feat(api): Knowledge Base Phase 1 後端四層架構

- models/knowledge.py: Pydantic Schema (EntryType/Source/Status/CRUD)
- db/models.py: KnowledgeEntryRecord ORM (PostgreSQL)
- repositories/interfaces.py: IKnowledgeRepository Protocol
- repositories/knowledge_repository.py: PostgreSQL CRUD 實作
- services/knowledge_service.py: 業務邏輯 (get_db_context 內部管理 session)
- api/v1/knowledge.py: REST Router (get_knowledge_service，無直接 DB 存取)
- main.py: 掛載 Knowledge Base Router
- k8s/jobs/migrate-knowledge-entries.yaml: DB Migration Job

API 端點: GET/POST / | GET/PATCH/DELETE /{id} | POST /{id}/approve
         GET /search | GET /categories

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

apps/api/src/models/knowledge.py

@@ -0,0 +1,109 @@
+"""
+Knowledge Base Models
+=====================
+Phase KB-1: 知識庫資料模型
+
+兩層架構:
+- KnowledgeEntry: 知識條目 (incident_case / runbook / best_practice / postmortem)
+- Playbook: 獨立系統，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)
+
+遵循 leWOOOgo 積木化原則:
+- Pydantic BaseModel 定義
+- PostgreSQL Episodic Memory
+"""
+
+from datetime import datetime
+from enum import Enum
+
+from pydantic import BaseModel, Field
+
+from src.utils.timezone import now_taipei
+
+
+# =============================================================================
+# Enums
+# =============================================================================
+
+class EntryType(str, Enum):
+    """知識條目類型"""
+    INCIDENT_CASE = "incident_case"      # AI 從 Incident 萃取的案例分析
+    RUNBOOK = "runbook"                  # 手動建立的操作手冊
+    BEST_PRACTICE = "best_practice"      # 最佳實踐文章
+    POSTMORTEM = "postmortem"            # 事後分析報告
+
+
+class EntrySource(str, Enum):
+    """知識來源"""
+    AI_EXTRACTED = "ai_extracted"        # AI 自動萃取
+    HUMAN = "human"                      # 人工建立
+
+
+class EntryStatus(str, Enum):
+    """知識條目狀態"""
+    DRAFT = "draft"                      # 草稿
+    REVIEW = "review"                    # 審核中
+    APPROVED = "approved"                # 已批准
+    ARCHIVED = "archived"                # 已封存
+
+
+# =============================================================================
+# Pydantic Models
+# =============================================================================
+
+class KnowledgeEntryCreate(BaseModel):
+    """建立知識條目 Request"""
+    title: str = Field(..., min_length=1, max_length=255)
+    content: str = Field(..., min_length=1)
+    entry_type: EntryType
+    category: str = Field(..., min_length=1, max_length=100)
+    tags: list[str] = Field(default_factory=list)
+    source: EntrySource = EntrySource.HUMAN
+    related_incident_id: str | None = None
+    related_playbook_id: str | None = None
+    created_by: str | None = None
+
+
+class KnowledgeEntryUpdate(BaseModel):
+    """更新知識條目 Request"""
+    title: str | None = None
+    content: str | None = None
+    entry_type: EntryType | None = None
+    category: str | None = None
+    tags: list[str] | None = None
+    status: EntryStatus | None = None
+
+
+class KnowledgeEntry(BaseModel):
+    """知識條目完整模型"""
+    id: str
+    title: str
+    content: str
+    entry_type: EntryType
+    category: str
+    tags: list[str] = Field(default_factory=list)
+    source: EntrySource
+    status: EntryStatus = EntryStatus.DRAFT
+    related_incident_id: str | None = None
+    related_playbook_id: str | None = None
+    view_count: int = 0
+    created_by: str | None = None
+    created_at: datetime = Field(default_factory=now_taipei)
+    updated_at: datetime = Field(default_factory=now_taipei)
+
+    model_config = {"from_attributes": True}
+
+
+class CategoryCount(BaseModel):
+    """分類統計"""
+    category: str
+    count: int
+
+
+class KnowledgeListResponse(BaseModel):
+    """列表回應"""
+    items: list[KnowledgeEntry]
+    total: int
+    categories: list[CategoryCount] = Field(default_factory=list)