feat: 支持 SQLite + 离线部署 + MCP 启动优化
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xiamuceer
+73
-42
@@ -60,52 +60,83 @@ async def get_engine(user_id: str):
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async with _cache_lock:
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if cache_key not in _engine_cache:
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# 优化后的PostgreSQL连接配置
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connect_args = {
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"server_settings": {
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"application_name": settings.app_name,
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"jit": "off", # 关闭JIT以提高短查询性能
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},
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"command_timeout": 60, # 命令超时60秒
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"statement_cache_size": 500, # 启用语句缓存，提升重复查询性能
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# 检测数据库类型
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is_sqlite = 'sqlite' in settings.database_url.lower()
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# 基础引擎参数
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engine_args = {
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"echo": settings.database_echo_pool,
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"echo_pool": settings.database_echo_pool,
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"future": True,
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}
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engine = create_async_engine(
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settings.database_url,
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echo=settings.database_echo_pool, # 根据配置决定是否输出连接池日志
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echo_pool=settings.database_echo_pool, # 连接池操作日志
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future=True,
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pool_size=settings.database_pool_size, # 核心连接数：50（优化后）
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max_overflow=settings.database_max_overflow, # 溢出连接数：30（优化后）
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pool_timeout=settings.database_pool_timeout, # 连接超时：90秒（优化后）
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pool_pre_ping=settings.database_pool_pre_ping, # 连接前检测
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pool_recycle=settings.database_pool_recycle, # 连接回收：1800秒
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pool_use_lifo=settings.database_pool_use_lifo, # LIFO策略提高复用
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pool_reset_on_return=settings.database_pool_reset_on_return, # 连接归还时重置
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max_identifier_length=settings.database_max_identifier_length, # 标识符最大长度
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connect_args=connect_args
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)
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if is_sqlite:
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# SQLite 配置（使用 NullPool，不支持连接池参数）
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engine_args["connect_args"] = {
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"check_same_thread": False,
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"timeout": 30.0, # 等待锁释放的超时时间（秒）
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}
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# 启用连接前检测以支持更好的并发
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engine_args["pool_pre_ping"] = True
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logger.info("📊 使用 SQLite 数据库（NullPool，超时30秒，WAL模式）")
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else:
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# PostgreSQL 配置（完整连接池支持）
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connect_args = {
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"server_settings": {
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"application_name": settings.app_name,
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"jit": "off",
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},
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"command_timeout": 60,
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"statement_cache_size": 500,
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}
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engine_args.update({
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"pool_size": settings.database_pool_size,
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"max_overflow": settings.database_max_overflow,
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"pool_timeout": settings.database_pool_timeout,
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"pool_pre_ping": settings.database_pool_pre_ping,
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"pool_recycle": settings.database_pool_recycle,
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"pool_use_lifo": settings.database_pool_use_lifo,
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"pool_reset_on_return": settings.database_pool_reset_on_return,
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"max_identifier_length": settings.database_max_identifier_length,
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"connect_args": connect_args
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})
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total_connections = settings.database_pool_size + settings.database_max_overflow
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estimated_concurrent_users = total_connections * 2
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logger.info(
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f"📊 PostgreSQL 连接池配置:\n"
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f" ├─ 核心连接: {settings.database_pool_size}\n"
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f" ├─ 溢出连接: {settings.database_max_overflow}\n"
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f" ├─ 总连接数: {total_connections}\n"
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f" ├─ 获取超时: {settings.database_pool_timeout}秒\n"
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f" ├─ 连接回收: {settings.database_pool_recycle}秒\n"
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f" └─ 预估并发: {estimated_concurrent_users}+用户"
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)
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engine = create_async_engine(settings.database_url, **engine_args)
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_engine_cache[cache_key] = engine
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# 计算总连接数和预估并发能力
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total_connections = settings.database_pool_size + settings.database_max_overflow
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estimated_concurrent_users = total_connections * 2 # 每个用户平均0.5个连接
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logger.info(
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f" \n"
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f" ├─ 连接池配置:\n"
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f" │ ├─ 核心连接: {settings.database_pool_size}\n"
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f" │ ├─ 溢出连接: {settings.database_max_overflow}\n"
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f" │ └─ 总连接数: {total_connections}\n"
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f" ├─ 超时配置:\n"
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f" │ ├─ 获取超时: {settings.database_pool_timeout}秒\n"
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f" │ └─ 连接回收: {settings.database_pool_recycle}秒 ({settings.database_pool_recycle//60}分钟)\n"
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f" ├─ 优化策略:\n"
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f" │ ├─ 复用策略: LIFO（后进先出）\n"
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f" │ ├─ 健康检查: Pre-ping enabled\n"
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f" │ └─ 归还重置: {settings.database_pool_reset_on_return}\n"
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f" └─ 预估并发: {estimated_concurrent_users}-{estimated_concurrent_users + 50}用户"
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)
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# 如果是 SQLite，启用 WAL 模式以支持读写并发
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if is_sqlite:
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try:
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from sqlalchemy import event
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from sqlalchemy.pool import NullPool
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@event.listens_for(engine.sync_engine, "connect")
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def set_sqlite_pragma(dbapi_conn, connection_record):
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cursor = dbapi_conn.cursor()
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cursor.execute("PRAGMA journal_mode=WAL")
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cursor.execute("PRAGMA synchronous=NORMAL")
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cursor.execute("PRAGMA cache_size=-64000") # 64MB 缓存
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cursor.execute("PRAGMA busy_timeout=30000") # 30秒超时
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cursor.close()
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logger.info("✅ SQLite WAL 模式已启用（支持读写并发）")
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except Exception as e:
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logger.warning(f"⚠️ 启用 WAL 模式失败: {e}，使用默认配置")
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return _engine_cache[cache_key]
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