# Design Document: 知识库租户分组展示 (knowledge-tenant-view) ## Overview 本设计将知识库管理页面从扁平列表改造为两层结构:第一层按 `tenant_id` 分组展示租户汇总卡片,第二层展示某租户下的知识条目列表。改造涉及三个层面: 1. **后端 API 层** — 在 `knowledge_bp` 中新增租户汇总端点 `/api/knowledge/tenants`,并为现有 `/api/knowledge` 和 `/api/knowledge/stats` 端点增加 `tenant_id` 查询参数支持。 2. **业务逻辑层** — 在 `KnowledgeManager` 中新增 `get_tenant_summary()` 方法,并为 `get_knowledge_paginated()`、`search_knowledge()`、`get_knowledge_stats()` 方法增加 `tenant_id` 过滤参数。`add_knowledge_entry()` 方法也需接受 `tenant_id` 参数。 3. **前端展示层** — 在 `dashboard.js` 中实现 `Tenant_List_View` 和 `Tenant_Detail_View` 两个视图状态的切换逻辑,包括面包屑导航、统计面板上下文切换、搜索范围限定。 数据模型 `KnowledgeEntry` 已有 `tenant_id` 字段(`String(50)`, indexed),无需数据库迁移。 ## Architecture ```mermaid graph TD subgraph Frontend["前端 (dashboard.js)"] TLV[Tenant_List_View
租户卡片列表] TDV[Tenant_Detail_View
租户知识条目列表] Stats[统计面板
全局/租户统计切换] Breadcrumb[面包屑导航] end subgraph API["Flask Blueprint (knowledge_bp)"] EP1["GET /api/knowledge/tenants"] EP2["GET /api/knowledge?tenant_id=X"] EP3["GET /api/knowledge/stats?tenant_id=X"] EP4["GET /api/knowledge/search?q=...&tenant_id=X"] EP5["POST /api/knowledge (含 tenant_id)"] end subgraph Service["KnowledgeManager"] M1[get_tenant_summary] M2[get_knowledge_paginated
+tenant_id filter] M3[get_knowledge_stats
+tenant_id filter] M4[search_knowledge
+tenant_id filter] M5[add_knowledge_entry
+tenant_id param] end subgraph DB["SQLAlchemy"] KE[KnowledgeEntry
tenant_id indexed] end TLV -->|点击租户卡片| TDV TDV -->|面包屑返回| TLV TLV --> EP1 TDV --> EP2 TDV --> EP4 Stats --> EP3 TDV --> EP5 EP1 --> M1 EP2 --> M2 EP3 --> M3 EP4 --> M4 EP5 --> M5 M1 --> KE M2 --> KE M3 --> KE M4 --> KE M5 --> KE ``` ### 设计决策 - **不引入新模型/表**:`tenant_id` 已存在于 `KnowledgeEntry`,聚合查询通过 `GROUP BY` 实现,无需额外的 Tenant 表。 - **视图状态管理在前端**:使用 JS 变量 `currentTenantId` 控制当前视图层级,避免引入前端路由框架。 - **统计面板复用**:同一个统计面板根据 `currentTenantId` 是否为 `null` 决定请求全局或租户级统计。 - **搜索范围自动限定**:当处于 `Tenant_Detail_View` 时,搜索请求自动附加 `tenant_id` 参数。 ## Components and Interfaces ### 1. KnowledgeManager 新增/修改方法 ```python # 新增方法 def get_tenant_summary(self) -> List[Dict[str, Any]]: """ 按 tenant_id 聚合活跃知识条目,返回租户汇总列表。 返回格式: [ { "tenant_id": "market_a", "entry_count": 42, "verified_count": 30, "category_distribution": {"FAQ": 20, "故障排查": 22} }, ... ] 按 entry_count 降序排列。 """ # 修改方法签名 def get_knowledge_paginated( self, page=1, per_page=10, category_filter='', verified_filter='', tenant_id: Optional[str] = None # 新增 ) -> Dict[str, Any] def search_knowledge( self, query: str, top_k=3, verified_only=True, tenant_id: Optional[str] = None # 新增 ) -> List[Dict[str, Any]] def get_knowledge_stats( self, tenant_id: Optional[str] = None # 新增 ) -> Dict[str, Any] def add_knowledge_entry( self, question, answer, category, confidence_score=0.5, is_verified=False, tenant_id: Optional[str] = None # 新增,默认取 config ) -> bool ``` ### 2. Knowledge API 新增/修改端点 | 端点 | 方法 | 变更 | 说明 | |------|------|------|------| | `/api/knowledge/tenants` | GET | 新增 | 返回租户汇总数组 | | `/api/knowledge` | GET | 修改 | 增加 `tenant_id` 查询参数 | | `/api/knowledge/stats` | GET | 修改 | 增加 `tenant_id` 查询参数 | | `/api/knowledge/search` | GET | 修改 | 增加 `tenant_id` 查询参数 | | `/api/knowledge` | POST | 修改 | 请求体增加 `tenant_id` 字段 | ### 3. 前端组件 | 组件 | 职责 | |------|------| | `loadTenantList()` | 请求 `/api/knowledge/tenants`,渲染租户卡片 | | `loadTenantDetail(tenantId, page)` | 请求 `/api/knowledge?tenant_id=X`,渲染知识条目列表 | | `renderBreadcrumb(tenantId)` | 渲染面包屑 "知识库 > {tenant_id}" | | `loadKnowledgeStats(tenantId)` | 根据 tenantId 是否为 null 请求全局/租户统计 | | `searchKnowledge()` | 搜索时自动附加 `currentTenantId` | ## Data Models ### KnowledgeEntry(现有,无变更) ```python class KnowledgeEntry(Base): __tablename__ = "knowledge_entries" id = Column(Integer, primary_key=True) tenant_id = Column(String(50), nullable=False, default="default", index=True) question = Column(Text, nullable=False) answer = Column(Text, nullable=False) category = Column(String(100), nullable=False) confidence_score = Column(Float, default=0.0) usage_count = Column(Integer, default=0) created_at = Column(DateTime, default=datetime.now) updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now) is_active = Column(Boolean, default=True) is_verified = Column(Boolean, default=False) verified_by = Column(String(100)) verified_at = Column(DateTime) vector_embedding = Column(Text) search_frequency = Column(Integer, default=0) last_accessed = Column(DateTime) relevance_score = Column(Float) ``` ### Tenant Summary(API 响应结构,非持久化) ```json { "tenant_id": "market_a", "entry_count": 42, "verified_count": 30, "category_distribution": { "FAQ": 20, "故障排查": 22 } } ``` ### Stats 响应结构(扩展) ```json { "total_entries": 100, "active_entries": 80, "category_distribution": {"FAQ": 40, "故障排查": 60}, "average_confidence": 0.85, "tenant_id": "market_a" // 新增,仅当按租户筛选时返回 } ``` ## Correctness Properties *A property is a characteristic or behavior that should hold true across all valid executions of a system — essentially, a formal statement about what the system should do. Properties serve as the bridge between human-readable specifications and machine-verifiable correctness guarantees.* ### Property 1: Tenant summary correctly aggregates active entries *For any* set of `KnowledgeEntry` records with mixed `is_active` and `tenant_id` values, calling `get_tenant_summary()` should return a list where each element's `entry_count` equals the number of active entries for that `tenant_id`, each `verified_count` equals the number of active+verified entries for that `tenant_id`, and each `category_distribution` correctly reflects the category counts of active entries for that `tenant_id`. **Validates: Requirements 1.1, 1.2** ### Property 2: Tenant summary sorted by entry_count descending *For any* result returned by `get_tenant_summary()`, the list should be sorted such that for every consecutive pair of elements `(a, b)`, `a.entry_count >= b.entry_count`. **Validates: Requirements 1.3** ### Property 3: Knowledge entry filtering by tenant, category, and verified status *For any* combination of `tenant_id`, `category_filter`, and `verified_filter` parameters, all entries returned by `get_knowledge_paginated()` should satisfy all specified filter conditions simultaneously. Specifically: every returned entry's `tenant_id` matches the requested `tenant_id`, every returned entry's `category` matches `category_filter` (if provided), and every returned entry's `is_verified` matches `verified_filter` (if provided). **Validates: Requirements 2.1, 2.3** ### Property 4: Pagination consistency with tenant filter *For any* `tenant_id` and valid `page`/`per_page` values, the entries returned by `get_knowledge_paginated(tenant_id=X, page=P, per_page=N)` should be a correct slice of the full filtered result set. The `total` field should equal the count of all matching entries, `total_pages` should equal `ceil(total / per_page)`, and the number of returned entries should equal `min(per_page, total - (page-1)*per_page)` when `page <= total_pages`. **Validates: Requirements 2.2** ### Property 5: New entry tenant association *For any* valid `tenant_id` and valid entry data (question, answer, category), calling `add_knowledge_entry(tenant_id=X, ...)` should result in the newly created `KnowledgeEntry` record having `tenant_id == X`. If `tenant_id` is not provided, it should default to the configured `get_config().server.tenant_id`. **Validates: Requirements 5.2** ### Property 6: Search results scoped to tenant *For any* search query and `tenant_id`, all results returned by `search_knowledge(query=Q, tenant_id=X)` should have `tenant_id == X`. The result set should be a subset of what `search_knowledge(query=Q)` returns (without tenant filter). **Validates: Requirements 6.2** ### Property 7: Stats scoped to tenant *For any* `tenant_id`, the statistics returned by `get_knowledge_stats(tenant_id=X)` should reflect only entries with `tenant_id == X`. Specifically, `total_entries` should equal the count of active entries for that tenant, and `average_confidence` should equal the mean confidence of those entries. When `tenant_id` is omitted, the stats should aggregate across all tenants. **Validates: Requirements 7.3, 7.4** ## Error Handling ### API 层错误处理 所有 API 端点已使用 `@handle_api_errors` 装饰器,该装饰器捕获以下异常: | 异常类型 | HTTP 状态码 | 说明 | |----------|------------|------| | `ValueError` | 400 | 参数校验失败(如 `page < 1`) | | `PermissionError` | 403 | 权限不足 | | `Exception` | 500 | 数据库查询失败等未预期错误 | ### 业务逻辑层错误处理 - `get_tenant_summary()` — 数据库异常时返回空列表 `[]`,记录 error 日志。 - `get_knowledge_paginated()` — 异常时返回空结构 `{"knowledge": [], "total": 0, ...}`(现有行为保持不变)。 - `get_knowledge_stats()` — 异常时返回空字典 `{}`(现有行为保持不变)。 - `add_knowledge_entry()` — 异常时返回 `False`,记录 error 日志。 ### 前端错误处理 - API 请求失败时通过 `showNotification(message, 'error')` 展示错误提示。 - 网络超时或断连时显示通用错误消息。 - 批量操作部分失败时显示成功/失败计数。 ## Testing Strategy ### 测试框架 - **单元测试**: `pytest` - **属性测试**: `hypothesis`(Python property-based testing 库) - **每个属性测试最少运行 100 次迭代** ### 属性测试(Property-Based Tests) 每个 Correctness Property 对应一个属性测试,使用 `hypothesis` 的 `@given` 装饰器生成随机输入。 测试标签格式: `Feature: knowledge-tenant-view, Property {number}: {property_text}` | Property | 测试描述 | 生成策略 | |----------|---------|---------| | Property 1 | 生成随机 KnowledgeEntry 列表(混合 tenant_id、is_active),验证 `get_tenant_summary()` 聚合正确性 | `st.lists(st.builds(KnowledgeEntry, tenant_id=st.sampled_from([...]), is_active=st.booleans()))` | | Property 2 | 验证 `get_tenant_summary()` 返回列表按 entry_count 降序 | 复用 Property 1 的生成策略 | | Property 3 | 生成随机 tenant_id + category + verified 组合,验证过滤结果一致性 | `st.sampled_from(tenant_ids)`, `st.sampled_from(categories)`, `st.sampled_from(['true','false',''])` | | Property 4 | 生成随机 page/per_page,验证分页切片正确性 | `st.integers(min_value=1, max_value=10)` for page/per_page | | Property 5 | 生成随机 tenant_id 和条目数据,验证新建条目的 tenant_id | `st.text(min_size=1, max_size=50)` for tenant_id | | Property 6 | 生成随机搜索词和 tenant_id,验证搜索结果范围 | `st.text()` for query, `st.sampled_from(tenant_ids)` | | Property 7 | 生成随机 tenant_id,验证统计数据与手动聚合一致 | `st.sampled_from(tenant_ids)` + `st.none()` | ### 单元测试(Unit Tests) 单元测试聚焦于边界情况和具体示例: - **边界**: 无活跃条目时 `get_tenant_summary()` 返回空数组 - **边界**: 不存在的 `tenant_id` 查询返回空列表 + `total=0` - **示例**: 数据库异常时 API 返回 500 - **示例**: `add_knowledge_entry` 不传 `tenant_id` 时使用配置默认值 - **集成**: 前端 `loadTenantList()` → API → Manager 完整链路 ### 测试配置 ```python from hypothesis import settings @settings(max_examples=100) ``` 每个属性测试函数头部添加注释引用设计文档中的 Property 编号,例如: ```python # Feature: knowledge-tenant-view, Property 1: Tenant summary correctly aggregates active entries @given(entries=st.lists(knowledge_entry_strategy(), min_size=0, max_size=50)) def test_tenant_summary_aggregation(entries): ... ```