(self.IMAGE_DIR, "emoji", filename) try: # 保存文件 with open(file_path, "wb") as f: f.write(image_bytes) # 保存到数据库 image_doc = { "hash": image_hash, "path": file_path, "type": "emoji", "description": description, "timestamp": timestamp, } db.images.update_one({"hash": image_hash}, {"$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: print("处理图片中") # 计算图片哈希 image_bytes = base64.b64decode(image_base64) image_hash = hashlib.md5(image_bytes).hexdigest() image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # 查询缓存的描述 cached_description = self._get_description_from_db(image_hash, "image") if cached_description: print("图片描述缓存中") 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, image_format) cached_description = self._get_description_from_db(image_hash, "emoji") if cached_description: logger.info(f"缓存图片描述: {cached_description}") return f"[图片：{cached_description}]" print(f"描述是{description}") 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"{timestamp}_{image_hash[:8]}.{image_format}" if not os.path.exists(os.path.join(self.IMAGE_DIR, "image")): os.makedirs(os.path.join(self.IMAGE_DIR, "image")) file_path = os.path.join(self.IMAGE_DIR, "image", 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, } 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 Args: image_path: 图片文件路径 Returns: str: base64编码的图片数据 """ try: with open(image_path, "rb") as f: image_data = f.read() return base64.b64encode(image_data).decode("utf-8") except Exception as e: logger.error(f"读取图片失败: {image_path}, 错误: {str(e)}") return None