feat: add all application source code
- apps/api: FastAPI backend with Dockerfile - apps/web: Next.js frontend with Dockerfile - apps/sensor: Signal collection agent - packages: shared packages Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
OG T
411
apps/api/src/db/models.py
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411
apps/api/src/db/models.py
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"""
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Database Models
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===============
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CTO-201: Approval & AuditLog persistence
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Schema 設計原則：
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- UUID 主鍵 (PostgreSQL 相容)
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- JSON 欄位儲存複雜結構
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- 完整時間戳記
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- 索引優化查詢
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"""
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from datetime import datetime, timezone
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from typing import Any
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from uuid import uuid4
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from sqlalchemy import (
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DateTime,
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Enum as SQLEnum,
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Index,
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Integer,
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String,
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Text,
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JSON,
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)
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from sqlalchemy.orm import Mapped, mapped_column
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from src.db.base import Base
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from src.models.approval import ApprovalStatus, RiskLevel
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from src.models.incident import Severity, IncidentStatus
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# =============================================================================
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# Helper Functions
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# =============================================================================
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def utc_now() -> datetime:
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"""Get current UTC datetime"""
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return datetime.now(timezone.utc)
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def generate_uuid() -> str:
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"""Generate UUID string"""
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return str(uuid4())
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# =============================================================================
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# ApprovalRecord - 授權記錄持久化
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# =============================================================================
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class ApprovalRecord(Base):
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"""
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授權記錄 - 對應 Pydantic ApprovalRequest
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Note: 與 in-memory TrustEngine 的 ApprovalRequest 同步
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"""
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__tablename__ = "approval_records"
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# Primary Key
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id: Mapped[str] = mapped_column(
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String(36),
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primary_key=True,
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default=generate_uuid,
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)
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# Core Fields
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action: Mapped[str] = mapped_column(String(500), nullable=False)
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description: Mapped[str] = mapped_column(Text, nullable=False)
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status: Mapped[str] = mapped_column(
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SQLEnum(ApprovalStatus),
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default=ApprovalStatus.PENDING,
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nullable=False,
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)
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risk_level: Mapped[str] = mapped_column(
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SQLEnum(RiskLevel),
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nullable=False,
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)
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# Signature Tracking
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required_signatures: Mapped[int] = mapped_column(Integer, default=1)
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current_signatures: Mapped[int] = mapped_column(Integer, default=0)
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signatures: Mapped[dict[str, Any]] = mapped_column(JSON, default=list)
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# Blast Radius (JSON)
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blast_radius: Mapped[dict[str, Any]] = mapped_column(JSON, default=dict)
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# Dry-Run Checks (JSON)
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dry_run_checks: Mapped[list[dict[str, Any]]] = mapped_column(JSON, default=list)
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# Metadata
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requested_by: Mapped[str] = mapped_column(String(100), nullable=False)
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rejection_reason: Mapped[str | None] = mapped_column(Text, nullable=True)
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extra_metadata: Mapped[dict[str, Any] | None] = mapped_column(JSON, nullable=True)
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# ==========================================================================
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# 戰略 B: 告警風暴收斂 (Alert Storm Convergence)
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# ==========================================================================
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# 告警指紋 - 根據 namespace + deployment + alert_name 產生的唯一 Hash
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fingerprint: Mapped[str | None] = mapped_column(
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String(64),
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nullable=True,
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index=True,
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comment="SHA256 hash of alert identity (namespace:deployment:alert_name)",
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)
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# 聚合次數 - 相同指紋告警的累計觸發次數
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hit_count: Mapped[int] = mapped_column(
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Integer,
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default=1,
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nullable=False,
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comment="Number of times this alert pattern was triggered",
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)
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# 最後觸發時間 - 同指紋告警最近一次出現的時間
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last_seen_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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nullable=False,
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comment="Last time this alert pattern was seen",
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)
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# Timestamps
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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)
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updated_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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onupdate=utc_now,
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)
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expires_at: Mapped[datetime | None] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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)
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resolved_at: Mapped[datetime | None] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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)
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# Indexes
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__table_args__ = (
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Index("ix_approval_status", "status"),
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Index("ix_approval_risk_level", "risk_level"),
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Index("ix_approval_created_at", "created_at"),
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Index("ix_approval_requested_by", "requested_by"),
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Index("ix_approval_fingerprint", "fingerprint"), # 戰略 B: 指紋查詢優化
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)
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# =============================================================================
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# AuditLog - 稽核日誌
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# =============================================================================
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class TimelineEvent(Base):
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"""
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時間軸事件 - Phase 4 Action Timeline
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事件類型:
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- system: 系統告警接收
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- agent: ClawBot AI 分析
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- security: 權限阻擋
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- human: 人類授權
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- exec: 執行完成
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"""
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__tablename__ = "timeline_events"
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# Primary Key
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id: Mapped[str] = mapped_column(
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String(36),
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primary_key=True,
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default=generate_uuid,
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)
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# Event Type & Status
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event_type: Mapped[str] = mapped_column(
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String(20),
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nullable=False,
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comment="system, agent, security, human, exec",
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)
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status: Mapped[str] = mapped_column(
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String(20),
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nullable=False,
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default="info",
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comment="info, success, warning, error",
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)
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# Content
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title: Mapped[str] = mapped_column(String(500), nullable=False)
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description: Mapped[str | None] = mapped_column(Text, nullable=True)
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# Actor
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actor: Mapped[str | None] = mapped_column(String(100), nullable=True)
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actor_role: Mapped[str | None] = mapped_column(String(50), nullable=True)
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# Context
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risk_level: Mapped[str | None] = mapped_column(String(20), nullable=True)
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approval_id: Mapped[str | None] = mapped_column(String(36), nullable=True, index=True)
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# Timestamp
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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)
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# Indexes
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__table_args__ = (
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Index("ix_timeline_event_type", "event_type"),
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Index("ix_timeline_created_at", "created_at"),
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)
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class AuditLog(Base):
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"""
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稽核日誌 - 記錄所有執行結果
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每次 K8s 操作完成後寫入一筆記錄
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"""
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__tablename__ = "audit_logs"
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# Primary Key
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id: Mapped[str] = mapped_column(
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String(36),
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primary_key=True,
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default=generate_uuid,
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)
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# Reference to Approval
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approval_id: Mapped[str] = mapped_column(
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String(36),
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nullable=False,
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index=True,
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)
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# Operation Details
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operation_type: Mapped[str] = mapped_column(
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String(50),
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nullable=False,
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comment="e.g., RESTART_DEPLOYMENT, DELETE_POD",
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)
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target_resource: Mapped[str] = mapped_column(
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String(200),
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nullable=False,
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comment="e.g., deployment/api-backend, pod/nginx-xxx",
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)
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namespace: Mapped[str] = mapped_column(
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String(63),
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default="default",
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nullable=False,
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)
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# Execution Result
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success: Mapped[bool] = mapped_column(default=False, nullable=False)
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error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
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# K8s Response (Raw)
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k8s_response: Mapped[dict[str, Any] | None] = mapped_column(
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JSON,
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nullable=True,
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comment="Raw Kubernetes API response",
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)
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# Execution Context
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executed_by: Mapped[str] = mapped_column(
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String(100),
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nullable=False,
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comment="Who triggered the execution",
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)
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execution_duration_ms: Mapped[int | None] = mapped_column(
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Integer,
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nullable=True,
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comment="Execution time in milliseconds",
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)
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# Dry-Run Result (pre-execution validation)
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dry_run_passed: Mapped[bool] = mapped_column(
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default=True,
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nullable=False,
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)
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dry_run_message: Mapped[str | None] = mapped_column(Text, nullable=True)
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# Timestamps
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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)
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# Indexes
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__table_args__ = (
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Index("ix_audit_approval_id", "approval_id"),
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Index("ix_audit_operation_type", "operation_type"),
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Index("ix_audit_success", "success"),
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Index("ix_audit_created_at", "created_at"),
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)
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# =============================================================================
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# IncidentRecord - Phase 6.2 Episodic Memory (PostgreSQL)
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# =============================================================================
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class IncidentRecord(Base):
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"""
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事件記錄 - 對應 Pydantic Incident Schema v0.3
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Phase 6.2: Episodic Memory (長期記憶)
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- 從 Working Memory (Redis) 遷移過來
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- 永久保留，供 RAG 檢索
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- 複雜結構使用 JSONB 欄位
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三層記憶架構:
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- Working Memory (Redis): 7 天 TTL
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- Episodic Memory (PostgreSQL): 此表，永久保留
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- Semantic Memory (Vector DB): Phase 6.3+
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"""
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__tablename__ = "incidents"
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# === 主鍵 ===
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incident_id: Mapped[str] = mapped_column(
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String(30),
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primary_key=True,
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comment="事件唯一識別碼 (如 INC-20260322-A1B2C3)",
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)
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# === 狀態與嚴重度 ===
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status: Mapped[str] = mapped_column(
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SQLEnum(IncidentStatus),
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default=IncidentStatus.INVESTIGATING,
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nullable=False,
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comment="事件狀態 (investigating, mitigating, resolved, closed, escalated)",
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)
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severity: Mapped[str] = mapped_column(
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SQLEnum(Severity),
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nullable=False,
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comment="事件嚴重度 (P0, P1, P2, P3)",
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)
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# === 感知層 (Signals) - JSONB ===
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signals: Mapped[list[dict[str, Any]]] = mapped_column(
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JSON,
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default=list,
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nullable=False,
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comment="關聯的告警信號列表 (JSONB)",
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)
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affected_services: Mapped[list[str]] = mapped_column(
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JSON,
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default=list,
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nullable=False,
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comment="受影響的服務列表",
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)
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# === 認知層 (AI Decision Chain) - JSONB ===
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decision_chain: Mapped[dict[str, Any] | None] = mapped_column(
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JSON,
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nullable=True,
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comment="AI 決策鏈 (完整推論過程)",
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)
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# === 決策層 (Proposals) ===
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proposal_ids: Mapped[list[str]] = mapped_column(
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JSON,
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default=list,
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nullable=False,
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comment="關聯的 ApprovalRequest ID 列表",
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)
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# === 結果層 (Outcome) - JSONB ===
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outcome: Mapped[dict[str, Any] | None] = mapped_column(
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JSON,
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nullable=True,
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comment="事件結果與人類回饋",
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)
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# === 時間軸 ===
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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nullable=False,
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)
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updated_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=utc_now,
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onupdate=utc_now,
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nullable=False,
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)
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resolved_at: Mapped[datetime | None] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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)
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closed_at: Mapped[datetime | None] = mapped_column(
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DateTime(timezone=True),
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nullable=True,
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)
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# === 記憶管理 ===
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ttl_days: Mapped[int] = mapped_column(
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Integer,
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default=7,
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nullable=False,
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comment="Working Memory TTL (天)",
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)
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vectorized: Mapped[bool] = mapped_column(
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default=False,
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nullable=False,
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comment="是否已向量化到 Vector DB (Semantic Memory)",
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)
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# === 索引 ===
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__table_args__ = (
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Index("ix_incident_status", "status"),
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Index("ix_incident_severity", "severity"),
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Index("ix_incident_created_at", "created_at"),
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Index("ix_incident_resolved_at", "resolved_at"),
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)
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