bf45b80bd2
Some checks failed
CD Pipeline / build-and-deploy (push) Has been cancelled
ADR-085: AI 學習成果不可存在 Cache 架構鐵律確立： - PostgreSQL = System of Record（AI 的永久記憶） - Redis = Warm Cache（加速讀取，TTL 到期從 PG 復原） 核心變更： 1. models.py: 新增 PlaybookRecord / DynamicBaselineRecord / LogClusterRecord ORM 2. base.py: ALTER TABLE playbooks 補加 trust_score / requires_approval_level 等欄位 3. playbook_repository.py: 完整雙寫實作（PG upsert + Redis cache） 4. dynamic_baseline_service.py: Holt-Winters 訓練結果寫入 PG，Redis 只作 24h warm cache 5. log_anomaly_detector.py: Drain3 cluster template 寫入 PG（UPSERT on cluster_id） 6. main.py: 啟動時執行 backfill_redis_to_pg()（Redis → PG 冪等補救） 修正的問題： - Playbook 7天 Redis TTL 到期 → AI 失去所有修復知識 - trust_score EWMA 隨 Redis TTL 歸零 → AI 重新回到初始信任度 0.3 - Holt-Winters 基線 24h TTL → AI 每天重新學習「正常」的定義 - Drain3 cluster 沒有持久化 → AI 把已知 log pattern 反覆當新 pattern Phase 4 新服務（requirements.txt 已加入 statsmodels + drain3 + numpy） Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1113 lines
40 KiB
Python
1113 lines
40 KiB
Python
"""
|
||
Database Models
|
||
===============
|
||
CTO-201: Approval & AuditLog persistence
|
||
|
||
Schema 設計原則：
|
||
- UUID 主鍵 (PostgreSQL 相容)
|
||
- JSON 欄位儲存複雜結構
|
||
- 完整時間戳記
|
||
- 索引優化查詢
|
||
"""
|
||
|
||
from datetime import datetime
|
||
from typing import Any
|
||
from uuid import uuid4
|
||
|
||
from sqlalchemy import (
|
||
JSON,
|
||
DateTime,
|
||
Index,
|
||
Integer,
|
||
String,
|
||
Text,
|
||
)
|
||
from sqlalchemy import (
|
||
Enum as SQLEnum,
|
||
)
|
||
from sqlalchemy.dialects.postgresql import ENUM as PgEnum
|
||
from sqlalchemy.orm import Mapped, mapped_column
|
||
|
||
from src.db.base import Base
|
||
from src.models.approval import ApprovalStatus, RiskLevel
|
||
from src.models.incident import IncidentStatus, Severity
|
||
from src.models.knowledge import EntrySource, EntryStatus, EntryType
|
||
|
||
# =============================================================================
|
||
# Helper Functions
|
||
# =============================================================================
|
||
|
||
def taipei_now() -> datetime:
|
||
"""取得台北時區當前時間 (UTC+8)
|
||
|
||
🔴 HARD RULE: 全系統使用台北時區，禁止 UTC
|
||
2026-04-02 Claude Code: C1 時區統一遷移 (首席架構師審查)
|
||
"""
|
||
from src.utils.timezone import now_taipei
|
||
return now_taipei()
|
||
|
||
|
||
def generate_uuid() -> str:
|
||
"""Generate UUID string"""
|
||
return str(uuid4())
|
||
|
||
|
||
# =============================================================================
|
||
# ApprovalRecord - 授權記錄持久化
|
||
# =============================================================================
|
||
|
||
class ApprovalRecord(Base):
|
||
"""
|
||
授權記錄 - 對應 Pydantic ApprovalRequest
|
||
|
||
Note: 與 in-memory TrustEngine 的 ApprovalRequest 同步
|
||
"""
|
||
__tablename__ = "approval_records"
|
||
|
||
# Primary Key
|
||
id: Mapped[str] = mapped_column(
|
||
String(36),
|
||
primary_key=True,
|
||
default=generate_uuid,
|
||
)
|
||
|
||
# Core Fields
|
||
action: Mapped[str] = mapped_column(String(500), nullable=False)
|
||
description: Mapped[str] = mapped_column(Text, nullable=False)
|
||
status: Mapped[str] = mapped_column(
|
||
SQLEnum(ApprovalStatus),
|
||
default=ApprovalStatus.PENDING,
|
||
nullable=False,
|
||
)
|
||
risk_level: Mapped[str] = mapped_column(
|
||
SQLEnum(RiskLevel),
|
||
nullable=False,
|
||
)
|
||
|
||
# Signature Tracking
|
||
required_signatures: Mapped[int] = mapped_column(Integer, default=1)
|
||
current_signatures: Mapped[int] = mapped_column(Integer, default=0)
|
||
signatures: Mapped[dict[str, Any]] = mapped_column(JSON, default=list)
|
||
|
||
# Blast Radius (JSON)
|
||
blast_radius: Mapped[dict[str, Any]] = mapped_column(JSON, default=dict)
|
||
|
||
# Dry-Run Checks (JSON)
|
||
dry_run_checks: Mapped[list[dict[str, Any]]] = mapped_column(JSON, default=list)
|
||
|
||
# Metadata
|
||
requested_by: Mapped[str] = mapped_column(String(100), nullable=False)
|
||
rejection_reason: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
extra_metadata: Mapped[dict[str, Any] | None] = mapped_column(JSON, nullable=True)
|
||
|
||
# ==========================================================================
|
||
# 戰略 B: 告警風暴收斂 (Alert Storm Convergence)
|
||
# ==========================================================================
|
||
# 告警指紋 - 根據 namespace + deployment + alert_name 產生的唯一 Hash
|
||
fingerprint: Mapped[str | None] = mapped_column(
|
||
String(64),
|
||
nullable=True,
|
||
index=True,
|
||
comment="SHA256 hash of alert identity (namespace:deployment:alert_name)",
|
||
)
|
||
# 聚合次數 - 相同指紋告警的累計觸發次數
|
||
hit_count: Mapped[int] = mapped_column(
|
||
Integer,
|
||
default=1,
|
||
nullable=False,
|
||
comment="Number of times this alert pattern was triggered",
|
||
)
|
||
# 最後觸發時間 - 同指紋告警最近一次出現的時間
|
||
last_seen_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
nullable=False,
|
||
comment="Last time this alert pattern was seen",
|
||
)
|
||
|
||
# Sprint 5.1 MultiSig 雙簽核支援 (2026-04-08 Claude Sonnet 4.6 Asia/Taipei，ADR-062 Q3)
|
||
approval_level: Mapped[str] = mapped_column(
|
||
String(20),
|
||
default="standard",
|
||
nullable=False,
|
||
comment="standard=1票審核, critical=2票MultiSig",
|
||
)
|
||
approval_votes: Mapped[list[dict[str, Any]]] = mapped_column(
|
||
JSON,
|
||
default=list,
|
||
nullable=False,
|
||
comment="[{user_id, voted_at, action}]",
|
||
)
|
||
required_votes: Mapped[int] = mapped_column(
|
||
Integer,
|
||
default=1,
|
||
nullable=False,
|
||
comment="standard=1, critical=2",
|
||
)
|
||
|
||
# 2026-04-06 ogt: Phase 26 — 關聯 Incident ID
|
||
# Playbook 萃取和 KM 寫入必須知道 incident_id，不能靠文字解析
|
||
incident_id: Mapped[str | None] = mapped_column(
|
||
String(64),
|
||
nullable=True,
|
||
index=True,
|
||
comment="Associated Incident ID (INC-YYYYMMDD-XXXXXX)",
|
||
)
|
||
|
||
# 2026-04-09 Claude Sonnet 4.6: Telegram 訊息持久化
|
||
# Redis tg_msg:{id} TTL 24h 過期後仍可查詢，支援跨 Session 狀態更新
|
||
telegram_message_id: Mapped[int | None] = mapped_column(
|
||
Integer,
|
||
nullable=True,
|
||
comment="Telegram message_id of the approval card sent to operator",
|
||
)
|
||
telegram_chat_id: Mapped[int | None] = mapped_column(
|
||
Integer,
|
||
nullable=True,
|
||
comment="Telegram chat_id where the approval card was sent",
|
||
)
|
||
|
||
# Timestamps
|
||
created_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
)
|
||
updated_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
onupdate=taipei_now,
|
||
)
|
||
expires_at: Mapped[datetime | None] = mapped_column(
|
||
DateTime(timezone=True),
|
||
nullable=True,
|
||
)
|
||
resolved_at: Mapped[datetime | None] = mapped_column(
|
||
DateTime(timezone=True),
|
||
nullable=True,
|
||
)
|
||
|
||
# Indexes
|
||
__table_args__ = (
|
||
Index("ix_approval_status", "status"),
|
||
Index("ix_approval_risk_level", "risk_level"),
|
||
Index("ix_approval_created_at", "created_at"),
|
||
Index("ix_approval_requested_by", "requested_by"),
|
||
Index("ix_approval_fingerprint", "fingerprint"), # 戰略 B: 指紋查詢優化
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# AuditLog - 稽核日誌
|
||
# =============================================================================
|
||
|
||
class TimelineEvent(Base):
|
||
"""
|
||
時間軸事件 - Phase 4 Action Timeline
|
||
|
||
事件類型:
|
||
- system: 系統告警接收
|
||
- agent: OpenClaw AI 分析
|
||
- security: 權限阻擋
|
||
- human: 人類授權
|
||
- exec: 執行完成
|
||
"""
|
||
__tablename__ = "timeline_events"
|
||
|
||
# Primary Key
|
||
id: Mapped[str] = mapped_column(
|
||
String(36),
|
||
primary_key=True,
|
||
default=generate_uuid,
|
||
)
|
||
|
||
# Event Type & Status
|
||
event_type: Mapped[str] = mapped_column(
|
||
String(20),
|
||
nullable=False,
|
||
comment="system, agent, security, human, exec",
|
||
)
|
||
status: Mapped[str] = mapped_column(
|
||
String(20),
|
||
nullable=False,
|
||
default="info",
|
||
comment="info, success, warning, error",
|
||
)
|
||
|
||
# Content
|
||
title: Mapped[str] = mapped_column(String(500), nullable=False)
|
||
description: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
|
||
# Actor
|
||
actor: Mapped[str | None] = mapped_column(String(100), nullable=True)
|
||
actor_role: Mapped[str | None] = mapped_column(String(50), nullable=True)
|
||
|
||
# Context
|
||
risk_level: Mapped[str | None] = mapped_column(String(20), nullable=True)
|
||
approval_id: Mapped[str | None] = mapped_column(String(36), nullable=True, index=True)
|
||
|
||
# Timestamp
|
||
created_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
)
|
||
|
||
# Indexes
|
||
__table_args__ = (
|
||
Index("ix_timeline_event_type", "event_type"),
|
||
Index("ix_timeline_created_at", "created_at"),
|
||
)
|
||
|
||
|
||
class AuditLog(Base):
|
||
"""
|
||
稽核日誌 - 記錄所有執行結果
|
||
|
||
每次 K8s 操作完成後寫入一筆記錄
|
||
"""
|
||
__tablename__ = "audit_logs"
|
||
|
||
# Primary Key
|
||
id: Mapped[str] = mapped_column(
|
||
String(36),
|
||
primary_key=True,
|
||
default=generate_uuid,
|
||
)
|
||
|
||
# Reference to Approval
|
||
approval_id: Mapped[str] = mapped_column(
|
||
String(36),
|
||
nullable=False,
|
||
index=True,
|
||
)
|
||
|
||
# Operation Details
|
||
operation_type: Mapped[str] = mapped_column(
|
||
String(50),
|
||
nullable=False,
|
||
comment="e.g., RESTART_DEPLOYMENT, DELETE_POD",
|
||
)
|
||
target_resource: Mapped[str] = mapped_column(
|
||
String(200),
|
||
nullable=False,
|
||
comment="e.g., deployment/api-backend, pod/nginx-xxx",
|
||
)
|
||
namespace: Mapped[str] = mapped_column(
|
||
String(63),
|
||
default="default",
|
||
nullable=False,
|
||
)
|
||
|
||
# Execution Result
|
||
success: Mapped[bool] = mapped_column(default=False, nullable=False)
|
||
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
|
||
# K8s Response (Raw)
|
||
k8s_response: Mapped[dict[str, Any] | None] = mapped_column(
|
||
JSON,
|
||
nullable=True,
|
||
comment="Raw Kubernetes API response",
|
||
)
|
||
|
||
# Execution Context
|
||
executed_by: Mapped[str] = mapped_column(
|
||
String(100),
|
||
nullable=False,
|
||
comment="Who triggered the execution",
|
||
)
|
||
execution_duration_ms: Mapped[int | None] = mapped_column(
|
||
Integer,
|
||
nullable=True,
|
||
comment="Execution time in milliseconds",
|
||
)
|
||
|
||
# Dry-Run Result (pre-execution validation)
|
||
dry_run_passed: Mapped[bool] = mapped_column(
|
||
default=True,
|
||
nullable=False,
|
||
)
|
||
dry_run_message: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
|
||
# ==========================================================================
|
||
# Phase 18: 失敗自動修復閉環欄位 (2026-03-26)
|
||
# ==========================================================================
|
||
|
||
# 授權來源追蹤
|
||
authorization_channel: Mapped[str | None] = mapped_column(
|
||
String(20),
|
||
nullable=True,
|
||
comment="Authorization source: web, telegram, auto",
|
||
)
|
||
|
||
# 重試與修復追蹤
|
||
retry_count: Mapped[int] = mapped_column(
|
||
Integer,
|
||
default=0,
|
||
nullable=False,
|
||
comment="Number of retry attempts",
|
||
)
|
||
failure_classification: Mapped[str | None] = mapped_column(
|
||
String(50),
|
||
nullable=True,
|
||
comment="Failure type: TIMEOUT, K8S_ERROR, NETWORK_ERROR, PERMISSION_DENIED",
|
||
)
|
||
source_approval_id: Mapped[str | None] = mapped_column(
|
||
String(36),
|
||
nullable=True,
|
||
index=True,
|
||
comment="Original approval ID if this is a repair attempt",
|
||
)
|
||
|
||
# 自動修復狀態
|
||
auto_repair_attempted: Mapped[bool] = mapped_column(
|
||
default=False,
|
||
nullable=False,
|
||
comment="Whether auto-repair was attempted",
|
||
)
|
||
auto_repair_result: Mapped[str | None] = mapped_column(
|
||
Text,
|
||
nullable=True,
|
||
comment="Auto-repair result: AI analysis and repair outcome",
|
||
)
|
||
|
||
# Timestamps
|
||
created_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
)
|
||
|
||
# Indexes
|
||
__table_args__ = (
|
||
Index("ix_audit_approval_id", "approval_id"),
|
||
Index("ix_audit_operation_type", "operation_type"),
|
||
Index("ix_audit_success", "success"),
|
||
Index("ix_audit_created_at", "created_at"),
|
||
Index("ix_audit_authorization_channel", "authorization_channel"), # Phase 18
|
||
Index("ix_audit_failure_classification", "failure_classification"), # Phase 18
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# AutoRepairExecution - Phase 10 操作記錄
|
||
# 2026-04-08 Claude Code: 統帥指令「所有操作都必須被記錄，寫入資料庫」
|
||
# =============================================================================
|
||
|
||
class AutoRepairExecution(Base):
|
||
"""
|
||
自動修復執行記錄
|
||
|
||
每次 evaluate_auto_repair 觸發並執行 (成功或失敗) 都寫入此表。
|
||
不依賴 approval_id（自動修復不需人工批准）。
|
||
"""
|
||
__tablename__ = "auto_repair_executions"
|
||
|
||
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=generate_uuid)
|
||
|
||
# 關聯
|
||
incident_id: Mapped[str] = mapped_column(String(30), nullable=False, index=True)
|
||
playbook_id: Mapped[str] = mapped_column(String(36), nullable=False, index=True)
|
||
playbook_name: Mapped[str] = mapped_column(String(200), nullable=False)
|
||
|
||
# 執行結果
|
||
success: Mapped[bool] = mapped_column(default=False, nullable=False)
|
||
executed_steps: Mapped[list] = mapped_column(JSON, default=list, nullable=False)
|
||
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
|
||
# 執行上下文
|
||
triggered_by: Mapped[str] = mapped_column(
|
||
String(50), default="auto_repair", nullable=False,
|
||
comment="auto_repair / cold_start_trust",
|
||
)
|
||
similarity_score: Mapped[float | None] = mapped_column(nullable=True)
|
||
risk_level: Mapped[str | None] = mapped_column(String(20), nullable=True)
|
||
execution_time_ms: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
|
||
# 時間戳 (台北時區)
|
||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now)
|
||
|
||
__table_args__ = (
|
||
Index("ix_are_created_at", "created_at"),
|
||
Index("ix_are_success", "success"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# AlertOperationLog - Phase 11 告警操作溯源 (Event Sourcing)
|
||
# 2026-04-08 Claude Code: 統帥指令「所有操作都必須被記錄，寫入資料庫」
|
||
# 不可變 — 只 INSERT，不 UPDATE/DELETE
|
||
# =============================================================================
|
||
|
||
class AlertOperationLog(Base):
|
||
"""
|
||
告警操作完整溯源
|
||
|
||
Event Sourcing 模式：每個告警生命週期的每個事件都寫一筆。
|
||
不可變 (Immutable)。
|
||
|
||
event_type 值：
|
||
ALERT_RECEIVED / TELEGRAM_SENT / USER_ACTION /
|
||
AUTO_REPAIR_TRIGGERED / EXECUTION_STARTED / EXECUTION_COMPLETED /
|
||
TELEGRAM_RESULT_SENT / RESOLVED / SILENCED / ESCALATED
|
||
"""
|
||
__tablename__ = "alert_operation_log"
|
||
|
||
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=generate_uuid)
|
||
|
||
# 關聯 (允許 NULL，不同事件有不同關聯)
|
||
incident_id: Mapped[str | None] = mapped_column(String(30), nullable=True, index=True)
|
||
approval_id: Mapped[str | None] = mapped_column(String(36), nullable=True, index=True)
|
||
audit_log_id: Mapped[str | None] = mapped_column(String(36), nullable=True)
|
||
auto_repair_id: Mapped[str | None] = mapped_column(String(36), nullable=True)
|
||
|
||
# 事件核心
|
||
# 2026-04-08 Claude Sonnet 4.6: Sprint 5.1 — 修正 enum 型別不符 (String→PgEnum, create_type=False)
|
||
event_type: Mapped[str] = mapped_column(
|
||
PgEnum(
|
||
"ALERT_RECEIVED", "TELEGRAM_SENT", "USER_ACTION", "AUTO_REPAIR_TRIGGERED",
|
||
"EXECUTION_STARTED", "EXECUTION_COMPLETED", "TELEGRAM_RESULT_SENT",
|
||
"RESOLVED", "SILENCED", "ESCALATED", "GUARDRAIL_BLOCKED",
|
||
"PRE_FLIGHT_PASSED", "PRE_FLIGHT_FAILED", "BACKUP_TRIGGERED",
|
||
"BACKUP_COMPLETED", "BACKUP_FAILED", "APPROVAL_ESCALATED", "CHANGE_APPLIED",
|
||
name="alert_event_type", create_type=False,
|
||
),
|
||
nullable=False, index=True,
|
||
)
|
||
actor: Mapped[str | None] = mapped_column(String(100), nullable=True, index=True)
|
||
action_detail: Mapped[str | None] = mapped_column(String(200), nullable=True)
|
||
|
||
# 執行結果 (NULL = 不適用)
|
||
success: Mapped[bool | None] = mapped_column(nullable=True)
|
||
error_message: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
|
||
# 結構化上下文
|
||
context: Mapped[dict] = mapped_column(JSON, default=dict, nullable=False)
|
||
|
||
# 時間戳 (台北時區，不可變)
|
||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now)
|
||
|
||
__table_args__ = (
|
||
Index("ix_aol_created_at", "created_at"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# IncidentRecord - Phase 6.2 Episodic Memory (PostgreSQL)
|
||
# =============================================================================
|
||
|
||
class IncidentRecord(Base):
|
||
"""
|
||
事件記錄 - 對應 Pydantic Incident Schema v0.3
|
||
|
||
Phase 6.2: Episodic Memory (長期記憶)
|
||
- 從 Working Memory (Redis) 遷移過來
|
||
- 永久保留，供 RAG 檢索
|
||
- 複雜結構使用 JSONB 欄位
|
||
|
||
三層記憶架構:
|
||
- Working Memory (Redis): 7 天 TTL
|
||
- Episodic Memory (PostgreSQL): 此表，永久保留
|
||
- Semantic Memory (Vector DB): Phase 6.3+
|
||
"""
|
||
__tablename__ = "incidents"
|
||
|
||
# === 主鍵 ===
|
||
incident_id: Mapped[str] = mapped_column(
|
||
String(30),
|
||
primary_key=True,
|
||
comment="事件唯一識別碼 (如 INC-20260322-A1B2C3)",
|
||
)
|
||
|
||
# === 狀態與嚴重度 ===
|
||
status: Mapped[str] = mapped_column(
|
||
SQLEnum(IncidentStatus),
|
||
default=IncidentStatus.INVESTIGATING,
|
||
nullable=False,
|
||
comment="事件狀態 (investigating, mitigating, resolved, closed, escalated)",
|
||
)
|
||
severity: Mapped[str] = mapped_column(
|
||
SQLEnum(Severity),
|
||
nullable=False,
|
||
comment="事件嚴重度 (P0, P1, P2, P3)",
|
||
)
|
||
|
||
# === 感知層 (Signals) - JSONB ===
|
||
signals: Mapped[list[dict[str, Any]]] = mapped_column(
|
||
JSON,
|
||
default=list,
|
||
nullable=False,
|
||
comment="關聯的告警信號列表 (JSONB)",
|
||
)
|
||
affected_services: Mapped[list[str]] = mapped_column(
|
||
JSON,
|
||
default=list,
|
||
nullable=False,
|
||
comment="受影響的服務列表",
|
||
)
|
||
|
||
# === 認知層 (AI Decision Chain) - JSONB ===
|
||
decision_chain: Mapped[dict[str, Any] | None] = mapped_column(
|
||
JSON,
|
||
nullable=True,
|
||
comment="AI 決策鏈 (完整推論過程)",
|
||
)
|
||
|
||
# === 決策層 (Proposals) ===
|
||
proposal_ids: Mapped[list[str]] = mapped_column(
|
||
JSON,
|
||
default=list,
|
||
nullable=False,
|
||
comment="關聯的 ApprovalRequest ID 列表",
|
||
)
|
||
|
||
# === 結果層 (Outcome) - JSONB ===
|
||
outcome: Mapped[dict[str, Any] | None] = mapped_column(
|
||
JSON,
|
||
nullable=True,
|
||
comment="事件結果與人類回饋",
|
||
)
|
||
|
||
# === ADR-073 Phase 2 欄位 (2026-04-12 ogt) ===
|
||
alertname: Mapped[str | None] = mapped_column(
|
||
String(100),
|
||
nullable=True,
|
||
comment="告警名稱 (從 signals labels 抽取)",
|
||
)
|
||
notification_type: Mapped[str | None] = mapped_column(
|
||
String(10),
|
||
nullable=True,
|
||
comment="通知類型 TYPE-1/2/3/4/4D (早期分診)",
|
||
)
|
||
alert_category: Mapped[str | None] = mapped_column(
|
||
String(50),
|
||
nullable=True,
|
||
comment="告警類別 config_drift/info/backup/infrastructure/kubernetes/database/general",
|
||
)
|
||
|
||
# === 頻率快照 (Phase 27, 2026-04-10 ogt) ===
|
||
# frequency_stats 原本只存記憶體/Redis(TTL=35天)，Pod重啟或超期即失
|
||
# 此欄位在 incident 建立時寫入快照，永久保存當時的頻率統計
|
||
frequency_snapshot: Mapped[dict[str, Any] | None] = mapped_column(
|
||
JSON,
|
||
nullable=True,
|
||
comment="建立時刻的 AnomalyFrequency 快照，永久保存 (Phase 27)",
|
||
)
|
||
|
||
# === 時間軸 ===
|
||
created_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
nullable=False,
|
||
)
|
||
updated_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
onupdate=taipei_now,
|
||
nullable=False,
|
||
)
|
||
resolved_at: Mapped[datetime | None] = mapped_column(
|
||
DateTime(timezone=True),
|
||
nullable=True,
|
||
)
|
||
closed_at: Mapped[datetime | None] = mapped_column(
|
||
DateTime(timezone=True),
|
||
nullable=True,
|
||
)
|
||
|
||
# === 記憶管理 ===
|
||
ttl_days: Mapped[int] = mapped_column(
|
||
Integer,
|
||
default=7,
|
||
nullable=False,
|
||
comment="Working Memory TTL (天)",
|
||
)
|
||
vectorized: Mapped[bool] = mapped_column(
|
||
default=False,
|
||
nullable=False,
|
||
comment="是否已向量化到 Vector DB (Semantic Memory)",
|
||
)
|
||
|
||
# === 索引 ===
|
||
__table_args__ = (
|
||
Index("ix_incident_status", "status"),
|
||
Index("ix_incident_severity", "severity"),
|
||
Index("ix_incident_created_at", "created_at"),
|
||
Index("ix_incident_resolved_at", "resolved_at"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# KnowledgeEntry - Knowledge Base Phase 1
|
||
# =============================================================================
|
||
|
||
class KnowledgeEntryRecord(Base):
|
||
"""
|
||
知識庫條目 - Knowledge Base Phase 1
|
||
|
||
兩層架構:
|
||
- KnowledgeEntry: 知識條目 (此表)
|
||
- Playbook: 獨立 Redis，透過 related_playbook_id 關聯
|
||
|
||
建立時間: 2026-04-02 (台北時區)
|
||
建立者: Claude Code (Knowledge Base Phase 1)
|
||
"""
|
||
__tablename__ = "knowledge_entries"
|
||
|
||
# Primary Key
|
||
id: Mapped[str] = mapped_column(
|
||
String(36),
|
||
primary_key=True,
|
||
default=generate_uuid,
|
||
)
|
||
|
||
# Core Fields
|
||
title: Mapped[str] = mapped_column(String(255), nullable=False)
|
||
content: Mapped[str] = mapped_column(Text, nullable=False)
|
||
entry_type: Mapped[str] = mapped_column(
|
||
SQLEnum(EntryType),
|
||
nullable=False,
|
||
comment="incident_case / runbook / best_practice / postmortem",
|
||
)
|
||
category: Mapped[str] = mapped_column(
|
||
String(100),
|
||
nullable=False,
|
||
comment="分類樹節點 (基礎設施/應用層/AI系統/安全合規)",
|
||
)
|
||
tags: Mapped[list[str]] = mapped_column(
|
||
JSON,
|
||
default=list,
|
||
nullable=False,
|
||
comment="標籤列表 (JSONB string array)",
|
||
)
|
||
|
||
# Source & Status
|
||
source: Mapped[str] = mapped_column(
|
||
SQLEnum(EntrySource),
|
||
nullable=False,
|
||
comment="ai_extracted / human",
|
||
)
|
||
status: Mapped[str] = mapped_column(
|
||
SQLEnum(EntryStatus),
|
||
default=EntryStatus.DRAFT,
|
||
nullable=False,
|
||
comment="draft / review / approved / archived",
|
||
)
|
||
|
||
# Relations (soft references, not FK)
|
||
related_incident_id: Mapped[str | None] = mapped_column(
|
||
String(30),
|
||
nullable=True,
|
||
comment="關聯 Incident ID",
|
||
)
|
||
related_playbook_id: Mapped[str | None] = mapped_column(
|
||
String(255),
|
||
nullable=True,
|
||
comment="關聯 Playbook Redis Key",
|
||
)
|
||
# 2026-04-04 ogt: Phase 25 P1 — Anti-Pattern 閉環攔截用症狀 hash (SymptomPattern.compute_hash())
|
||
symptoms_hash: Mapped[str | None] = mapped_column(
|
||
String(16),
|
||
nullable=True,
|
||
comment="症狀模式 hash (16字元 SHA256 前綴)，Anti-Pattern 閉環攔截使用",
|
||
)
|
||
|
||
# Metrics
|
||
view_count: Mapped[int] = mapped_column(
|
||
Integer,
|
||
default=0,
|
||
nullable=False,
|
||
)
|
||
|
||
# Metadata
|
||
created_by: Mapped[str | None] = mapped_column(String(100), nullable=True)
|
||
created_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
)
|
||
updated_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True),
|
||
default=taipei_now,
|
||
onupdate=taipei_now,
|
||
)
|
||
|
||
# Indexes
|
||
__table_args__ = (
|
||
Index("ix_knowledge_entry_type", "entry_type"),
|
||
Index("ix_knowledge_category", "category"),
|
||
Index("ix_knowledge_status", "status"),
|
||
Index("ix_knowledge_created_at", "created_at"),
|
||
# 2026-04-04 ogt: Phase 25 P1 — Anti-Pattern 快速查詢
|
||
Index("ix_knowledge_symptoms_hash", "symptoms_hash"),
|
||
)
|
||
|
||
|
||
# IncidentEvidence — ADR-081 Phase 1 EvidenceSnapshot 持久化
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6: AI 自主化飛輪 Phase 1 初始建立
|
||
class IncidentEvidence(Base):
|
||
"""
|
||
不可變事件證據快照表
|
||
|
||
每次決策前 PreDecisionInvestigator 拍攝一次 EvidenceSnapshot，
|
||
寫入此表以供：
|
||
- 決策溯源（LLM 推理過程的完整情報上下文）
|
||
- 學習訓練（Phase 3 fine-tune pipeline 金礦資料）
|
||
- 異常驗證（執行前 vs 執行後 state diff）
|
||
|
||
ADR-081: PreDecisionInvestigator + EvidenceSnapshot
|
||
設計原則：只追加寫入，禁止 UPDATE（event sourcing 對齊）
|
||
"""
|
||
__tablename__ = "incident_evidence"
|
||
|
||
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=generate_uuid)
|
||
|
||
# 關聯
|
||
incident_id: Mapped[str] = mapped_column(String(30), nullable=False, index=True)
|
||
# Phase 3 填充：matched_playbook_id 目前永久 null，Phase 3 修復
|
||
matched_playbook_id: Mapped[str | None] = mapped_column(String(36), nullable=True)
|
||
|
||
# Schema 版本（方便 fine-tune pipeline 過濾相容版本）
|
||
schema_version: Mapped[str] = mapped_column(String(10), default="v1", nullable=False)
|
||
|
||
# 8D 感官數據（各維度 nullable — MCP 失敗時部分缺失）
|
||
k8s_state: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="D1: kubectl describe pod + events"
|
||
)
|
||
recent_logs: Mapped[str | None] = mapped_column(
|
||
Text, nullable=True, comment="D2: container stderr tail-50，經 SanitizationService 清洗"
|
||
)
|
||
metrics_snapshot: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="D3: Prometheus 5min vs 1h baseline 對比"
|
||
)
|
||
recent_deployments: Mapped[list | None] = mapped_column(
|
||
JSON, nullable=True, comment="D4: ArgoCD/Gitea 過去 1h 部署 diff"
|
||
)
|
||
business_metrics: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="D5: 訂單量 / 登入成功率 / P0 SLI"
|
||
)
|
||
historical_context: Mapped[str | None] = mapped_column(
|
||
Text, nullable=True, comment="D6: 過去 30 天同 alertname 處置歷史摘要"
|
||
)
|
||
peer_health: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="D7: 同 Deployment 其他 replica 健康度"
|
||
)
|
||
dependency_topology: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="D8: Istio/Service Mesh 上下游 latency/error rate"
|
||
)
|
||
|
||
# 感官品質指標
|
||
mcp_health: Mapped[dict] = mapped_column(
|
||
JSON, default=dict, nullable=False,
|
||
comment="各 MCP 呼叫成敗 {tool_name: bool}，用於 decision_fusion 權重調整"
|
||
)
|
||
collection_duration_ms: Mapped[int | None] = mapped_column(
|
||
Integer, nullable=True, comment="情報蒐集總耗時（ms），P99 目標 < 8000"
|
||
)
|
||
sensors_attempted: Mapped[int] = mapped_column(
|
||
default=0, nullable=False, comment="嘗試啟動的感官數"
|
||
)
|
||
sensors_succeeded: Mapped[int] = mapped_column(
|
||
default=0, nullable=False, comment="成功回傳資料的感官數"
|
||
)
|
||
|
||
# LLM 輸入摘要（不超 8K tokens，由 Investigator 壓縮）
|
||
evidence_summary: Mapped[str | None] = mapped_column(
|
||
Text, nullable=True, comment="最終餵給 LLM 的情報摘要（UTF-8，< 8K tokens）"
|
||
)
|
||
|
||
# 執行前後 State（PostExecutionVerifier 填入 post_execution_state）
|
||
pre_execution_state: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="執行前環境狀態快照（PostExecutionVerifier 基準線）"
|
||
)
|
||
post_execution_state: Mapped[dict | None] = mapped_column(
|
||
JSON, nullable=True, comment="執行後環境狀態（PostExecutionVerifier 抓取，Phase 1 接線）"
|
||
)
|
||
verification_result: Mapped[str | None] = mapped_column(
|
||
String(20), nullable=True, comment="success / degraded / failed / timeout（PostExecutionVerifier 填入）"
|
||
)
|
||
|
||
# 時間戳（台北時區）
|
||
collected_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True), default=taipei_now, nullable=False
|
||
)
|
||
|
||
__table_args__ = (
|
||
Index("ix_incident_evidence_incident_id", "incident_id"),
|
||
Index("ix_incident_evidence_collected_at", "collected_at"),
|
||
Index("ix_incident_evidence_playbook_id", "matched_playbook_id"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# PlaybookRecord — Phase 3.5 Playbook PostgreSQL 持久化 (System of Record)
|
||
# ADR-085: AI 學習成果不可存在 Cache — Playbook 是 AI 的肌肉記憶
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 3.5 初始建立
|
||
#
|
||
# 核心鐵律：
|
||
# - PostgreSQL = System of Record（永久保存，AI 的長期記憶）
|
||
# - Redis = Warm Cache（7天 TTL，加速讀取，DB 為 source of truth）
|
||
# - trust_score, EWMA, 統計數據必須持久化 — 不能因 Redis TTL 消失
|
||
# =============================================================================
|
||
|
||
class PlaybookRecord(Base):
|
||
"""
|
||
Playbook 修復劇本 PostgreSQL ORM
|
||
|
||
與 Pydantic Playbook 模型對應。
|
||
Redis 為 warm cache（7d TTL），PostgreSQL 為 source of truth。
|
||
|
||
設計原則：
|
||
- AI 的學習成果（trust_score、success_count、failure_count）永久保存
|
||
- EWMA 信任度在 Redis TTL 後不會重置，Pod 重啟後 AI 記憶不失
|
||
- 雙寫：create/update 先寫 PG，再更新 Redis cache
|
||
- 讀取：Redis-first（cache hit），miss 時從 PG 載入並回填 Redis
|
||
"""
|
||
__tablename__ = "playbooks"
|
||
|
||
# Primary Key
|
||
playbook_id: Mapped[str] = mapped_column(
|
||
String(36), primary_key=True,
|
||
comment="Playbook 唯一識別碼 (PB-YYYYMMDD-XXXXXX)",
|
||
)
|
||
|
||
# Core Fields
|
||
name: Mapped[str] = mapped_column(String(256), nullable=False)
|
||
description: Mapped[str] = mapped_column(Text, default="", nullable=False)
|
||
status: Mapped[str] = mapped_column(String(20), default="draft", nullable=False)
|
||
source: Mapped[str] = mapped_column(String(20), default="extracted", nullable=False)
|
||
|
||
# Complex structures (JSONB)
|
||
symptom_pattern: Mapped[dict[str, Any]] = mapped_column(JSON, default=dict, nullable=False)
|
||
repair_steps: Mapped[list[dict[str, Any]]] = mapped_column(JSON, default=list, nullable=False)
|
||
|
||
# Timing
|
||
estimated_duration_minutes: Mapped[int] = mapped_column(Integer, default=5, nullable=False)
|
||
|
||
# Source tracing
|
||
source_incident_ids: Mapped[list[str]] = mapped_column(JSON, default=list, nullable=False)
|
||
ai_confidence: Mapped[float] = mapped_column(default=0.0, nullable=False)
|
||
|
||
# Stats — MUST be in PG (AI learning artifacts, cannot expire)
|
||
success_count: Mapped[int] = mapped_column(Integer, default=0, nullable=False)
|
||
failure_count: Mapped[int] = mapped_column(Integer, default=0, nullable=False)
|
||
last_used_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
|
||
|
||
# EWMA trust score — ADR-083 Phase 3, 絕對不能用 Redis TTL 管理
|
||
# trust_score 是 AI 累積學習的結晶，TTL 到期就歸零 = AI 記憶全部消失
|
||
trust_score: Mapped[float] = mapped_column(default=0.3, nullable=False,
|
||
comment="EWMA 動態信任度 (Phase 3)。成功 α=0.1，失敗 α=0.2（2x 衰減）。< 0.1 → 封存")
|
||
|
||
# Approval metadata
|
||
approved_by: Mapped[str | None] = mapped_column(String(100), nullable=True)
|
||
approved_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
|
||
tags: Mapped[list[str]] = mapped_column(JSON, default=list, nullable=False)
|
||
notes: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
|
||
# Sprint 5.1 護欄欄位 (2026-04-08)
|
||
requires_approval_level: Mapped[str] = mapped_column(
|
||
String(20), default="auto", nullable=False,
|
||
comment="auto=直接執行, standard=1票, critical=2票MultiSig",
|
||
)
|
||
stateful_targets: Mapped[list[str]] = mapped_column(JSON, default=list, nullable=False)
|
||
requires_pre_backup: Mapped[bool] = mapped_column(default=False, nullable=False)
|
||
|
||
# Timestamps
|
||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now, nullable=False)
|
||
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now,
|
||
onupdate=taipei_now, nullable=False)
|
||
|
||
__table_args__ = (
|
||
Index("ix_playbook_status", "status"),
|
||
Index("ix_playbook_trust_score", "trust_score"),
|
||
Index("ix_playbook_created_at", "created_at"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# DynamicBaselineRecord — Phase 4 Holt-Winters 訓練基線持久化
|
||
# ADR-084: 動態基線不能只存 Redis — AI 每天重學「正常」不是在學習
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 4 初始建立
|
||
#
|
||
# 核心鐵律：
|
||
# - 訓練好的 Holt-Winters 模型必須在 PG 長期保存
|
||
# - Redis 為 24h warm cache（加速 is_anomaly() 讀取）
|
||
# - 基線消失 = AI 對「正常」的認識消失 = 每天從頭學習 = 不是 AI
|
||
# =============================================================================
|
||
|
||
class DynamicBaselineRecord(Base):
|
||
"""
|
||
動態基線訓練結果 PostgreSQL ORM
|
||
|
||
Holt-Winters 訓練完成後：
|
||
1. 先寫入 PG（永久保存）
|
||
2. 再寫入 Redis（24h warm cache，加速讀取）
|
||
|
||
Redis key: baseline:{metric_name}
|
||
PG: 此表，metric_name 為主鍵，最新一筆 = 有效基線
|
||
"""
|
||
__tablename__ = "dynamic_baselines"
|
||
|
||
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=generate_uuid)
|
||
|
||
# 基線識別
|
||
metric_name: Mapped[str] = mapped_column(
|
||
String(200), nullable=False, index=True,
|
||
comment="基線識別名 (e.g. cpu_usage_node_mon)",
|
||
)
|
||
|
||
# 訓練結果（Holt-Winters 統計）
|
||
mean: Mapped[float] = mapped_column(nullable=False, comment="擬合值均值")
|
||
std: Mapped[float] = mapped_column(nullable=False, comment="殘差標準差")
|
||
|
||
# 24h 季節性因子（JSON 陣列，長度 24）
|
||
seasonal_factors: Mapped[list[float]] = mapped_column(
|
||
JSON, default=list, nullable=False,
|
||
comment="24h 週期季節性因子（乘法形式，均值 ≈ 1.0）",
|
||
)
|
||
|
||
# 訓練元資料
|
||
datapoint_count: Mapped[int] = mapped_column(Integer, default=0, nullable=False)
|
||
promql: Mapped[str] = mapped_column(Text, default="", nullable=False,
|
||
comment="訓練使用的 PromQL 查詢")
|
||
lookback_hours: Mapped[int] = mapped_column(Integer, default=336, nullable=False)
|
||
|
||
# Timestamps
|
||
trained_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now, nullable=False)
|
||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now, nullable=False)
|
||
|
||
__table_args__ = (
|
||
Index("ix_dynamic_baseline_metric", "metric_name"),
|
||
Index("ix_dynamic_baseline_trained_at", "trained_at"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# LogClusterRecord — Phase 4 Drain3 學習到的 Log Pattern 持久化
|
||
# ADR-084: Drain3 模板不能只存 Redis — 每次重啟 AI 把已知 pattern 當新 pattern
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 4 初始建立
|
||
#
|
||
# 核心鐵律：
|
||
# - Drain3 學到的 log cluster template 必須在 PG 長期保存
|
||
# - 新 cluster 事件列表 (log_anomaly:new) 才存 Redis（短期工作記憶）
|
||
# - 基礎知識庫（已學到的 pattern）必須在 PG
|
||
# =============================================================================
|
||
|
||
class LogClusterRecord(Base):
|
||
"""
|
||
Drain3 Log Cluster Template 持久化
|
||
|
||
每個新 pattern 首次偵測到時：
|
||
1. 寫入 PG（永久保存，AI 的 log 語意理解）
|
||
2. 推送到 Redis list log_anomaly:new（短期工作記憶）
|
||
|
||
Re-detect 相同 template 時只更新 last_seen_at + size，不重複寫入 PG。
|
||
"""
|
||
__tablename__ = "log_clusters"
|
||
|
||
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=generate_uuid)
|
||
|
||
# Cluster 識別（MD5[:8] of template）
|
||
cluster_id: Mapped[str] = mapped_column(
|
||
String(16), nullable=False, unique=True, index=True,
|
||
comment="模板 MD5[:8].upper()，穩定 ID",
|
||
)
|
||
|
||
# Drain3 模板
|
||
template: Mapped[str] = mapped_column(
|
||
Text, nullable=False,
|
||
comment="Drain3 萃取的 log 模板 (e.g. 'ERROR <*> connection failed to <*>')",
|
||
)
|
||
|
||
# 統計
|
||
size: Mapped[int] = mapped_column(Integer, default=1, nullable=False,
|
||
comment="命中次數（第一次 = 1）")
|
||
source: Mapped[str] = mapped_column(String(50), default="k8s_pod", nullable=False,
|
||
comment="k8s_pod | host_syslog | app_log")
|
||
|
||
# 樣本日誌（保留首次觸發的原始行，供事後分析）
|
||
sample_log: Mapped[str | None] = mapped_column(Text, nullable=True,
|
||
comment="首次觸發的原始 log 行（前 500 字元）")
|
||
|
||
# Timestamps
|
||
first_seen_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now, nullable=False)
|
||
last_seen_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=taipei_now,
|
||
onupdate=taipei_now, nullable=False)
|
||
|
||
__table_args__ = (
|
||
Index("ix_log_cluster_first_seen", "first_seen_at"),
|
||
Index("ix_log_cluster_source", "source"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# AgentSession — Phase 2 多 Agent 辯證 Audit Trail
|
||
# =============================================================================
|
||
|
||
class AgentSession(Base):
|
||
"""
|
||
ADR-082 Phase 2: 多 Agent 辯證 Immutable Event Log
|
||
|
||
每個 Agent 每次「發言」寫一行。
|
||
session_id 串連同一次 Incident 決策的所有 Agent turns。
|
||
|
||
不可刪除 — 只能新增（Immutable Event Sourcing）。
|
||
Phase 3 學習閉環依賴此表（Critic 挑戰成功作為負向學習信號）。
|
||
|
||
ADR-082: 多 Agent 協作架構
|
||
2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 2 初始建立
|
||
"""
|
||
__tablename__ = "agent_sessions"
|
||
|
||
id: Mapped[str] = mapped_column(
|
||
String(36), primary_key=True, default=lambda: str(uuid4()),
|
||
comment="行主鍵（UUID）"
|
||
)
|
||
session_id: Mapped[str] = mapped_column(
|
||
String(36), nullable=False,
|
||
comment="辯證 Session ID（一次 Incident 決策的所有 turns 共用同一 session_id）"
|
||
)
|
||
incident_id: Mapped[str] = mapped_column(
|
||
String(50), nullable=False,
|
||
comment="關聯 Incident ID"
|
||
)
|
||
agent_role: Mapped[str] = mapped_column(
|
||
String(20), nullable=False,
|
||
comment="Agent 角色：diagnostician / solver / reviewer / critic / coordinator"
|
||
)
|
||
|
||
# 輸入指紋（sha256[:16]）— 用於查重、快取命中追蹤
|
||
input_hash: Mapped[str] = mapped_column(
|
||
String(16), nullable=False, default="",
|
||
comment="sha256(input_json)[:16]，供查重與快取命中追蹤"
|
||
)
|
||
|
||
# Agent 輸出（完整 JSON，供 Phase 3 學習 + 事後複盤）
|
||
output_json: Mapped[dict] = mapped_column(
|
||
JSON, nullable=False, default=dict,
|
||
comment="Agent 原始輸出（DiagnosisReport / ActionPlan / 等序列化 dict）"
|
||
)
|
||
|
||
# 品質指標
|
||
latency_ms: Mapped[int] = mapped_column(
|
||
Integer, nullable=False, default=0,
|
||
comment="此 Agent 的執行耗時（ms）"
|
||
)
|
||
vote: Mapped[str] = mapped_column(
|
||
String(20), nullable=False, default="abstain",
|
||
comment="Agent 投票：approve / reject / request_revision / abstain / degraded"
|
||
)
|
||
degraded: Mapped[bool] = mapped_column(
|
||
nullable=False, default=False,
|
||
comment="True = 此 Agent 因熔斷/超時降級，輸出為 rule-based mock"
|
||
)
|
||
|
||
# 時間戳（台北時區）
|
||
created_at: Mapped[datetime] = mapped_column(
|
||
DateTime(timezone=True), default=taipei_now, nullable=False
|
||
)
|
||
|
||
__table_args__ = (
|
||
Index("ix_agent_sessions_session_id", "session_id"),
|
||
Index("ix_agent_sessions_incident_id", "incident_id"),
|
||
Index("ix_agent_sessions_created_at", "created_at"),
|
||
# 查詢某 session 中特定 role 的 turn（Coordinator 聚合時常用）
|
||
Index("ix_agent_sessions_session_role", "session_id", "agent_role"),
|
||
)
|