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✨ feat(avatar): 引入头像缓存服务并优化头像获取 (#2055)
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Co-authored-by: webjoin111 <455457521@qq.com>
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@@ -18,6 +18,7 @@ require("nonebot_plugin_htmlrender")
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require("nonebot_plugin_uninfo")
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require("nonebot_plugin_waiter")
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from .avatar_service import avatar_service
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from .db_context import Model, disconnect, with_db_timeout
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from .llm import (
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AI,
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@@ -57,6 +58,7 @@ __all__ = [
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"Model",
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"PluginInit",
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"PluginInitManager",
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"avatar_service",
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"chat",
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"clear_model_cache",
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"code",
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@@ -0,0 +1,141 @@
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"""
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头像缓存服务
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提供一个统一的、带缓存的头像获取服务,支持多平台和可配置的过期策略。
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"""
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import os
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from pathlib import Path
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import time
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from nonebot_plugin_apscheduler import scheduler
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from zhenxun.configs.config import Config
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from zhenxun.configs.path_config import DATA_PATH
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from zhenxun.services.log import logger
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from zhenxun.utils.http_utils import AsyncHttpx
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from zhenxun.utils.platform import PlatformUtils
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Config.add_plugin_config(
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"avatar_cache",
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"ENABLED",
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True,
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help="是否启用头像缓存功能",
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default_value=True,
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type=bool,
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)
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Config.add_plugin_config(
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"avatar_cache",
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"TTL_DAYS",
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7,
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help="头像缓存的有效期(天)",
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default_value=7,
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type=int,
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)
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Config.add_plugin_config(
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"avatar_cache",
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"CLEANUP_INTERVAL_HOURS",
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24,
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help="后台清理过期缓存的间隔时间(小时)",
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default_value=24,
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type=int,
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)
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class AvatarService:
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"""
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一个集中式的头像缓存服务,提供L1(内存)和L2(文件)两级缓存。
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"""
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def __init__(self):
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self.cache_path = (DATA_PATH / "cache" / "avatars").resolve()
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self.cache_path.mkdir(parents=True, exist_ok=True)
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self._memory_cache: dict[str, Path] = {}
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def _get_cache_path(self, platform: str, identifier: str) -> Path:
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"""
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根据平台和ID生成存储的文件路径。
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例如: data/cache/avatars/qq/123456789.png
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"""
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identifier = str(identifier)
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return self.cache_path / platform / f"{identifier}.png"
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async def get_avatar_path(
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self, platform: str, identifier: str, force_refresh: bool = False
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) -> Path | None:
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"""
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获取用户或群组的头像本地路径。
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参数:
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platform: 平台名称 (e.g., 'qq')
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identifier: 用户ID或群组ID
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force_refresh: 是否强制刷新缓存
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返回:
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Path | None: 头像的本地文件路径,如果获取失败则返回None。
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"""
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if not Config.get_config("avatar_cache", "ENABLED"):
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return None
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cache_key = f"{platform}-{identifier}"
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if not force_refresh and cache_key in self._memory_cache:
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if self._memory_cache[cache_key].exists():
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return self._memory_cache[cache_key]
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local_path = self._get_cache_path(platform, identifier)
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ttl_seconds = Config.get_config("avatar_cache", "TTL_DAYS", 7) * 86400
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if not force_refresh and local_path.exists():
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try:
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file_mtime = os.path.getmtime(local_path)
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if time.time() - file_mtime < ttl_seconds:
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self._memory_cache[cache_key] = local_path
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return local_path
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except FileNotFoundError:
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pass
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avatar_url = PlatformUtils.get_user_avatar_url(identifier, platform)
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if not avatar_url:
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return None
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local_path.parent.mkdir(parents=True, exist_ok=True)
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if await AsyncHttpx.download_file(avatar_url, local_path):
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self._memory_cache[cache_key] = local_path
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return local_path
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else:
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logger.warning(f"下载头像失败: {avatar_url}", "AvatarService")
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return None
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async def _cleanup_cache(self):
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"""后台定时清理过期的缓存文件"""
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if not Config.get_config("avatar_cache", "ENABLED"):
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return
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logger.info("开始执行头像缓存清理任务...", "AvatarService")
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ttl_seconds = Config.get_config("avatar_cache", "TTL_DAYS", 7) * 86400
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now = time.time()
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deleted_count = 0
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for root, _, files in os.walk(self.cache_path):
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for name in files:
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file_path = Path(root) / name
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try:
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if now - os.path.getmtime(file_path) > ttl_seconds:
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file_path.unlink()
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deleted_count += 1
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except FileNotFoundError:
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continue
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logger.info(
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f"头像缓存清理完成,共删除 {deleted_count} 个过期文件。", "AvatarService"
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)
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avatar_service = AvatarService()
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@scheduler.scheduled_job(
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"interval", hours=Config.get_config("avatar_cache", "CLEANUP_INTERVAL_HOURS", 24)
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)
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async def _run_avatar_cache_cleanup():
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await avatar_service._cleanup_cache()
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