changes:(services) Modify the query method for user memory to batch processing.
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@@ -353,15 +353,13 @@ async def get_workspace_total_memory_count(
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"details": []
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}
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# 2. 对每个 host_id 调用 search_all 获取 total
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# 2. 使用 search_all_batch 批量查询所有宿主的记忆数量
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from app.services import memory_storage_service
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total_count = 0
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details = []
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# 如果提供了 end_user_id,只查询该用户
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if end_user_id:
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search_result = await memory_storage_service.search_all(end_user_id=end_user_id)
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batch_result = await memory_storage_service.search_all_batch([end_user_id])
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count = batch_result.get(end_user_id, 0)
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# 查询用户名称
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from app.repositories.end_user_repository import EndUserRepository
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repo = EndUserRepository(db)
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@@ -369,42 +367,31 @@ async def get_workspace_total_memory_count(
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user_name = end_user.other_name if end_user else None
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return {
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"total_memory_count": search_result.get("total", 0),
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"total_memory_count": count,
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"host_count": 1,
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"details": [{
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"end_user_id": end_user_id,
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"count": search_result.get("total", 0),
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"count": count,
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"name": user_name
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}]
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}
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for host in hosts:
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try:
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end_user_id_str = str(host.id)
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search_result = await memory_storage_service.search_all(
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end_user_id=end_user_id_str
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)
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host_total = search_result.get("total", 0)
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total_count += host_total
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details.append({
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"end_user_id": end_user_id_str,
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"count": host_total,
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"name": host.other_name # 使用 other_name 字段
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})
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business_logger.debug(f"EndUser {end_user_id_str} ({host.other_name}) 记忆数: {host_total}")
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except Exception as e:
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business_logger.warning(f"获取 end_user {host.id} 记忆数失败: {str(e)}")
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# 失败的 host 记为 0
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details.append({
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"end_user_id": str(host.id),
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"count": 0,
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"name": host.other_name # 使用 other_name 字段
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})
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# 批量查询所有宿主记忆数量(一次 Neo4j 查询)
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end_user_ids = [str(host.id) for host in hosts]
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batch_result = await memory_storage_service.search_all_batch(end_user_ids)
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# 构建 host name 映射
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host_name_map = {str(host.id): host.other_name for host in hosts}
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total_count = sum(batch_result.values())
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details = [
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{
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"end_user_id": uid,
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"count": batch_result.get(uid, 0),
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"name": host_name_map.get(uid)
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}
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for uid in end_user_ids
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]
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result = {
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"total_memory_count": total_count,
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@@ -6,13 +6,13 @@
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"""
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import time
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from contextlib import contextmanager
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from contextlib import asynccontextmanager, contextmanager
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from app.core.logging_config import get_api_logger
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# 获取API专用日志器
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api_logger = get_api_logger()
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# 同步的上下文管理器,使用@contextmanager修饰
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@contextmanager
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def timer(label: str, user_count: int = 0):
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"""上下文管理器:用于测量代码块执行时间
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@@ -35,3 +35,27 @@ def timer(label: str, user_count: int = 0):
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elapsed = (time.perf_counter() - start) * 1000 # 转换为毫秒
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extra_info = f", 用户数: {user_count}" if user_count > 0 else ""
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api_logger.info(f"[性能统计] {label}: {elapsed:.2f}ms{extra_info}")
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# 异步的上下文管理器,使用@asynccontextmanager装饰
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@asynccontextmanager
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async def async_timer(label: str, user_count: int = 0):
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"""异步上下文管理器:用于测量包含 await 的异步代码块执行时间
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Args:
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label: 统计标签,用于标识被测量的代码块
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user_count: 用户数,可选参数,用于记录处理的用户数量
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Usage:
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async with async_timer("获取用户列表"):
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users = await get_users()
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async with async_timer("批量处理", user_count=len(user_ids)):
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await process_users(user_ids)
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"""
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start = time.perf_counter()
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try:
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yield
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finally:
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elapsed = (time.perf_counter() - start) * 1000 # 转换为毫秒
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extra_info = f", 用户数: {user_count}" if user_count > 0 else ""
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api_logger.info(f"[性能统计] {label}: {elapsed:.2f}ms{extra_info}")
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