16337
baa895a6f1
- 创建 FastAPI 项目结构 - 实现告警数据模型（SQLAlchemy） - 实现 multipart/form-data 告警接收接口 - 实现阿里云 OSS 图片上传模块 - 实现告警查询和处理 API - 实现异步大模型分析模块
120 lines
3.8 KiB
Python
120 lines
3.8 KiB
Python
import enum
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from datetime import datetime, timezone
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from typing import Optional
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from sqlalchemy import Column, String, Integer, DateTime, Text, Enum, JSON, create_engine
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from sqlalchemy.orm import declarative_base, sessionmaker
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from sqlalchemy.pool import StaticPool
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from app.config import settings
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Base = declarative_base()
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class AlertStatus(str, enum.Enum):
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PENDING = "pending"
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CONFIRMED = "confirmed"
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IGNORED = "ignored"
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RESOLVED = "resolved"
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class AlertLevel(str, enum.Enum):
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LOW = "low"
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MEDIUM = "medium"
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HIGH = "high"
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CRITICAL = "critical"
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class Alert(Base):
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__tablename__ = "alerts"
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id = Column(Integer, primary_key=True, autoincrement=True)
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alert_no = Column(String(32), unique=True, nullable=False, index=True)
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camera_id = Column(String(64), nullable=False, index=True)
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roi_id = Column(String(64), nullable=True)
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alert_type = Column(String(64), nullable=False)
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algorithm = Column(String(128), nullable=True)
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confidence = Column(Integer, nullable=True)
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duration_minutes = Column(Integer, nullable=True)
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trigger_time = Column(DateTime, nullable=False)
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message = Column(Text, nullable=True)
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snapshot_url = Column(String(512), nullable=True)
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snapshot_path = Column(String(512), nullable=True)
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status = Column(Enum(AlertStatus), default=AlertStatus.PENDING)
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handle_remark = Column(Text, nullable=True)
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handled_by = Column(String(64), nullable=True)
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handled_at = Column(DateTime, nullable=True)
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ai_analysis = Column(JSON, nullable=True)
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created_at = Column(DateTime, default=lambda: datetime.now(timezone.utc))
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updated_at = Column(DateTime, default=lambda: datetime.now(timezone.utc), onupdate=lambda: datetime.now(timezone.utc))
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def to_dict(self) -> dict:
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return {
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"id": self.id,
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"alert_no": self.alert_no,
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"camera_id": self.camera_id,
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"roi_id": self.roi_id,
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"alert_type": self.alert_type,
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"algorithm": self.algorithm,
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"confidence": self.confidence,
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"duration_minutes": self.duration_minutes,
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"trigger_time": self.trigger_time.isoformat() if self.trigger_time else None,
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"message": self.message,
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"snapshot_url": self.snapshot_url,
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"status": self.status.value if self.status else None,
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"handle_remark": self.handle_remark,
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"handled_by": self.handled_by,
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"handled_at": self.handled_at.isoformat() if self.handled_at else None,
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"ai_analysis": self.ai_analysis,
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"created_at": self.created_at.isoformat() if self.created_at else None,
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"updated_at": self.updated_at.isoformat() if self.updated_at else None,
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}
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_engine = None
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_SessionLocal = None
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def get_engine():
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global _engine
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if _engine is None:
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db_url = settings.database.url
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connect_args = {}
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if "sqlite" in db_url:
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db_path = db_url.replace("sqlite:///", "")
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os.makedirs(os.path.dirname(db_path) if os.path.dirname(db_path) else ".", exist_ok=True)
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connect_args = {"check_same_thread": False}
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_engine = create_engine(
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db_url,
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echo=settings.app.debug,
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poolclass=StaticPool if "sqlite" in db_url else None,
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connect_args=connect_args,
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)
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else:
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_engine = create_engine(db_url, echo=settings.app.debug)
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return _engine
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def get_session():
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global _SessionLocal
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if _SessionLocal is None:
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_SessionLocal = sessionmaker(bind=get_engine(), autocommit=False, autoflush=False)
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return _SessionLocal()
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def init_db():
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engine = get_engine()
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Base.metadata.create_all(bind=engine)
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def close_db():
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global _engine, _SessionLocal
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if _engine:
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_engine.dispose()
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_engine = None
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_SessionLocal = None
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