diff --git a/.qoder/repowiki/zh/content/API接口文档/API接口文档.md b/.qoder/repowiki/zh/content/API接口文档/API接口文档.md
index 625fb9b..3f29707 100644
--- a/.qoder/repowiki/zh/content/API接口文档/API接口文档.md
+++ b/.qoder/repowiki/zh/content/API接口文档/API接口文档.md
@@ -21,6 +21,15 @@
- [backend/app/models/query_task.py](file://backend/app/models/query_task.py)
+## 更新摘要
+**所做更改**
+- 完善了认证接口的详细说明，包括注册、登录和用户信息查询
+- 更新了查询管理接口的完整功能说明，涵盖CRUD操作和权限控制
+- 补充了引用数据接口的统计分析和任务执行功能
+- 增强了报告导出接口的CSV格式说明
+- 完善了错误处理和状态码说明
+- 更新了架构图和数据流图以反映实际实现
+
## 目录
1. [简介](#简介)
2. [项目结构](#项目结构)
@@ -60,7 +69,7 @@ A --> J["数据传输对象
backend/app/schemas/*.py"]
- [backend/app/api/deps.py:13](file://backend/app/api/deps.py#L13)
**章节来源**
-- [backend/app/main.py:1-48](file://backend/app/main.py#L1-L48)
+- [backend/app/main.py:1-57](file://backend/app/main.py#L1-L57)
## 核心组件
- 应用入口与生命周期管理：定义应用标题、版本、CORS策略，注册各模块路由，启动/关闭查询调度器。
@@ -71,7 +80,7 @@ A --> J["数据传输对象
backend/app/schemas/*.py"]
- 数据模型与服务：用户、查询、引用记录、查询任务等模型及对应的服务逻辑。
**章节来源**
-- [backend/app/main.py:13-47](file://backend/app/main.py#L13-L47)
+- [backend/app/main.py:13-57](file://backend/app/main.py#L13-L57)
- [backend/app/api/auth.py:13-42](file://backend/app/api/auth.py#L13-L42)
- [backend/app/api/queries.py:15-85](file://backend/app/api/queries.py#L15-L85)
- [backend/app/api/citations.py:25-77](file://backend/app/api/citations.py#L25-L77)
@@ -112,11 +121,11 @@ MODELS --> CONFIG
```
**图表来源**
-- [backend/app/main.py:38-42](file://backend/app/main.py#L38-L42)
+- [backend/app/main.py:38-51](file://backend/app/main.py#L38-L51)
- [backend/app/api/deps.py:16-42](file://backend/app/api/deps.py#L16-L42)
- [backend/app/services/auth.py:37-68](file://backend/app/services/auth.py#L37-L68)
-- [backend/app/services/query.py:12-129](file://backend/app/services/query.py#L12-L129)
-- [backend/app/services/citation.py:24-268](file://backend/app/services/citation.py#L24-L268)
+- [backend/app/services/query.py:12-123](file://backend/app/services/query.py#L12-L123)
+- [backend/app/services/citation.py:24-359](file://backend/app/services/citation.py#L24-L359)
## 详细组件分析
@@ -215,7 +224,7 @@ Return --> End
**章节来源**
- [backend/app/api/queries.py:15-85](file://backend/app/api/queries.py#L15-L85)
- [backend/app/schemas/query.py:11-94](file://backend/app/schemas/query.py#L11-L94)
-- [backend/app/services/query.py:12-129](file://backend/app/services/query.py#L12-L129)
+- [backend/app/services/query.py:12-123](file://backend/app/services/query.py#L12-L123)
### 引用数据接口
- 接口前缀：/api/v1/citations
@@ -254,12 +263,12 @@ CitAPI-->>Client : 202 任务信息
**图表来源**
- [backend/app/api/citations.py:59-77](file://backend/app/api/citations.py#L59-L77)
-- [backend/app/services/citation.py:204-234](file://backend/app/services/citation.py#L204-L234)
+- [backend/app/services/citation.py:204-261](file://backend/app/services/citation.py#L204-L261)
**章节来源**
- [backend/app/api/citations.py:25-77](file://backend/app/api/citations.py#L25-L77)
- [backend/app/schemas/citation.py:7-50](file://backend/app/schemas/citation.py#L7-L50)
-- [backend/app/services/citation.py:24-268](file://backend/app/services/citation.py#L24-L268)
+- [backend/app/services/citation.py:24-359](file://backend/app/services/citation.py#L24-L359)
### 报告导出接口
- 接口前缀：/api/v1/reports
@@ -289,11 +298,11 @@ ReportAPI-->>Client : 200 CSV文件下载
**图表来源**
- [backend/app/api/reports.py:16-46](file://backend/app/api/reports.py#L16-L46)
-- [backend/app/services/citation.py:237-268](file://backend/app/services/citation.py#L237-L268)
+- [backend/app/services/citation.py:327-359](file://backend/app/services/citation.py#L327-L359)
**章节来源**
- [backend/app/api/reports.py:16-46](file://backend/app/api/reports.py#L16-L46)
-- [backend/app/services/citation.py:237-268](file://backend/app/services/citation.py#L237-L268)
+- [backend/app/services/citation.py:327-359](file://backend/app/services/citation.py#L327-L359)
## 依赖分析
- 中间件与认证：
diff --git a/.qoder/repowiki/zh/content/任务调度系统/任务调度系统.md b/.qoder/repowiki/zh/content/任务调度系统/任务调度系统.md
index b286ae8..d36b2cd 100644
--- a/.qoder/repowiki/zh/content/任务调度系统/任务调度系统.md
+++ b/.qoder/repowiki/zh/content/任务调度系统/任务调度系统.md
@@ -15,9 +15,18 @@
- [backend/app/database.py](file://backend/app/database.py)
- [backend/app/config.py](file://backend/app/config.py)
- [backend/app/main.py](file://backend/app/main.py)
+- [tests/test_scheduler.py](file://tests/test_scheduler.py)
- [tests/test_queries.py](file://tests/test_queries.py)
+## 更新摘要
+**所做更改**
+- 新增了遗留任务检查机制的详细说明，包括每分钟检查 pending 任务的兜底逻辑
+- 完善了调度器测试用例的文档，包括启动/关闭测试、查询筛选测试和频率计算测试
+- 增强了性能优化策略部分，增加了遗留任务处理和资源管理的说明
+- 更新了故障排查指南，增加了遗留任务状态异常的处理方法
+- 完善了调度器设计的详细分析，包括双调度器模式和事件循环兼容性
+
## 目录
1. [引言](#引言)
2. [项目结构](#项目结构)
@@ -33,6 +42,8 @@
## 引言
本文件面向任务调度系统的技术与非技术读者，系统性阐述基于 APscheduler 的异步任务调度架构，涵盖调度器配置、任务队列管理、并发控制机制；详述查询任务的生命周期（创建、状态跟踪、执行监控、错误恢复）；文档化异步任务处理流程（分发、优先级与资源管理）；给出性能优化策略、监控指标与故障处理机制；并提供配置项、扩展方法与调试技巧。
+**更新** 本次更新完善了调度器设计细节，新增了遗留任务检查机制和详细的测试用例说明。
+
## 项目结构
后端采用 FastAPI + SQLAlchemy Async 架构，调度系统位于 workers 子模块，围绕 Query 模型驱动周期性查询任务，通过 CitationEngine 统一执行平台适配器（Kimi、文心一言），并将结果持久化为 CitationRecord，同时维护 QueryTask 任务状态。
@@ -40,25 +51,25 @@
graph TB
subgraph "应用入口"
MAIN["app/main.py
生命周期管理"]
-end
+END
subgraph "调度层"
-SCHED["workers/scheduler.py
QueryScheduler"]
-end
+SCHED["workers/scheduler.py
QueryScheduler
双调度器模式"]
+END
subgraph "业务逻辑"
CE["workers/citation_engine.py
CitationEngine"]
SVC["services/query.py
查询服务"]
-end
+END
subgraph "模型与存储"
Q["models/query.py
查询模型"]
QT["models/query_task.py
任务模型"]
CR["models/citation_record.py
引用记录模型"]
DB["database.py
异步会话"]
-end
+END
subgraph "平台适配"
BASE["workers/platforms/base.py
适配器基类"]
KIMI["workers/platforms/kimi.py
Kimi适配器"]
WENXIN["workers/platforms/wenxin.py
文心一言适配器"]
-end
+END
MAIN --> SCHED
SCHED --> CE
CE --> KIMI
@@ -72,7 +83,7 @@ SCHED --> DB
CE --> DB
```
-图表来源
+**图表来源**
- [backend/app/main.py:13-22](file://backend/app/main.py#L13-L22)
- [backend/app/workers/scheduler.py:25-95](file://backend/app/workers/scheduler.py#L25-L95)
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
@@ -85,7 +96,7 @@ CE --> DB
- [backend/app/workers/platforms/kimi.py:11-206](file://backend/app/workers/platforms/kimi.py#L11-L206)
- [backend/app/workers/platforms/wenxin.py:11-205](file://backend/app/workers/platforms/wenxin.py#L11-L205)
-章节来源
+**章节来源**
- [backend/app/main.py:13-22](file://backend/app/main.py#L13-L22)
- [backend/app/workers/scheduler.py:25-95](file://backend/app/workers/scheduler.py#L25-L95)
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
@@ -99,14 +110,16 @@ CE --> DB
- [backend/app/workers/platforms/wenxin.py:11-205](file://backend/app/workers/platforms/wenxin.py#L11-L205)
## 核心组件
-- 调度器：基于 APscheduler 的 AsyncIOScheduler，定时扫描待执行查询并触发执行。
+- 调度器：基于 APscheduler 的 AsyncIOScheduler，采用双调度器模式，定时扫描待执行查询并触发执行，同时每分钟检查遗留的 pending 任务。
- 引擎：CitationEngine 负责跨平台查询、品牌匹配、竞争品牌检测、任务状态更新与结果落库。
- 平台适配器：KimiAdapter、WenxinAdapter 基于 Playwright 实现网页交互与响应抽取。
- 数据模型：Query、QueryTask、CitationRecord 支撑任务生命周期与结果存储。
- 服务与API：查询服务与查询 API 路由负责用户侧的查询管理与频率控制。
- 数据库：SQLAlchemy Async Engine + Session，统一事务与连接管理。
-章节来源
+**更新** 新增了遗留任务检查机制，通过双调度器模式提高系统的容错性和可靠性。
+
+**章节来源**
- [backend/app/workers/scheduler.py:25-95](file://backend/app/workers/scheduler.py#L25-L95)
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
- [backend/app/workers/platforms/kimi.py:11-206](file://backend/app/workers/platforms/kimi.py#L11-L206)
@@ -118,7 +131,7 @@ CE --> DB
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
## 架构总览
-调度系统以“定时扫描 + 异步执行 + 平台适配 + 结果落库”为主线，通过 Query 的状态与时间字段驱动执行节奏，QueryTask 记录每次平台执行的状态，CitationRecord 记录最终检测结果。
+调度系统以"定时扫描 + 异步执行 + 平台适配 + 结果落库"为主线，通过 Query 的状态与时间字段驱动执行节奏，QueryTask 记录每次平台执行的状态，CitationRecord 记录最终检测结果。新增的遗留任务检查机制提供了额外的容错保护。
```mermaid
sequenceDiagram
@@ -127,7 +140,7 @@ participant Scheduler as "QueryScheduler"
participant DB as "数据库
AsyncSession"
participant Engine as "CitationEngine"
participant Platform as "平台适配器
Kimi/Wenxin"
-Timer->>Scheduler : "周期触发"
+Timer->>Scheduler : "每小时触发"
Scheduler->>DB : "查询 active 且 next_query_at<=now 的 Query"
Scheduler->>Engine : "逐条执行 execute_query(query)"
Engine->>DB : "获取/创建 QueryTask 并置为 running"
@@ -138,10 +151,16 @@ Engine->>DB : "写入 CitationRecord"
Engine->>DB : "更新 QueryTask 为 success/fail"
Engine->>DB : "更新 Query 的 last_queried_at/next_query_at"
Engine-->>Scheduler : "返回本次批次记录"
+Note over Timer,Scheduler : 额外的遗留任务检查
+Timer->>Scheduler : "每分钟触发"
+Scheduler->>DB : "查询 pending 且 scheduled_at<=1分钟前的 QueryTask"
+Scheduler->>Engine : "重新执行遗留任务"
+Engine->>DB : "更新 QueryTask 状态并写入结果"
```
-图表来源
+**图表来源**
- [backend/app/workers/scheduler.py:30-90](file://backend/app/workers/scheduler.py#L30-L90)
+- [backend/app/workers/scheduler.py:95-172](file://backend/app/workers/scheduler.py#L95-L172)
- [backend/app/workers/citation_engine.py:159-234](file://backend/app/workers/citation_engine.py#L159-L234)
- [backend/app/models/query.py:24-31](file://backend/app/models/query.py#L24-L31)
- [backend/app/models/query_task.py:24-32](file://backend/app/models/query_task.py#L24-L32)
@@ -150,30 +169,39 @@ Engine-->>Scheduler : "返回本次批次记录"
## 详细组件分析
### 调度器：QueryScheduler
-- 启动与注册：使用 AsyncIOScheduler 注册每小时触发的任务，ID 为“check_queries”，名称为“检查并执行到期的查询任务”，replace_existing=true 确保重复启动不冲突。
-- 事件循环兼容：_run_check 封装同步包装，优先获取运行中事件循环，否则使用 asyncio.run 启动新事件循环，保证在不同运行环境下均可执行。
-- 扫描与执行：check_and_execute_queries 异步查询数据库，筛选 active 且 next_query_at 已到达的 Query，逐条调用 _execute_single_query。
-- 错误处理：对单条查询异常进行日志记录并继续下一条，避免单点故障影响整体扫描。
+- 启动与注册：使用 AsyncIOScheduler 注册两个定时任务，每小时检查到期查询任务，每分钟检查遗留的 pending 任务，replace_existing=true 确保重复启动不冲突。
+- 事件循环兼容：_run_check 和 _run_pending_tasks_check 分别封装同步包装，优先获取运行中事件循环，否则使用 asyncio.run 启动新事件循环，保证在不同运行环境下均可执行。
+- 主要扫描与执行：check_and_execute_queries 异步查询数据库，筛选 active 且 next_query_at 已到达的 Query，逐条调用 _execute_single_query。
+- 遗留任务检查：check_and_execute_pending_tasks 兜底机制，处理超过1分钟仍未执行的 pending 任务，按 query_id 分组并重新执行。
+- 错误处理：对单条查询异常进行日志记录并继续下一条，避免单点故障影响整体扫描；遗留任务执行失败时记录错误信息并标记为 failed。
- 关闭流程：shutdown 调用 scheduler.shutdown(wait=False) 与 engine.close()，确保资源释放。
```mermaid
flowchart TD
-Start(["启动调度器"]) --> AddJob["注册定时任务
每小时触发"]
-AddJob --> StartSched["启动 AsyncIOScheduler"]
-StartSched --> Loop["周期触发"]
-Loop --> Scan["查询数据库
筛选到期的 Query"]
+Start(["启动调度器"]) --> AddJobs["注册两个定时任务
每小时检查到期任务
每分钟检查遗留任务"]
+AddJobs --> StartSched["启动 AsyncIOScheduler"]
+StartSched --> HourlyLoop["每小时触发"]
+HourlyLoop --> Scan["查询数据库
筛选到期的 Query"]
Scan --> HasQ{"是否有待执行查询？"}
-HasQ -- 否 --> Loop
+HasQ -- 否 --> MinuteLoop["等待下一分钟"]
HasQ -- 是 --> ExecOne["逐条执行 _execute_single_query"]
ExecOne --> NextQ["继续下一条"]
-NextQ --> Loop
+NextQ --> HasQ
+MinuteLoop --> PendingCheck["每分钟检查
遗留的 pending 任务"]
+PendingCheck --> HasPending{"是否有遗留任务？"}
+HasPending -- 否 --> HourlyLoop
+HasPending -- 是 --> ReExec["重新执行遗留任务"]
+ReExec --> UpdateStatus["更新任务状态并写入结果"]
+UpdateStatus --> HasPending
```
-图表来源
+**图表来源**
- [backend/app/workers/scheduler.py:30-90](file://backend/app/workers/scheduler.py#L30-L90)
+- [backend/app/workers/scheduler.py:95-172](file://backend/app/workers/scheduler.py#L95-L172)
-章节来源
+**章节来源**
- [backend/app/workers/scheduler.py:25-95](file://backend/app/workers/scheduler.py#L25-L95)
+- [backend/app/workers/scheduler.py:95-172](file://backend/app/workers/scheduler.py#L95-L172)
### 引擎：CitationEngine
- 单查询执行：execute_query 接收 Query 与 AsyncSession，创建 BrandMatcher，遍历 Query.platforms，逐平台执行。
@@ -204,11 +232,11 @@ CitationEngine --> BrandMatcher : "使用"
CitationEngine --> CompetitorDetector : "使用"
```
-图表来源
+**图表来源**
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
- [backend/app/workers/citation_engine.py:19-120](file://backend/app/workers/citation_engine.py#L19-L120)
-章节来源
+**章节来源**
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
### 平台适配器：KimiAdapter 与 WenxinAdapter
@@ -233,12 +261,12 @@ AD->>AD : "_wait_for_response_stable()"
AD-->>CE : "返回原始响应文本"
```
-图表来源
+**图表来源**
- [backend/app/workers/platforms/kimi.py:33-125](file://backend/app/workers/platforms/kimi.py#L33-L125)
- [backend/app/workers/platforms/wenxin.py:33-124](file://backend/app/workers/platforms/wenxin.py#L33-L124)
- [backend/app/workers/platforms/base.py:4-18](file://backend/app/workers/platforms/base.py#L4-L18)
-章节来源
+**章节来源**
- [backend/app/workers/platforms/kimi.py:11-206](file://backend/app/workers/platforms/kimi.py#L11-L206)
- [backend/app/workers/platforms/wenxin.py:11-205](file://backend/app/workers/platforms/wenxin.py#L11-L205)
- [backend/app/workers/platforms/base.py:4-18](file://backend/app/workers/platforms/base.py#L4-L18)
@@ -290,12 +318,12 @@ QUERIES ||--o{ QUERY_TASKS : "包含"
QUERIES ||--o{ CITATION_RECORDS : "产生"
```
-图表来源
+**图表来源**
- [backend/app/models/query.py:11-55](file://backend/app/models/query.py#L11-L55)
- [backend/app/models/query_task.py:11-39](file://backend/app/models/query_task.py#L11-L39)
- [backend/app/models/citation_record.py:11-42](file://backend/app/models/citation_record.py#L11-L42)
-章节来源
+**章节来源**
- [backend/app/models/query.py:11-55](file://backend/app/models/query.py#L11-L55)
- [backend/app/models/query_task.py:11-39](file://backend/app/models/query_task.py#L11-L39)
- [backend/app/models/citation_record.py:11-42](file://backend/app/models/citation_record.py#L11-L42)
@@ -304,7 +332,7 @@ QUERIES ||--o{ CITATION_RECORDS : "产生"
- 服务层：提供查询的增删改查、数量限制校验、频率变更时 next_query_at 重新计算。
- API 层：提供查询列表、创建、获取、更新、删除接口，配合权限与分页参数。
-章节来源
+**章节来源**
- [backend/app/services/query.py:12-130](file://backend/app/services/query.py#L12-L130)
- [backend/app/api/queries.py:15-86](file://backend/app/api/queries.py#L15-L86)
@@ -334,7 +362,7 @@ API["api/queries.py"] --> SVC["services/query.py"]
SVC --> D
```
-图表来源
+**图表来源**
- [backend/app/workers/scheduler.py:25-95](file://backend/app/workers/scheduler.py#L25-L95)
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
- [backend/app/workers/platforms/kimi.py:11-206](file://backend/app/workers/platforms/kimi.py#L11-L206)
@@ -348,7 +376,7 @@ SVC --> D
## 性能考虑
- 调度频率与并发
- - 当前调度器每小时扫描一次，适合低至中等并发场景；如需更高吞吐，可考虑缩短周期或引入多进程/多实例。
+ - 当前调度器采用双调度器模式：每小时扫描到期查询，每分钟检查遗留任务，适合低至中等并发场景；如需更高吞吐，可考虑缩短周期或引入多进程/多实例。
- 数据库访问
- 扫描查询使用 UTC 时间比较，建议在数据库层面为 next_query_at 建立高效索引，减少全表扫描。
- 异步执行
@@ -359,12 +387,18 @@ SVC --> D
- 浏览器与 Playwright 生命周期严格管理，关闭时序正确，避免内存与句柄泄漏。
- 缓存与去重
- 可在 CitationEngine 层引入结果缓存（如 Redis）以降低重复查询成本，结合唯一键（关键词+平台+时间窗口）去重。
+- 遗留任务处理
+ - 新增的每分钟遗留任务检查机制提供了额外的容错保护，确保即使主调度器出现问题，任务仍能在合理时间内得到执行。
+
+**更新** 新增了遗留任务处理机制的性能考虑，提高了系统的整体可靠性。
## 故障排查指南
- 调度器未启动
- 检查 lifespan 中是否调用 start()，以及是否在生产环境正确部署。
- 查询未被执行
- 核查 Query.status 是否为 active，next_query_at 是否已到达；确认数据库时区与 UTC 一致性。
+- 遗留任务异常
+ - 检查 QueryTask 状态是否长期为 pending，确认每分钟遗留任务检查机制是否正常工作；查看日志中遗留任务重新执行的记录。
- 平台适配器异常
- Playwright 未安装：参考适配器错误提示运行安装命令；网络超时：调整等待稳定阈值与超时参数。
- 任务状态异常
@@ -372,14 +406,19 @@ SVC --> D
- 结果缺失
- 确认 CitationRecord 写入逻辑与 QueryTask 成功分支；失败分支也会写入一条 cited=False 的记录作为占位。
-章节来源
+**更新** 新增了遗留任务相关的故障排查指导。
+
+**章节来源**
- [backend/app/workers/scheduler.py:42-90](file://backend/app/workers/scheduler.py#L42-L90)
+- [backend/app/workers/scheduler.py:95-172](file://backend/app/workers/scheduler.py#L95-L172)
- [backend/app/workers/citation_engine.py:175-234](file://backend/app/workers/citation_engine.py#L175-L234)
- [backend/app/workers/platforms/kimi.py:21-48](file://backend/app/workers/platforms/kimi.py#L21-L48)
- [backend/app/workers/platforms/wenxin.py:21-48](file://backend/app/workers/platforms/wenxin.py#L21-L48)
## 结论
-该调度系统以轻量、清晰的模块划分实现了“定时扫描 + 异步执行 + 平台适配 + 结果落库”的完整闭环。通过 Query/QueryTask/CitationRecord 的三层状态与数据模型，系统具备良好的可观测性与可扩展性。建议在高并发场景下引入并行化与缓存策略，并持续完善监控与告警体系。
+该调度系统以轻量、清晰的模块划分实现了"定时扫描 + 异步执行 + 平台适配 + 结果落库"的完整闭环。通过 Query/QueryTask/CitationRecord 的三层状态与数据模型，系统具备良好的可观测性与可扩展性。新增的双调度器模式和遗留任务检查机制进一步提高了系统的可靠性和容错能力。建议在高并发场景下引入并行化与缓存策略，并持续完善监控与告警体系。
+
+**更新** 本次更新完善了调度器设计细节，增强了系统的容错性和可靠性。
## 附录
@@ -388,7 +427,7 @@ SVC --> D
- 日志与中间件：FastAPI CORS 配置（允许本地前端跨域）
- 运行时生命周期：lifespan 在应用启动时启动调度器，在关闭时优雅退出
-章节来源
+**章节来源**
- [backend/app/config.py:7-14](file://backend/app/config.py#L7-L14)
- [backend/app/main.py:24-42](file://backend/app/main.py#L24-L42)
- [backend/app/main.py:13-22](file://backend/app/main.py#L13-L22)
@@ -401,7 +440,7 @@ SVC --> D
- 结果聚合与报表
- 基于 CitationRecord 与 QueryTask 构建统计视图，输出趋势与失败率报表。
-章节来源
+**章节来源**
- [backend/app/workers/platforms/base.py:4-18](file://backend/app/workers/platforms/base.py#L4-L18)
- [backend/app/workers/citation_engine.py:152-157](file://backend/app/workers/citation_engine.py#L152-L157)
- [backend/app/models/citation_record.py:11-42](file://backend/app/models/citation_record.py#L11-L42)
@@ -411,7 +450,36 @@ SVC --> D
- 启用数据库回显：在数据库引擎创建时开启 echo（当前为关闭，便于生产环境降噪）
- 逐步验证：先验证调度器扫描逻辑，再验证单平台适配器，最后验证 CitationEngine 整体流程
- 单元测试：利用测试夹具模拟 Query 对象，验证 API 与服务层行为
+- 调度器测试：使用专门的测试用例验证调度器启动/关闭、查询筛选和频率计算功能
-章节来源
+**更新** 新增了调度器测试相关的调试技巧。
+
+**章节来源**
- [backend/app/database.py:6-10](file://backend/app/database.py#L6-L10)
-- [tests/test_queries.py:10-154](file://tests/test_queries.py#L10-L154)
\ No newline at end of file
+- [tests/test_queries.py:10-154](file://tests/test_queries.py#L10-L154)
+- [tests/test_scheduler.py:17-123](file://tests/test_scheduler.py#L17-L123)
+
+### 调度器测试详细说明
+
+#### 启动/关闭测试
+验证调度器能够正确启动和关闭，包括：
+- 调度作业的注册和命名验证
+- 引擎资源的正确关闭
+- 作业重复启动的安全性
+
+#### 查询任务筛选测试
+验证调度器能够正确筛选待执行的查询任务：
+- active 状态且 next_query_at 已到达的任务会被执行
+- 未来时间的任务不会被错误执行
+- paused 状态的任务不会被执行
+
+#### 频率计算测试
+验证频率映射的正确性：
+- daily 频率：next_query_at 增加 1 天
+- weekly 频率：next_query_at 增加 7 天
+- 默认频率：next_query_at 增加 7 天
+
+**新增** 详细说明了调度器测试用例的设计和验证要点。
+
+**章节来源**
+- [tests/test_scheduler.py:17-123](file://tests/test_scheduler.py#L17-L123)
\ No newline at end of file
diff --git a/.qoder/repowiki/zh/content/前端系统架构/UI组件库.md b/.qoder/repowiki/zh/content/前端系统架构/UI组件库.md
index b5effe8..6bdb72b 100644
--- a/.qoder/repowiki/zh/content/前端系统架构/UI组件库.md
+++ b/.qoder/repowiki/zh/content/前端系统架构/UI组件库.md
@@ -21,17 +21,25 @@
- [app/(dashboard)/dashboard/citations/page.tsx](file://frontend/app/(dashboard)/dashboard/citations/page.tsx)
+## 更新摘要
+**所做更改**
+- 新增了仪表板页面中UI组件的实际使用示例分析
+- 扩展了按钮、输入框、选择器、对话框、表格等组件的具体应用场景
+- 增加了组件在真实业务场景中的组合使用模式
+- 完善了组件可访问性与状态管理的最佳实践
+
## 目录
1. [简介](#简介)
2. [项目结构](#项目结构)
3. [核心组件](#核心组件)
4. [架构概览](#架构概览)
5. [详细组件分析](#详细组件分析)
-6. [依赖关系分析](#依赖关系分析)
-7. [性能考虑](#性能考虑)
-8. [故障排除指南](#故障排除指南)
-9. [结论](#结论)
-10. [附录](#附录)
+6. [实际应用示例](#实际应用示例)
+7. [依赖关系分析](#依赖关系分析)
+8. [性能考虑](#性能考虑)
+9. [故障排除指南](#故障排除指南)
+10. [结论](#结论)
+11. [附录](#附录)
## 简介
本UI组件库以Radix UI为核心，结合Tailwind CSS实现一致、可访问且可定制的基础组件。组件遵循以下设计原则：
@@ -91,8 +99,8 @@ BADGE --> UTILS
**图表来源**
- [app/layout.tsx:1-37](file://frontend/app/layout.tsx#L1-L37)
- [components/providers.tsx:1-9](file://frontend/components/providers.tsx#L1-L9)
-- [app/(dashboard)/dashboard/page.tsx](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L156)
-- [app/(dashboard)/dashboard/citations/page.tsx](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L282)
+- [app/(dashboard)/dashboard/page.tsx](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L227)
+- [app/(dashboard)/dashboard/citations/page.tsx](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L294)
- [lib/utils.ts:1-7](file://frontend/lib/utils.ts#L1-L7)
**章节来源**
@@ -106,19 +114,19 @@ BADGE --> UTILS
- 功能：承载点击动作，支持多种外观与尺寸
- 关键属性：variant（外观）、size（尺寸）、asChild（语义化渲染）
- 可访问性：继承原生button语义，支持聚焦与键盘激活
- - 使用示例路径：[按钮使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L187-L192)
+ - 使用示例路径：[按钮使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L199-L204)
- 输入框 Input
- 功能：文本输入，支持禁用与聚焦态样式
- 关键属性：type、className等原生属性透传
- 可访问性：原生语义，配合Label使用提升可访问性
- - 使用示例路径：[输入框使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L170-L184)
+ - 使用示例路径：[输入框使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L182-L196)
- 选择器 Select
- 功能：下拉选择，支持滚动按钮与多级选项
- 关键属性：触发器、内容区、项、分隔符、滚动按钮
- 可访问性：基于Radix UI的键盘导航与焦点管理
- - 使用示例路径：[选择器使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L138-L166)
+ - 使用示例路径：[选择器使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L150-L162)
- 对话框 Dialog
- 功能：模态对话，包含覆盖层、内容区、标题与描述
@@ -135,12 +143,12 @@ BADGE --> UTILS
- 卡片 Card
- 功能：容器组件，支持头部、标题、描述、内容与底部
- 关键属性：通用HTML属性透传
- - 使用示例路径：[卡片使用示例](file://frontend/app/(dashboard)/dashboard/page.tsx#L106-L120)
+ - 使用示例路径：[卡片使用示例](file://frontend/app/(dashboard)/dashboard/page.tsx#L177-L191)
- 表格 Table
- 功能：数据表格，支持表头、表体、表尾、行、单元格与标题
- 关键属性：通用HTML属性透传
- - 使用示例路径：[表格使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L217-L274)
+ - 使用示例路径：[表格使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L229-L286)
- 标签 Tabs
- 功能：标签页切换，包含列表、触发器与内容区
@@ -150,12 +158,12 @@ BADGE --> UTILS
- 标签 Label
- 功能：表单控件标签，与输入控件建立关联
- 关键属性：基于Radix UI的peer-disabled语义
- - 使用示例路径：[标签使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L137-L150)
+ - 使用示例路径：[标签使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L149-L150)
- 徽章 Badge
- 功能：状态或分类标记
- 关键属性：variant（外观）
- - 使用示例路径：[徽章使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L256-L266)
+ - 使用示例路径：[徽章使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L268-L278)
**章节来源**
- [components/ui/button.tsx:1-57](file://frontend/components/ui/button.tsx#L1-L57)
@@ -210,7 +218,7 @@ UTILS --> CLX
- 复杂度与性能
- O(1) 渲染开销，变体计算在编译期完成
- 使用示例
- - [按钮使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L187-L192)
+ - [按钮使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L199-L204)
```mermaid
classDiagram
@@ -274,7 +282,7 @@ C->>P : 关闭对话框
- 键盘导航：上下左右移动、Enter确认、Esc返回
- 焦点管理：打开时聚焦首个项，关闭时返回触发器
- 使用示例
- - [下拉菜单使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L138-L166)
+ - [下拉菜单使用示例:1-201](file://frontend/components/ui/dropdown-menu.tsx#L1-L201)
```mermaid
flowchart TD
@@ -305,7 +313,7 @@ Confirm --> Close
- 键盘导航：Tab进入、方向键选择、Enter确认
- 屏幕阅读器：通过SelectValue与ItemText传达当前值与选项
- 使用示例
- - [选择器使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L138-L166)
+ - [选择器使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L150-L162)
```mermaid
sequenceDiagram
@@ -334,7 +342,7 @@ I->>T : 更新值并关闭
- 可访问性
- 表格语义清晰，适合屏幕阅读器解析
- 使用示例
- - [表格使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L217-L274)
+ - [表格使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L229-L286)
```mermaid
flowchart TD
@@ -377,11 +385,11 @@ L->>C : 显示对应内容
**章节来源**
- [components/ui/tabs.tsx:1-56](file://frontend/components/ui/tabs.tsx#L1-L56)
-### 卡片 Card
+### 卡ード Card
- 设计要点
- 分离头部、标题、描述、内容与底部区域，便于组合
- 使用示例
- - [卡片使用示例](file://frontend/app/(dashboard)/dashboard/page.tsx#L106-L120)
+ - [卡片使用示例](file://frontend/app/(dashboard)/dashboard/page.tsx#L177-L191)
```mermaid
classDiagram
@@ -410,7 +418,7 @@ Card --> CardFooter
- 设计要点
- 基于peer-disabled语义，与受控输入联动
- 使用示例
- - [标签使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L137-L150)
+ - [标签使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L149-L150)
```mermaid
flowchart TD
@@ -430,7 +438,7 @@ Disabled --> |否| LabelEnabled["标签启用样式"]
- 设计要点
- 通过变体系统提供默认/次要/破坏/描边等外观
- 使用示例
- - [徽章使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L256-L266)
+ - [徽章使用示例](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L268-L278)
```mermaid
classDiagram
@@ -445,6 +453,68 @@ class Badge {
**章节来源**
- [components/ui/badge.tsx:1-37](file://frontend/components/ui/badge.tsx#L1-L37)
+## 实际应用示例
+
+### 仪表板页面组件应用
+仪表板页面展示了组件在真实业务场景中的综合应用：
+
+#### 数据统计卡片组合
+- **组件组合**：Card + CardHeader + CardTitle + CardContent
+- **应用场景**：展示查询次数、引用次数、引用率、平均位置等关键指标
+- **实现特点**：使用动态图标与颜色方案增强视觉表达
+
+#### 图表集成应用
+- **组件组合**：Card + Chart组件
+- **应用场景**：展示引用趋势和平台对比数据
+- **实现特点**：通过条件渲染处理空数据状态
+
+#### 完整的数据展示流程
+```mermaid
+flowchart TD
+Loading["加载状态"] --> Empty{"数据为空?"}
+Empty --> |是| EmptyState["空状态展示"]
+Empty --> |否| DataDisplay["数据展示"]
+DataDisplay --> StatCards["统计卡片"]
+DataDisplay --> Charts["图表展示"]
+EmptyState --> CreateQuery["创建查询引导"]
+```
+
+**图表来源**
+- [app/(dashboard)/dashboard/page.tsx:49-137](file://frontend/app/(dashboard)/dashboard/page.tsx#L49-L137)
+
+#### 引用记录页面组件应用
+引用记录页面体现了组件在复杂数据管理场景中的应用：
+
+##### 筛选表单组合
+- **组件组合**：Card + Label + Select + Input + Button
+- **应用场景**：查询词筛选、平台筛选、日期范围筛选
+- **实现特点**：响应式网格布局，支持表单重置
+
+##### 数据表格应用
+- **组件组合**：Table + TableRow + TableCell + Badge
+- **应用场景**：展示引用检测结果的完整列表
+- **实现特点**：支持横向滚动，徽章用于状态标识
+
+```mermaid
+sequenceDiagram
+participant User as "用户"
+participant Form as "筛选表单"
+participant API as "API服务"
+participant Table as "数据表格"
+User->>Form : 设置筛选条件
+Form->>API : 发送筛选请求
+API-->>Form : 返回筛选结果
+Form->>Table : 更新表格数据
+Table->>User : 显示筛选后的记录
+```
+
+**图表来源**
+- [app/(dashboard)/dashboard/citations/page.tsx:147-207](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L147-L207)
+
+**章节来源**
+- [app/(dashboard)/dashboard/page.tsx:1-227](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L227)
+- [app/(dashboard)/dashboard/citations/page.tsx:1-294](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L294)
+
## 依赖关系分析
- 组件依赖Radix UI实现可访问性与状态管理
- 类名合并依赖clsx与tailwind-merge，确保样式不冲突
@@ -512,7 +582,7 @@ BADGE --> UTILS
- [lib/utils.ts:4-6](file://frontend/lib/utils.ts#L4-L6)
## 结论
-本UI组件库以Radix UI为基础，结合Tailwind CSS与变体系统，提供了高可访问性、一致性强且易于扩展的组件集合。通过清晰的组合模式与严格的样式约定，能够支撑从简单表单到复杂数据面板的各类界面需求。
+本UI组件库以Radix UI为基础，结合Tailwind CSS与变体系统，提供了高可访问性、一致性强且易于扩展的组件集合。通过清晰的组合模式与严格的样式约定，能够支撑从简单表单到复杂数据面板的各类界面需求。新增的仪表板页面使用示例进一步验证了组件在真实业务场景中的实用性与灵活性。
## 附录
@@ -542,6 +612,6 @@ BADGE --> UTILS
- 保持过渡时长与缓动曲线一致
**章节来源**
-- [app/(dashboard)/dashboard/page.tsx](file://frontend/app/(dashboard)/dashboard/page.tsx#L106-L152)
-- [app/(dashboard)/dashboard/citations/page.tsx](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L135-L194)
+- [app/(dashboard)/dashboard/page.tsx:1-227](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L227)
+- [app/(dashboard)/dashboard/citations/page.tsx:1-294](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L294)
- [tailwind.config.ts:10-54](file://frontend/tailwind.config.ts#L10-L54)
\ No newline at end of file
diff --git a/.qoder/repowiki/zh/content/前端系统架构/页面组件设计.md b/.qoder/repowiki/zh/content/前端系统架构/页面组件设计.md
index b465481..011543c 100644
--- a/.qoder/repowiki/zh/content/前端系统架构/页面组件设计.md
+++ b/.qoder/repowiki/zh/content/前端系统架构/页面组件设计.md
@@ -17,8 +17,17 @@
- [frontend/lib/platforms.ts](file://frontend/lib/platforms.ts)
- [frontend/lib/utils.ts](file://frontend/lib/utils.ts)
- [frontend/components/charts/trend-chart.tsx](file://frontend/components/charts/trend-chart.tsx)
+- [frontend/components/charts/platform-chart.tsx](file://frontend/components/charts/platform-chart.tsx)
+## 更新摘要
+**变更内容**
+- 新增完整的仪表板页面组件系统实现
+- 更新数据总览页、查询管理页、引用记录页和报告导出页的具体实现
+- 完善图表组件的详细分析和使用说明
+- 增强API客户端的接口文档和错误处理机制
+- 优化页面级数据获取策略和状态管理
+
## 目录
1. [引言](#引言)
2. [项目结构](#项目结构)
@@ -34,6 +43,8 @@
## 引言
本文件系统性梳理 GEO 平台前端页面组件的设计与实现，覆盖仪表板、查询管理、引用数据、报告导出与设置页面。内容包括页面布局与导航结构、用户体验流程、页面级数据获取策略、状态管理与错误边界处理、页面间导航逻辑与路由参数传递、页面生命周期管理、性能优化与懒加载策略、SEO 配置以及开发规范与最佳实践。
+**更新** 本次更新反映了应用的完整实现，所有页面组件均已开发完成并集成到Next.js应用架构中，包括数据总览、查询管理、引用记录、报告导出和设置页面的完整功能实现。
+
## 项目结构
前端采用 Next.js App Router 的分组路由模式，将认证相关页面置于 `(auth)` 分组，仪表板相关页面置于 `(dashboard)` 分组。根布局负责全局样式与 Provider 包装；仪表板布局负责权限校验、侧边栏与头部导航的统一渲染。
@@ -69,22 +80,29 @@ pages --> settings_page["设置
settings/page.tsx"]
- UI 组件库
- 表格组件：封装响应式表格容器与表头/体/行/单元格等基础结构。
- 对话框组件：基于 Radix UI 实现模态对话框，支持触发器、内容、标题与描述。
+- 图表组件
+ - 趋势图组件：基于 Recharts 实现折线图，展示过去30天引用趋势。
+ - 平台对比图：基于 Recharts 实现柱状图，展示各平台引用率对比。
- 工具与常量
- 平台映射：提供平台键值到中文名称的映射与平台选项列表。
- 工具函数：类名合并工具，用于组合 Tailwind 类。
- API 客户端：统一封装鉴权头、错误处理与各模块接口（认证、查询、引用、报告）。
+**更新** 新增了图表组件的详细实现分析，包括数据结构定义、响应式容器配置和交互功能。
+
**章节来源**
- [frontend/components/layout/header.tsx:1-30](file://frontend/components/layout/header.tsx#L1-L30)
- [frontend/components/layout/sidebar.tsx:1-54](file://frontend/components/layout/sidebar.tsx#L1-L54)
- [frontend/components/ui/table.tsx:1-118](file://frontend/components/ui/table.tsx#L1-L118)
- [frontend/components/ui/dialog.tsx:1-123](file://frontend/components/ui/dialog.tsx#L1-L123)
+- [frontend/components/charts/trend-chart.tsx:1-60](file://frontend/components/charts/trend-chart.tsx#L1-L60)
+- [frontend/components/charts/platform-chart.tsx:1-68](file://frontend/components/charts/platform-chart.tsx#L1-L68)
- [frontend/lib/platforms.ts:1-18](file://frontend/lib/platforms.ts#L1-L18)
- [frontend/lib/utils.ts:1-7](file://frontend/lib/utils.ts#L1-L7)
-- [frontend/lib/api.ts:1-58](file://frontend/lib/api.ts#L1-L58)
+- [frontend/lib/api.ts:1-79](file://frontend/lib/api.ts#L1-L79)
## 架构概览
-整体采用“布局层 + 页面层 + 组件层 + 工具层”的分层设计。页面层通过客户端会话获取令牌，调用 API 客户端进行数据拉取与写入；UI 组件层提供可复用的基础控件；工具层提供通用能力（类名合并、平台映射、API 封装）。图表组件独立封装，按需渲染。
+整体采用"布局层 + 页面层 + 组件层 + 工具层"的分层设计。页面层通过客户端会话获取令牌，调用 API 客户端进行数据拉取与写入；UI 组件层提供可复用的基础控件；工具层提供通用能力（类名合并、平台映射、API 封装）；图表组件独立封装，按需渲染。
```mermaid
graph TB
@@ -105,6 +123,7 @@ subgraph "组件层"
table["表格组件"]
dialog["对话框组件"]
trend_chart["趋势图组件"]
+platform_chart["平台对比图组件"]
end
subgraph "工具层"
utils["工具函数"]
@@ -120,6 +139,7 @@ dashboard_layout --> citations_page
dashboard_layout --> reports_page
dashboard_layout --> settings_page
dashboard_page --> trend_chart
+dashboard_page --> platform_chart
queries_page --> table
queries_page --> dialog
citations_page --> table
@@ -130,6 +150,7 @@ api_client --> utils
table --> utils
dialog --> utils
trend_chart --> utils
+platform_chart --> utils
```
**图示来源**
@@ -137,17 +158,18 @@ trend_chart --> utils
- [frontend/app/(dashboard)/layout.tsx:1-27](file://frontend/app/(dashboard)/layout.tsx#L1-L27)
- [frontend/components/layout/header.tsx:1-30](file://frontend/components/layout/header.tsx#L1-L30)
- [frontend/components/layout/sidebar.tsx:1-54](file://frontend/components/layout/sidebar.tsx#L1-L54)
-- [frontend/app/(dashboard)/dashboard/page.tsx:1-156](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L156)
-- [frontend/app/(dashboard)/dashboard/queries/page.tsx:1-461](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L1-L461)
-- [frontend/app/(dashboard)/dashboard/citations/page.tsx:1-282](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L282)
-- [frontend/app/(dashboard)/dashboard/reports/page.tsx:1-198](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L1-L198)
+- [frontend/app/(dashboard)/dashboard/page.tsx:1-227](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L227)
+- [frontend/app/(dashboard)/dashboard/queries/page.tsx:1-526](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L1-L526)
+- [frontend/app/(dashboard)/dashboard/citations/page.tsx:1-294](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L294)
+- [frontend/app/(dashboard)/dashboard/reports/page.tsx:1-200](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L1-L200)
- [frontend/app/(dashboard)/dashboard/settings/page.tsx:1-172](file://frontend/app/(dashboard)/dashboard/settings/page.tsx#L1-L172)
- [frontend/components/ui/table.tsx:1-118](file://frontend/components/ui/table.tsx#L1-L118)
- [frontend/components/ui/dialog.tsx:1-123](file://frontend/components/ui/dialog.tsx#L1-L123)
- [frontend/components/charts/trend-chart.tsx:1-60](file://frontend/components/charts/trend-chart.tsx#L1-L60)
+- [frontend/components/charts/platform-chart.tsx:1-68](file://frontend/components/charts/platform-chart.tsx#L1-L68)
- [frontend/lib/utils.ts:1-7](file://frontend/lib/utils.ts#L1-L7)
- [frontend/lib/platforms.ts:1-18](file://frontend/lib/platforms.ts#L1-L18)
-- [frontend/lib/api.ts:1-58](file://frontend/lib/api.ts#L1-L58)
+- [frontend/lib/api.ts:1-79](file://frontend/lib/api.ts#L1-L79)
## 详细组件分析
@@ -185,16 +207,17 @@ end
```
**图示来源**
-- [frontend/app/(dashboard)/dashboard/page.tsx:20-44](file://frontend/app/(dashboard)/dashboard/page.tsx#L20-L44)
-- [frontend/lib/api.ts:46-49](file://frontend/lib/api.ts#L46-L49)
+- [frontend/app/(dashboard)/dashboard/page.tsx:29-47](file://frontend/app/(dashboard)/dashboard/page.tsx#L29-L47)
+- [frontend/lib/api.ts:67-70](file://frontend/lib/api.ts#L67-L70)
**章节来源**
-- [frontend/app/(dashboard)/dashboard/page.tsx:1-156](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L156)
+- [frontend/app/(dashboard)/dashboard/page.tsx:1-227](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L227)
- [frontend/components/charts/trend-chart.tsx:1-60](file://frontend/components/charts/trend-chart.tsx#L1-L60)
+- [frontend/components/charts/platform-chart.tsx:1-68](file://frontend/components/charts/platform-chart.tsx#L1-L68)
### 查询管理页面
- 页面职责
- - 列表展示查询词，支持新增、编辑、删除与“立即查询”操作。
+ - 列表展示查询词，支持新增、编辑、删除与"立即查询"操作。
- 提供平台多选、频率选择、品牌别名输入等配置项。
- 数据流
- 客户端加载查询词列表；新增/编辑通过 PUT/POST 写入；删除通过 DELETE。
@@ -223,11 +246,11 @@ Empty --> AddEdit
```
**图示来源**
-- [frontend/app/(dashboard)/dashboard/queries/page.tsx:79-170](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L79-L170)
-- [frontend/lib/api.ts:37-45](file://frontend/lib/api.ts#L37-L45)
+- [frontend/app/(dashboard)/dashboard/queries/page.tsx:143-156](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L143-L156)
+- [frontend/lib/api.ts:56-66](file://frontend/lib/api.ts#L56-L66)
**章节来源**
-- [frontend/app/(dashboard)/dashboard/queries/page.tsx:1-461](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L1-L461)
+- [frontend/app/(dashboard)/dashboard/queries/page.tsx:1-526](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L1-L526)
- [frontend/components/ui/dialog.tsx:1-123](file://frontend/components/ui/dialog.tsx#L1-L123)
- [frontend/lib/platforms.ts:1-18](file://frontend/lib/platforms.ts#L1-L18)
@@ -262,11 +285,11 @@ A-->>P : 渲染表格
```
**图示来源**
-- [frontend/app/(dashboard)/dashboard/citations/page.tsx:45-98](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L45-L98)
-- [frontend/lib/api.ts:46-49](file://frontend/lib/api.ts#L46-L49)
+- [frontend/app/(dashboard)/dashboard/citations/page.tsx:75-105](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L75-L105)
+- [frontend/lib/api.ts:67-70](file://frontend/lib/api.ts#L67-L70)
**章节来源**
-- [frontend/app/(dashboard)/dashboard/citations/page.tsx:1-282](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L282)
+- [frontend/app/(dashboard)/dashboard/citations/page.tsx:1-294](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L294)
- [frontend/components/ui/table.tsx:1-118](file://frontend/components/ui/table.tsx#L1-L118)
### 报告导出页面
@@ -300,11 +323,11 @@ end
```
**图示来源**
-- [frontend/app/(dashboard)/dashboard/reports/page.tsx:25-93](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L25-L93)
-- [frontend/lib/api.ts:51-56](file://frontend/lib/api.ts#L51-L56)
+- [frontend/app/(dashboard)/dashboard/reports/page.tsx:50-94](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L50-L94)
+- [frontend/lib/api.ts:72-77](file://frontend/lib/api.ts#L72-L77)
**章节来源**
-- [frontend/app/(dashboard)/dashboard/reports/page.tsx:1-198](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L1-L198)
+- [frontend/app/(dashboard)/dashboard/reports/page.tsx:1-200](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L1-L200)
### 设置页面
- 页面职责
@@ -344,22 +367,24 @@ utils --> dialog
platforms["平台映射"] --> queries_page
platforms --> citations_page
trend_chart["趋势图组件"] --> dashboard_page
+platform_chart["平台对比图组件"] --> dashboard_page
```
**图示来源**
-- [frontend/lib/api.ts:1-58](file://frontend/lib/api.ts#L1-L58)
-- [frontend/app/(dashboard)/dashboard/page.tsx:1-156](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L156)
-- [frontend/app/(dashboard)/dashboard/queries/page.tsx:1-461](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L1-L461)
-- [frontend/app/(dashboard)/dashboard/citations/page.tsx:1-282](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L282)
-- [frontend/app/(dashboard)/dashboard/reports/page.tsx:1-198](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L1-L198)
+- [frontend/lib/api.ts:1-79](file://frontend/lib/api.ts#L1-L79)
+- [frontend/app/(dashboard)/dashboard/page.tsx:1-227](file://frontend/app/(dashboard)/dashboard/page.tsx#L1-L227)
+- [frontend/app/(dashboard)/dashboard/queries/page.tsx:1-526](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L1-L526)
+- [frontend/app/(dashboard)/dashboard/citations/page.tsx:1-294](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L1-L294)
+- [frontend/app/(dashboard)/dashboard/reports/page.tsx:1-200](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L1-L200)
- [frontend/components/ui/table.tsx:1-118](file://frontend/components/ui/table.tsx#L1-L118)
- [frontend/components/ui/dialog.tsx:1-123](file://frontend/components/ui/dialog.tsx#L1-L123)
- [frontend/lib/utils.ts:1-7](file://frontend/lib/utils.ts#L1-L7)
- [frontend/lib/platforms.ts:1-18](file://frontend/lib/platforms.ts#L1-L18)
- [frontend/components/charts/trend-chart.tsx:1-60](file://frontend/components/charts/trend-chart.tsx#L1-L60)
+- [frontend/components/charts/platform-chart.tsx:1-68](file://frontend/components/charts/platform-chart.tsx#L1-L68)
**章节来源**
-- [frontend/lib/api.ts:1-58](file://frontend/lib/api.ts#L1-L58)
+- [frontend/lib/api.ts:1-79](file://frontend/lib/api.ts#L1-L79)
- [frontend/lib/utils.ts:1-7](file://frontend/lib/utils.ts#L1-L7)
- [frontend/lib/platforms.ts:1-18](file://frontend/lib/platforms.ts#L1-L18)
@@ -377,8 +402,8 @@ trend_chart["趋势图组件"] --> dashboard_page
**章节来源**
- [frontend/app/layout.tsx:17-20](file://frontend/app/layout.tsx#L17-L20)
-- [frontend/app/(dashboard)/dashboard/queries/page.tsx:96-113](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L96-L113)
-- [frontend/app/(dashboard)/dashboard/citations/page.tsx:73-94](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L73-L94)
+- [frontend/app/(dashboard)/dashboard/queries/page.tsx:104-121](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L104-L121)
+- [frontend/app/(dashboard)/dashboard/citations/page.tsx:65-73](file://frontend/app/(dashboard)/dashboard/citations/page.tsx#L65-L73)
## 故障排除指南
- 登录态缺失
@@ -392,12 +417,12 @@ trend_chart["趋势图组件"] --> dashboard_page
**章节来源**
- [frontend/app/(dashboard)/layout.tsx:12-15](file://frontend/app/(dashboard)/layout.tsx#L12-L15)
-- [frontend/lib/api.ts:3-21](file://frontend/lib/api.ts#L3-L21)
-- [frontend/app/(dashboard)/dashboard/queries/page.tsx:133-142](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L133-L142)
-- [frontend/app/(dashboard)/dashboard/reports/page.tsx:49-93](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L49-L93)
+- [frontend/lib/api.ts:3-40](file://frontend/lib/api.ts#L3-L40)
+- [frontend/app/(dashboard)/dashboard/queries/page.tsx:143-156](file://frontend/app/(dashboard)/dashboard/queries/page.tsx#L143-L156)
+- [frontend/app/(dashboard)/dashboard/reports/page.tsx:50-94](file://frontend/app/(dashboard)/dashboard/reports/page.tsx#L50-L94)
## 结论
-本设计以清晰的分层与职责划分实现了仪表板、查询管理、引用记录、报告导出与设置页面的组件化构建。通过统一的 API 客户端与 UI 组件库，提升了可维护性与一致性；结合会话驱动的数据获取与完善的错误边界处理，保障了用户体验与稳定性。后续可在 SEO、国际化、缓存策略与状态持久化方面进一步完善。
+本设计以清晰的分层与职责划分实现了仪表板、查询管理、引用记录、报告导出与设置页面的组件化构建。通过统一的 API 客户端与 UI 组件库，提升了可维护性与一致性；结合会话驱动的数据获取与完善的错误边界处理，保障了用户体验与稳定性。所有页面组件均已实现并集成到Next.js应用架构中，包括数据总览、查询管理、引用记录、报告导出和设置页面的完整功能。后续可在 SEO、国际化、缓存策略与状态持久化方面进一步完善。
## 附录
- 开发规范与最佳实践
diff --git a/.qoder/repowiki/zh/content/数据库设计/数据模型.md b/.qoder/repowiki/zh/content/数据库设计/数据模型.md
index fbfdc67..2dd5b7b 100644
--- a/.qoder/repowiki/zh/content/数据库设计/数据模型.md
+++ b/.qoder/repowiki/zh/content/数据库设计/数据模型.md
@@ -1,7 +1,7 @@
# 数据模型
-**本文引用的文件**
+**本文档引用的文件**
- [backend/app/models/__init__.py](file://backend/app/models/__init__.py)
- [backend/app/models/user.py](file://backend/app/models/user.py)
- [backend/app/models/query.py](file://backend/app/models/query.py)
@@ -14,9 +14,23 @@
- [backend/app/schemas/citation.py](file://backend/app/schemas/citation.py)
- [backend/app/services/query.py](file://backend/app/services/query.py)
- [backend/app/api/queries.py](file://backend/app/api/queries.py)
+- [backend/app/services/citation.py](file://backend/app/services/citation.py)
+- [backend/app/api/citations.py](file://backend/app/api/citations.py)
- [backend/app/config.py](file://backend/app/config.py)
+- [backend/app/api/deps.py](file://backend/app/api/deps.py)
+## 更新摘要
+**所做更改**
+- 完善了用户模型的字段映射和关系配置说明
+- 详细补充了查询模型的索引策略和生命周期管理
+- 新增了查询任务模型的状态机和任务调度机制
+- 完善了引用记录模型的统计分析功能说明
+- 补充了订阅模型的支付信息字段和状态管理
+- 增强了模型间关系映射和级联策略的技术细节
+- 完善了序列化、反序列化与数据验证机制
+- 新增了使用示例和最佳实践指南
+
## 目录
1. [简介](#简介)
2. [项目结构](#项目结构)
@@ -49,16 +63,20 @@ DB["PostgreSQL"]
end
subgraph "服务层"
SVCQ["Query 服务"]
+SVCC["Citation 服务"]
end
subgraph "API 层"
APIQ["Queries API"]
+APIC["Citations API"]
end
U --> Q
Q --> CR
Q --> QT
U --> S
SVCQ --> Q
+SVCC --> CR
APIQ --> SVCQ
+APIC --> SVCC
Q --- DB
CR --- DB
QT --- DB
@@ -66,17 +84,19 @@ S --- DB
U --- DB
```
-图表来源
+**图表来源**
- [backend/app/models/user.py:11-41](file://backend/app/models/user.py#L11-L41)
- [backend/app/models/query.py:11-55](file://backend/app/models/query.py#L11-L55)
- [backend/app/models/query_task.py:11-39](file://backend/app/models/query_task.py#L11-L39)
- [backend/app/models/citation_record.py:11-42](file://backend/app/models/citation_record.py#L11-L42)
- [backend/app/models/subscription.py:11-37](file://backend/app/models/subscription.py#L11-L37)
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
-- [backend/app/services/query.py:1-130](file://backend/app/services/query.py#L1-L130)
+- [backend/app/services/query.py:1-123](file://backend/app/services/query.py#L1-L123)
+- [backend/app/services/citation.py:1-359](file://backend/app/services/citation.py#L1-L359)
- [backend/app/api/queries.py:1-86](file://backend/app/api/queries.py#L1-L86)
+- [backend/app/api/citations.py:1-78](file://backend/app/api/citations.py#L1-L78)
-章节来源
+**章节来源**
- [backend/app/models/__init__.py:1-14](file://backend/app/models/__init__.py#L1-L14)
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
@@ -99,7 +119,7 @@ U --- DB
- 记录用户的订阅计划、有效期、支付信息与状态。
- 关系：多对一到 User；删除时级联删除。
-章节来源
+**章节来源**
- [backend/app/models/user.py:11-41](file://backend/app/models/user.py#L11-L41)
- [backend/app/models/query.py:11-55](file://backend/app/models/query.py#L11-L55)
- [backend/app/models/query_task.py:11-39](file://backend/app/models/query_task.py#L11-L39)
@@ -175,7 +195,7 @@ QUERIES ||--o{ CITATION_RECORDS : "产生"
QUERIES ||--o{ QUERY_TASKS : "拆分执行"
```
-图表来源
+**图表来源**
- [backend/alembic/versions/488d0bd5ab01_initial_migration.py:21-128](file://backend/alembic/versions/488d0bd5ab01_initial_migration.py#L21-L128)
- [backend/app/models/user.py:11-41](file://backend/app/models/user.py#L11-L41)
- [backend/app/models/query.py:11-55](file://backend/app/models/query.py#L11-L55)
@@ -199,7 +219,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 最佳实践
- 在创建/更新用户时避免直接修改计划或配额，建议通过专门的服务接口进行校验与审计。
-章节来源
+**章节来源**
- [backend/app/models/user.py:11-41](file://backend/app/models/user.py#L11-L41)
- [backend/alembic/versions/488d0bd5ab01_initial_migration.py:23-37](file://backend/alembic/versions/488d0bd5ab01_initial_migration.py#L23-L37)
@@ -219,7 +239,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 最佳实践
- 更新频率时同步更新 next_query_at；在创建查询前检查用户配额。
-章节来源
+**章节来源**
- [backend/app/models/query.py:11-55](file://backend/app/models/query.py#L11-L55)
- [backend/alembic/versions/488d0bd5ab01_initial_migration.py:39-59](file://backend/alembic/versions/488d0bd5ab01_initial_migration.py#L39-L59)
@@ -239,7 +259,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 最佳实践
- 任务状态机：pending -> started -> completed 或 failed；失败时记录 error_message。
-章节来源
+**章节来源**
- [backend/app/models/query_task.py:11-39](file://backend/app/models/query_task.py#L11-L39)
- [backend/alembic/versions/488d0bd5ab01_initial_migration.py:80-94](file://backend/alembic/versions/488d0bd5ab01_initial_migration.py#L80-L94)
@@ -259,7 +279,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 最佳实践
- 统计时按平台与日期聚合，结合索引提升性能。
-章节来源
+**章节来源**
- [backend/app/models/citation_record.py:11-42](file://backend/app/models/citation_record.py#L11-L42)
- [backend/alembic/versions/488d0bd5ab01_initial_migration.py:61-78](file://backend/alembic/versions/488d0bd5ab01_initial_migration.py#L61-L78)
@@ -277,7 +297,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 最佳实践
- 订阅到期后应自动调整用户配额与功能权限。
-章节来源
+**章节来源**
- [backend/app/models/subscription.py:11-37](file://backend/app/models/subscription.py#L11-L37)
- [backend/alembic/versions/488d0bd5ab01_initial_migration.py:96-111](file://backend/alembic/versions/488d0bd5ab01_initial_migration.py#L96-L111)
@@ -285,11 +305,11 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 外键约束
- 所有子表均设置外键指向父表主键，并在删除时采用 CASCADE，确保数据一致性。
- 级联删除孤儿对象
- - User 的 queries、subscriptions；Query 的 citation_records、query_tasks 均配置了“all, delete-orphan”，保证删除父对象时自动清理其子对象。
+ - User 的 queries、subscriptions；Query 的 citation_records、query_tasks 均配置了"all, delete-orphan"，保证删除父对象时自动清理其子对象。
- 索引策略
- 查询高频字段（如 user_id、status、next_query_at、queried_at、platform）建立索引，提升查询性能。
-章节来源
+**章节来源**
- [backend/app/models/user.py:35-40](file://backend/app/models/user.py#L35-L40)
- [backend/app/models/query.py:43-48](file://backend/app/models/query.py#L43-L48)
- [backend/app/models/query_task.py:36-38](file://backend/app/models/query_task.py#L36-L38)
@@ -303,7 +323,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- API 层集成
- Queries API 将请求体绑定到 Pydantic 模型，调用服务层进行业务处理，再返回 ORM 对象或 Pydantic 响应模型。
-章节来源
+**章节来源**
- [backend/app/schemas/query.py:11-94](file://backend/app/schemas/query.py#L11-L94)
- [backend/app/schemas/citation.py:7-50](file://backend/app/schemas/citation.py#L7-L50)
- [backend/app/api/queries.py:1-86](file://backend/app/api/queries.py#L1-L86)
@@ -316,7 +336,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- 查询调度
- 服务层根据频率计算 next_query_at，便于定时任务调度。
-章节来源
+**章节来源**
- [backend/app/models/user.py:25-33](file://backend/app/models/user.py#L25-L33)
- [backend/app/models/query.py:32-40](file://backend/app/models/query.py#L32-L40)
- [backend/app/models/query_task.py:27-32](file://backend/app/models/query_task.py#L27-L32)
@@ -340,7 +360,7 @@ QUERIES ||--o{ QUERY_TASKS : "拆分执行"
- DELETE /queries/{query_id} -> 204 No Content
- 参考路径：[查询 API:15-86](file://backend/app/api/queries.py#L15-L86)
-章节来源
+**章节来源**
- [backend/app/services/query.py:45-129](file://backend/app/services/query.py#L45-L129)
- [backend/app/api/queries.py:15-86](file://backend/app/api/queries.py#L15-L86)
@@ -361,13 +381,13 @@ BASE --> MODELS["模型类"]
MODELS --> DB["PostgreSQL"]
```
-图表来源
+**图表来源**
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
- [backend/app/config.py](file://backend/app/config.py#L7)
-章节来源
+**章节来源**
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
-- [backend/app/config.py:1-17](file://backend/app/config.py#L1-L17)
+- [backend/app/config.py:1-23](file://backend/app/config.py#L1-L23)
## 性能考量
- 索引设计
@@ -385,7 +405,7 @@ MODELS --> DB["PostgreSQL"]
## 故障排查指南
- 查询配额超限
- - 现象：创建查询时报错“PermissionError: Query limit exceeded”
+ - 现象：创建查询时报错"PermissionError: Query limit exceeded"
- 处理：检查用户 max_queries 与当前查询数量，必要时升级计划或清理历史查询。
- 参考路径：[创建查询服务:45-81](file://backend/app/services/query.py#L45-L81)
- 查询不存在
@@ -401,7 +421,7 @@ MODELS --> DB["PostgreSQL"]
- 处理：检查 error_message 字段；核对平台可用性与 API 密钥配置。
- 参考路径：[查询任务模型:11-39](file://backend/app/models/query_task.py#L11-L39)
-章节来源
+**章节来源**
- [backend/app/services/query.py:45-129](file://backend/app/services/query.py#L45-L129)
- [backend/app/api/queries.py:42-85](file://backend/app/api/queries.py#L42-L85)
- [backend/app/schemas/query.py:18-33](file://backend/app/schemas/query.py#L18-L33)
@@ -413,7 +433,11 @@ GEO 项目的数据模型围绕用户、查询、任务、引用记录与订阅
## 附录
- 数据库连接配置
- DATABASE_URL：PostgreSQL 异步连接字符串
- - 参考路径：[配置](file://backend/app/config.py#L7)
+ - 参考路径：[配置](file://backend/app/config.py#L12)
- 模型导出入口
- models/__init__.py 统一导出所有模型
- - 参考路径：[模型导出:1-14](file://backend/app/models/__init__.py#L1-L14)
\ No newline at end of file
+ - 参考路径：[模型导出:1-14](file://backend/app/models/__init__.py#L1-L14)
+- JWT 认证配置
+ - JWT_SECRET：JWT 密钥
+ - JWT_EXPIRE_HOURS：JWT 过期时间（小时）
+ - 参考路径：[认证依赖:16-43](file://backend/app/api/deps.py#L16-L43)
\ No newline at end of file
diff --git a/.qoder/repowiki/zh/content/测试策略/测试策略.md b/.qoder/repowiki/zh/content/测试策略/测试策略.md
index 101b7a3..f338bb2 100644
--- a/.qoder/repowiki/zh/content/测试策略/测试策略.md
+++ b/.qoder/repowiki/zh/content/测试策略/测试策略.md
@@ -4,13 +4,16 @@
**本文引用的文件**
- [tests/conftest.py](file://tests/conftest.py)
- [tests/test_auth.py](file://tests/test_auth.py)
+- [tests/test_business_flow.py](file://tests/test_business_flow.py)
- [tests/test_citation_engine.py](file://tests/test_citation_engine.py)
- [tests/test_citations.py](file://tests/test_citations.py)
- [tests/test_queries.py](file://tests/test_queries.py)
+- [tests/test_scheduler.py](file://tests/test_scheduler.py)
- [backend/app/main.py](file://backend/app/main.py)
- [backend/app/api/deps.py](file://backend/app/api/deps.py)
- [backend/app/services/auth.py](file://backend/app/services/auth.py)
- [backend/app/workers/citation_engine.py](file://backend/app/workers/citation_engine.py)
+- [backend/app/workers/scheduler.py](file://backend/app/workers/scheduler.py)
- [backend/app/api/auth.py](file://backend/app/api/auth.py)
- [backend/app/api/citations.py](file://backend/app/api/citations.py)
- [backend/app/api/queries.py](file://backend/app/api/queries.py)
@@ -18,20 +21,29 @@
- [backend/app/config.py](file://backend/app/config.py)
+## 更新摘要
+**变更内容**
+- 新增业务流程测试章节，涵盖端到端业务场景测试
+- 新增调度器测试章节，包括定时任务调度和频率计算测试
+- 完善测试最佳实践，增加业务流程测试和调度器测试的最佳实践指导
+- 更新测试策略以反映新增的测试覆盖范围
+
## 目录
1. [引言](#引言)
2. [项目结构](#项目结构)
3. [核心组件](#核心组件)
4. [架构总览](#架构总览)
5. [详细组件分析](#详细组件分析)
-6. [依赖分析](#依赖分析)
-7. [性能考虑](#性能考虑)
-8. [故障排查指南](#故障排查指南)
-9. [结论](#结论)
-10. [附录](#附录)
+6. [业务流程测试策略](#业务流程测试策略)
+7. [调度器测试策略](#调度器测试策略)
+8. [依赖分析](#依赖分析)
+9. [性能考虑](#性能考虑)
+10. [故障排查指南](#故障排查指南)
+11. [结论](#结论)
+12. [附录](#附录)
## 引言
-本测试策略文档面向GEO项目的Pytest测试体系，覆盖单元测试与集成测试的设计与实施要点。内容包括：测试夹具与模拟对象的组织方式、测试数据管理策略、认证模块、引用引擎、查询处理等关键功能的测试用例设计思路；同时给出测试最佳实践，包括覆盖率目标、持续集成配置建议以及测试环境管理方案，并提供调试技巧与性能测试方法。
+本测试策略文档面向GEO项目的Pytest测试体系，覆盖单元测试、集成测试和业务流程测试的设计与实施要点。内容包括：测试夹具与模拟对象的组织方式、测试数据管理策略、认证模块、引用引擎、查询处理、业务流程和调度器等关键功能的测试用例设计思路；同时给出测试最佳实践，包括覆盖率目标、持续集成配置建议以及测试环境管理方案，并提供调试技巧与性能测试方法。
## 项目结构
测试目录位于仓库根目录下的tests，采用按功能模块划分的组织方式，配合Pytest的conftest集中式夹具与模拟对象，确保测试隔离与可重复性。后端应用以FastAPI为核心，API层通过依赖注入获取当前用户与数据库会话，服务层封装业务逻辑，工作器(worker)负责异步任务与平台适配。
@@ -44,6 +56,8 @@ TA["tests/test_auth.py"]
TQ["tests/test_queries.py"]
TC["tests/test_citations.py"]
TCE["tests/test_citation_engine.py"]
+TB["tests/test_business_flow.py"]
+TS["tests/test_scheduler.py"]
end
subgraph "后端应用"
M["backend/app/main.py"]
@@ -54,15 +68,19 @@ AUTH_API["backend/app/api/auth.py"]
QUERIES_API["backend/app/api/queries.py"]
CITATIONS_API["backend/app/api/citations.py"]
CE["backend/app/workers/citation_engine.py"]
+QS["backend/app/workers/scheduler.py"]
end
C --> TA
C --> TQ
C --> TC
C --> TCE
+C --> TB
+C --> TS
TA --> AUTH_API
TQ --> QUERIES_API
TC --> CITATIONS_API
TCE --> CE
+TS --> QS
AUTH_API --> D
QUERIES_API --> D
CITATIONS_API --> D
@@ -73,19 +91,20 @@ M --> QUERIES_API
M --> CITATIONS_API
```
-图表来源
-- [tests/conftest.py:1-71](file://tests/conftest.py#L1-L71)
+**图表来源**
+- [tests/conftest.py:1-123](file://tests/conftest.py#L1-L123)
- [backend/app/main.py:1-48](file://backend/app/main.py#L1-L48)
- [backend/app/api/deps.py:1-43](file://backend/app/api/deps.py#L1-L43)
- [backend/app/api/auth.py:1-43](file://backend/app/api/auth.py#L1-L43)
- [backend/app/api/queries.py:1-86](file://backend/app/api/queries.py#L1-L86)
- [backend/app/api/citations.py:1-78](file://backend/app/api/citations.py#L1-L78)
- [backend/app/workers/citation_engine.py:1-309](file://backend/app/workers/citation_engine.py#L1-L309)
+- [backend/app/workers/scheduler.py:1-182](file://backend/app/workers/scheduler.py#L1-L182)
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
- [backend/app/config.py:1-17](file://backend/app/config.py#L1-L17)
-章节来源
-- [tests/conftest.py:1-71](file://tests/conftest.py#L1-L71)
+**章节来源**
+- [tests/conftest.py:1-123](file://tests/conftest.py#L1-L123)
- [backend/app/main.py:1-48](file://backend/app/main.py#L1-L48)
## 核心组件
@@ -94,14 +113,17 @@ M --> CITATIONS_API
- 用户与令牌：提供模拟用户对象、JWT访问令牌及请求头，便于认证相关接口测试。
- 异步HTTP客户端：基于ASGI传输创建异步HTTP客户端，用于端到端API测试。
- 依赖覆盖：通过依赖注入覆盖当前用户解析逻辑，简化认证流程。
+ - 内存数据库：使用SQLite内存数据库进行集成测试，确保测试隔离性。
- 测试数据管理
- 使用pytest fixture生成模拟模型对象（如查询、引用记录），保证测试数据一致性与可读性。
- 通过patch对服务层函数进行桩替，隔离外部依赖，提升测试确定性。
+ - 直接操作数据库模型进行复杂场景测试，如权限隔离和统计计算。
- 测试运行与并发
- 使用pytest-asyncio标记异步测试，确保事件循环正确初始化与清理。
+ - 支持并行执行多个测试文件，提高测试执行效率。
-章节来源
-- [tests/conftest.py:19-71](file://tests/conftest.py#L19-L71)
+**章节来源**
+- [tests/conftest.py:19-123](file://tests/conftest.py#L19-L123)
## 架构总览
下图展示了测试与被测系统的交互关系：测试通过异步HTTP客户端直接调用FastAPI路由，路由依赖当前用户与数据库会话，服务层完成业务逻辑，工作器负责平台查询与品牌匹配。
@@ -135,8 +157,8 @@ APP-->>AC : 序列化响应
AC-->>T : 断言结果
```
-图表来源
-- [tests/conftest.py:65-71](file://tests/conftest.py#L65-L71)
+**图表来源**
+- [tests/conftest.py:117-123](file://tests/conftest.py#L117-L123)
- [backend/app/main.py:38-42](file://backend/app/main.py#L38-L42)
- [backend/app/api/deps.py:16-43](file://backend/app/api/deps.py#L16-L43)
- [backend/app/api/auth.py:13-43](file://backend/app/api/auth.py#L13-L43)
@@ -186,13 +208,13 @@ AUTH-->>AC : 200/401
AC-->>T : 断言
```
-图表来源
+**图表来源**
- [tests/test_auth.py:25-104](file://tests/test_auth.py#L25-L104)
- [backend/app/api/auth.py:13-43](file://backend/app/api/auth.py#L13-L43)
- [backend/app/services/auth.py:37-69](file://backend/app/services/auth.py#L37-L69)
- [backend/app/api/deps.py:16-43](file://backend/app/api/deps.py#L16-L43)
-章节来源
+**章节来源**
- [tests/test_auth.py:1-104](file://tests/test_auth.py#L1-L104)
- [backend/app/api/auth.py:1-43](file://backend/app/api/auth.py#L1-L43)
- [backend/app/services/auth.py:1-69](file://backend/app/services/auth.py#L1-L69)
@@ -231,13 +253,13 @@ BrandMatcher <.. CitationEngine : "使用"
CompetitorDetector <.. CitationEngine : "使用"
```
-图表来源
+**图表来源**
- [backend/app/workers/citation_engine.py:19-120](file://backend/app/workers/citation_engine.py#L19-L120)
- [backend/app/workers/citation_engine.py:122-146](file://backend/app/workers/citation_engine.py#L122-L146)
- [backend/app/workers/citation_engine.py:148-309](file://backend/app/workers/citation_engine.py#L148-L309)
-章节来源
-- [tests/test_citation_engine.py:1-54](file://tests/test_citation_engine.py#L1-L54)
+**章节来源**
+- [tests/test_citation_engine.py:1-127](file://tests/test_citation_engine.py#L1-L127)
- [backend/app/workers/citation_engine.py:1-309](file://backend/app/workers/citation_engine.py#L1-L309)
### 引用数据与报告测试策略
@@ -279,11 +301,11 @@ REP-->>AC : 200 + text/csv + attachment
AC-->>T : 断言
```
-图表来源
+**图表来源**
- [tests/test_citations.py:23-93](file://tests/test_citations.py#L23-L93)
- [backend/app/api/citations.py:25-78](file://backend/app/api/citations.py#L25-L78)
-章节来源
+**章节来源**
- [tests/test_citations.py:1-93](file://tests/test_citations.py#L1-L93)
- [backend/app/api/citations.py:1-78](file://backend/app/api/citations.py#L1-L78)
@@ -333,22 +355,140 @@ Q-->>AC : 204/404
AC-->>T : 断言
```
-图表来源
+**图表来源**
- [tests/test_queries.py:29-154](file://tests/test_queries.py#L29-L154)
- [backend/app/api/queries.py:15-86](file://backend/app/api/queries.py#L15-L86)
-章节来源
+**章节来源**
- [tests/test_queries.py:1-154](file://tests/test_queries.py#L1-L154)
- [backend/app/api/queries.py:1-86](file://backend/app/api/queries.py#L1-L86)
+## 业务流程测试策略
+
+### 测试目标
+业务流程测试旨在验证GEO应用的核心业务场景，包括用户完整注册登录流程、查询词生命周期管理、权限隔离机制、配额限制控制、统计计算准确性以及CSV导出功能。
+
+### 关键测试场景
+- **完整用户流程**：从注册到登录再到查询管理的端到端流程
+- **查询生命周期**：创建、更新、暂停、恢复、删除的完整生命周期
+- **权限隔离**：确保用户间数据完全隔离
+- **配额限制**：免费用户的查询数量限制验证
+- **统计准确性**：引用统计数据的正确性验证
+- **CSV导出**：导出功能的完整性测试
+
+### 测试实现策略
+- **用户管理**：通过fixture创建真实用户账户，模拟完整的用户生命周期
+- **权限测试**：使用两个独立用户账户验证权限隔离机制
+- **数据验证**：直接操作数据库模型验证统计计算的准确性
+- **端到端验证**：通过异步HTTP客户端验证完整的业务流程
+
+```mermaid
+sequenceDiagram
+participant T as "业务流程测试"
+participant AC as "异步HTTP客户端"
+participant AUTH as "认证路由"
+participant QUERIES as "查询路由"
+participant CITATIONS as "引用路由"
+participant DB as "数据库"
+T->>AC : 注册用户
+AC->>AUTH : POST /api/v1/auth/register
+AUTH->>DB : 创建用户记录
+AUTH-->>AC : 201 Created
+T->>AC : 登录用户
+AC->>AUTH : POST /api/v1/auth/login
+AUTH-->>AC : 200 OK + Token
+T->>AC : 创建查询
+AC->>QUERIES : POST /api/v1/queries/
+QUERIES->>DB : 创建查询记录
+QUERIES-->>AC : 201 Created
+T->>AC : 验证统计
+AC->>CITATIONS : GET /api/v1/citations/stats
+CITATIONS->>DB : 查询引用记录
+CITATIONS-->>AC : 200 OK + 统计数据
+AC-->>T : 断言业务流程正确性
+```
+
+**图表来源**
+- [tests/test_business_flow.py:83-126](file://tests/test_business_flow.py#L83-L126)
+- [tests/test_business_flow.py:131-186](file://tests/test_business_flow.py#L131-L186)
+- [tests/test_business_flow.py:192-222](file://tests/test_business_flow.py#L192-L222)
+- [tests/test_business_flow.py:228-296](file://tests/test_business_flow.py#L228-L296)
+
+### 测试用例设计要点
+- **用户隔离**：使用独立fixture创建多个用户，确保权限测试的准确性
+- **数据完整性**：通过直接操作数据库模型验证统计计算的正确性
+- **流程完整性**：覆盖业务流程的所有关键节点和异常场景
+- **边界条件**：测试配额限制、权限边界等关键边界条件
+
+**章节来源**
+- [tests/test_business_flow.py:1-441](file://tests/test_business_flow.py#L1-L441)
+
+## 调度器测试策略
+
+### 测试目标
+调度器测试专注于验证查询调度器的定时任务执行能力，包括调度器的启动/关闭、查询任务筛选机制、频率计算逻辑以及遗留任务处理功能。
+
+### 关键测试场景
+- **调度器生命周期**：启动、正常运行和优雅关闭
+- **查询筛选机制**：仅执行活跃且到期的查询任务
+- **频率计算**：daily和weekly频率的next_query_at计算
+- **遗留任务处理**：处理超过1分钟未执行的pending任务
+- **异常处理**：查询执行失败时的异常处理和日志记录
+
+### 测试实现策略
+- **调度器控制**：通过patch替换真实的APScheduler，使用AsyncMock控制调度器行为
+- **数据库隔离**：使用独立的测试会话，确保调度器测试不影响其他测试
+- **时间控制**：通过精确的时间戳控制查询的到期状态
+- **频率验证**：使用datetime.utcnow()进行精确的时间计算验证
+
+```mermaid
+classDiagram
+class QueryScheduler {
++start() void
++check_and_execute_queries() void
++check_and_execute_pending_tasks() void
++shutdown() void
+-_run_check() void
+-_run_pending_tasks_check() void
+-_execute_single_query(query, db) void
+}
+class CitationEngine {
++execute_query(query, db) list
++execute_single_platform(keyword, platform, target_brand, brand_aliases) dict
+}
+class AsyncIOScheduler {
++add_job(job, trigger, id, name) void
++start() void
++shutdown() void
+}
+QueryScheduler --> CitationEngine : "调用"
+QueryScheduler --> AsyncIOScheduler : "使用"
+```
+
+**图表来源**
+- [backend/app/workers/scheduler.py:27-182](file://backend/app/workers/scheduler.py#L27-L182)
+
+### 测试用例设计要点
+- **调度器生命周期**：验证调度器启动时添加的定时任务和名称
+- **查询筛选**：通过创建不同状态和到期时间的查询验证筛选逻辑
+- **频率计算**：使用绝对误差容差验证next_query_at的计算精度
+- **遗留任务处理**：验证pending任务的兜底处理机制
+- **异常处理**：确保查询执行失败时不会中断整个调度流程
+
+**章节来源**
+- [tests/test_scheduler.py:1-123](file://tests/test_scheduler.py#L1-L123)
+- [backend/app/workers/scheduler.py:1-182](file://backend/app/workers/scheduler.py#L1-L182)
+
## 依赖分析
- 测试与被测模块耦合
- 测试通过ASGI传输直接调用路由，避免引入额外适配层
- 通过依赖覆盖与patch解耦服务层与数据库、第三方平台
+ - 业务流程测试直接操作数据库模型，确保测试数据的准确性
- 外部依赖与集成点
- 数据库：通过异步引擎与会话管理，测试中可使用内存数据库或独立测试库
- JWT：通过服务层令牌生成与校验，测试中直接构造令牌头
- 平台适配器：通过patch替换，避免真实网络请求
+ - 调度器：通过patch替换真实的APScheduler，使用AsyncMock控制调度行为
- 循环依赖与风险
- 当前结构清晰，无明显循环依赖；注意在测试中避免对真实调度器的依赖
@@ -357,26 +497,32 @@ graph LR
T_AUTH["测试: 认证"] --> A_AUTH["路由: 认证"]
T_QUERIES["测试: 查询"] --> A_QUERIES["路由: 查询"]
T_CIT["测试: 引用"] --> A_CIT["路由: 引用"]
+T_BUSINESS["测试: 业务流程"] --> A_QUERIES
+T_BUSINESS --> A_CIT
+T_SCHED["测试: 调度器"] --> QS["调度器: QueryScheduler"]
A_AUTH --> S_AUTH["服务: 认证"]
A_QUERIES --> S_QUERY["服务: 查询"]
A_CIT --> S_CIT["服务: 引用"]
S_AUTH --> DB["数据库"]
S_QUERY --> DB
S_CIT --> DB
+QS --> CE["引擎: CitationEngine"]
+QS --> DB
DB --> CFG["配置"]
```
-图表来源
+**图表来源**
- [tests/test_auth.py:1-104](file://tests/test_auth.py#L1-L104)
-- [tests/test_queries.py:1-154](file://tests/test_queries.py#L1-L154)
-- [tests/test_citations.py:1-93](file://tests/test_citations.py#L1-L93)
+- [tests/test_business_flow.py:1-441](file://tests/test_business_flow.py#L1-L441)
+- [tests/test_scheduler.py:1-123](file://tests/test_scheduler.py#L1-L123)
- [backend/app/api/auth.py:1-43](file://backend/app/api/auth.py#L1-L43)
- [backend/app/api/queries.py:1-86](file://backend/app/api/queries.py#L1-L86)
- [backend/app/api/citations.py:1-78](file://backend/app/api/citations.py#L1-L78)
+- [backend/app/workers/scheduler.py:1-182](file://backend/app/workers/scheduler.py#L1-L182)
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
- [backend/app/config.py:1-17](file://backend/app/config.py#L1-L17)
-章节来源
+**章节来源**
- [backend/app/database.py:1-29](file://backend/app/database.py#L1-L29)
- [backend/app/config.py:1-17](file://backend/app/config.py#L1-L17)
@@ -384,29 +530,37 @@ DB --> CFG["配置"]
- 测试并发与资源
- 使用pytest-asyncio并行执行异步测试，减少总耗时
- 通过会话级调度器模拟避免真实后台任务带来的不稳定因素
+ - 业务流程测试使用内存数据库，避免磁盘I/O开销
- 数据库与缓存
- 建议使用独立测试数据库实例，避免与开发/生产数据冲突
- 对高频查询场景，可在测试中模拟数据库延迟，评估路由与服务层的超时与重试策略
+ - 调度器测试使用AsyncMock，避免真实的定时任务执行
- 接口响应与序列化
- 对大列表与统计聚合接口，关注JSON序列化开销与分页参数边界
+ - 业务流程测试中直接操作数据库模型，避免不必要的API调用
- 平台适配器性能
- 通过patch模拟不同响应时延与错误率，评估引擎的容错与降级策略
+ - 调度器测试中使用精确的时间控制，避免真实的等待时间
## 故障排查指南
- 常见问题定位
- 认证失败：检查令牌生成与头设置、依赖覆盖是否生效
- 404查询：确认查询ID与用户归属，检查服务层查询逻辑
- 403配额：检查服务层权限异常抛出与HTTP状态映射
+ - 调度器异常：检查APScheduler的启动状态和job配置
+ - 业务流程失败：检查数据库事务和fixture的使用
- 调试技巧
- 在conftest中临时打印依赖解析过程，定位get_current_user解析失败原因
- 使用pytest的-v与-s选项查看详细输出，结合patch的side_effect观察异常传播
- 对数据库相关测试，开启SQLAlchemy echo以查看生成的SQL
+ - 调度器测试中使用AsyncMock的assert_called_once()验证调度器行为
- 性能与稳定性
- 对于长时间运行的异步测试，确保事件循环正确关闭
- 对需要真实网络请求的场景，优先使用patch模拟，必要时增加超时与重试
+ - 业务流程测试中合理使用fixture，避免重复创建昂贵的对象
## 结论
-本测试策略以Pytest为核心，结合会话级调度器模拟、依赖覆盖与patch技术，实现了对认证、查询、引用与引擎模块的全面覆盖。通过明确的夹具与测试数据管理，确保测试的可维护性与可重复性。建议在CI中启用并行执行与覆盖率统计，并为数据库与平台适配器建立稳定的模拟层，持续提升测试效率与质量。
+本测试策略以Pytest为核心，结合会话级调度器模拟、依赖覆盖与patch技术，实现了对认证、查询、引用、引擎模块以及业务流程和调度器的全面覆盖。通过明确的夹具与测试数据管理，确保测试的可维护性与可重复性。新增的业务流程测试和调度器测试进一步完善了测试体系，涵盖了端到端业务场景和定时任务调度的关键功能。建议在CI中启用并行执行与覆盖率统计，并为数据库与平台适配器建立稳定的模拟层，持续提升测试效率与质量。
## 附录
- 测试覆盖率要求建议
@@ -414,12 +568,18 @@ DB --> CFG["配置"]
- 分支覆盖率：≥70%
- 行覆盖率：≥80%
- 函数/方法覆盖率：≥90%
+ - 业务流程覆盖率：≥95%
+ - 调度器覆盖率：≥90%
- 持续集成配置建议
- 使用GitHub Actions或GitLab CI，包含Python版本矩阵、依赖安装、数据库准备、pytest执行与覆盖率上传
- 将测试与lint、类型检查并行，确保主干分支质量
+ - 为业务流程测试和调度器测试单独配置执行时间限制
- 测试环境管理
- 使用独立测试数据库与Redis实例，避免污染
- 通过环境变量切换测试配置，确保敏感信息不泄露
+ - 业务流程测试使用内存数据库，调度器测试使用AsyncMock
- 性能测试方法
- 使用pytest-benchmark或locust对高频路由进行基准测试
- - 对引擎执行流程进行压力测试，评估平台适配器与数据库写入瓶颈
\ No newline at end of file
+ - 对引擎执行流程进行压力测试，评估平台适配器与数据库写入瓶颈
+ - 调度器测试中使用时间控制和AsyncMock，避免真实的定时等待
+ - 业务流程测试中评估端到端流程的响应时间和吞吐量
\ No newline at end of file
diff --git a/.qoder/repowiki/zh/meta/repowiki-metadata.json b/.qoder/repowiki/zh/meta/repowiki-metadata.json
index 48250d1..ee8b041 100644
--- a/.qoder/repowiki/zh/meta/repowiki-metadata.json
+++ b/.qoder/repowiki/zh/meta/repowiki-metadata.json
@@ -1 +1 @@
-{"knowledge_relations":[{"id":1,"source_id":"34e572eb-6fc8-4de7-8061-63783ef8be24","target_id":"2793782c-91c8-4052-b9db-39513426c736","source_type":"WIKI_ITEM","target_type":"WIKI_ITEM","relationship_type":"PARENT_CHILD","extra":"Wiki parent-child relationship: 34e572eb-6fc8-4de7-8061-63783ef8be24 -\u003e 2793782c-91c8-4052-b9db-39513426c736","gmt_create":"2026-04-22T19:25:18.918463+08:00","gmt_modified":"2026-04-22T19:25:18.918463+08:00"},{"id":2,"source_id":"34e572eb-6fc8-4de7-8061-63783ef8be24","target_id":"e23bd86e-b4ac-40eb-b1c1-38d929fd5419","source_type":"WIKI_ITEM","target_type":"WIKI_ITEM","relationship_type":"PARENT_CHILD","extra":"Wiki parent-child relationship: 34e572eb-6fc8-4de7-8061-63783ef8be24 -\u003e 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GEO 平台项目全面分析\n\n## 1. 项目介绍\n\n### 目标与愿景\nGEO 平台是一个基于人工智能技术的学术查询与引用管理系统，旨在为用户提供智能化的品牌引用检测和数据分析服务。该项目通过集成多个AI平台，实现对网络内容中特定品牌引用的自动检测和统计分析。\n\n### 核心目标\n- **智能引用检测**：自动识别网络内容中对特定品牌的引用情况\n- **多平台集成**：支持多个AI平台的数据获取和处理\n- **实时监控**：提供定时查询和实时更新功能\n- **数据可视化**：通过图表展示引用趋势和统计数据\n\n### 目标用户\n- 学术研究人员\n- 市场分析师\n- 品牌监测机构\n- 内容创作者\n\n## 2. 技术架构\n\n### 整体架构设计\n\n```mermaid\ngraph TB\n subgraph \"前端层\"\n FE[Next.js 前端]\n UI[React 组件]\n Auth[认证系统]\n end\n \n subgraph \"后端层\"\n API[FastAPI API]\n WS[工作器]\n SCH[调度器]\n end\n \n subgraph \"数据层\"\n DB[(PostgreSQL)]\n RD[Redis 缓存]\n end\n \n subgraph \"AI平台\"\n WX[Wenxin 平台]\n KM[Kimi 平台]\n end\n \n FE --\u003e API\n UI --\u003e FE\n Auth --\u003e FE\n API --\u003e DB\n API --\u003e RD\n WS --\u003e WX\n WS --\u003e KM\n SCH --\u003e WS\n API --\u003e WS\n```\n\n### 核心设计模式\n- **分层架构**：清晰的前后端分离和业务逻辑分层\n- **异步编程**：基于 asyncio 的高性能异步处理\n- **依赖注入**：通过 FastAPI 的依赖系统管理服务\n- **适配器模式**：统一不同AI平台的接口调用\n\n### 系统关系图\n\n```mermaid\nsequenceDiagram\n participant U as 用户\n participant F as 前端\n participant B as 后端API\n participant S as 调度器\n participant W as 引用引擎\n participant P as AI平台\n \n U-\u003e\u003eF: 发起查询请求\n F-\u003e\u003eB: HTTP请求\n B-\u003e\u003eS: 触发查询任务\n S-\u003e\u003eW: 执行查询\n W-\u003e\u003eP: 调用AI平台\n P--\u003e\u003eW: 返回结果\n W--\u003e\u003eB: 处理后的数据\n B--\u003e\u003eF: 响应结果\n F--\u003e\u003eU: 展示数据\n```\n\n## 3. 关键实现\n\n### 主要入口点\n\n**后端主入口**\n- `backend/app/main.py` - FastAPI 应用主入口，包含路由注册和中间件配置\n\n**前端主入口**\n- `frontend/app/layout.tsx` - Next.js 应用布局组件，包含全局样式和提供者配置\n\n### 核心模块\n\n**数据库配置**\n- `backend/app/database.py` - SQLAlchemy 异步数据库配置和会话管理\n\n**配置管理**\n- `backend/app/config.py` - Pydantic 设置类，管理环境变量和配置参数\n\n**工作器系统**\n- `backend/app/workers/scheduler.py` - APScheduler 定时任务调度器\n- `backend/app/workers/citation_engine.py` - 引用检测引擎核心\n\n**API 路由**\n- `backend/app/api/auth.py` - 用户认证相关接口\n- `backend/app/api/citations.py` - 引用数据相关接口\n- `backend/app/api/queries.py` - 查询任务相关接口\n\n### 配置方法\n\n**Docker 配置**\n- `docker-compose.yml` - 多容器部署配置，包含数据库、缓存和应用服务\n\n**依赖管理**\n- `backend/requirements.txt` - Python 后端依赖包\n- `frontend/package.json` - Node.js 前端依赖包\n\n### 外部依赖\n\n**后端关键技术栈**\n- FastAPI + Uvicorn：高性能异步Web框架\n- SQLAlchemy 2.0：异步ORM框架\n- APScheduler：任务调度框架\n- Redis：缓存和队列存储\n- Playwright：浏览器自动化\n\n**前端关键技术栈**\n- Next.js 14：React 框架\n- Radix UI：可访问性UI组件库\n- Recharts：数据可视化图表\n- Tailwind CSS：CSS框架\n\n### 集成点\n\n**AI平台适配**\n- `backend/app/workers/platforms/kimi.py` - Kimi AI平台适配器\n- `backend/app/workers/platforms/wenxin.py` - 百度文心平台适配器\n\n**认证集成**\n- `frontend/components/providers.tsx` - NextAuth.js 认证提供者\n- `frontend/lib/auth.ts` - 前端认证工具函数\n\n### 组件关系图\n\n```mermaid\ngraph LR\n subgraph \"认证模块\"\n AUTH_API[认证API]\n AUTH_FE[认证前端]\n NEXT_AUTH[NextAuth集成]\n end\n \n subgraph \"查询模块\"\n QUERY_API[查询API]\n QUERY_FE[查询前端]\n SCHEDULER[调度器]\n ENGINE[引用引擎]\n end\n \n subgraph \"数据模块\"\n MODELS[数据模型]\n DB[(数据库)]\n REDIS[(Redis)]\n end\n \n AUTH_API --\u003e MODELS\n QUERY_API --\u003e MODELS\n ENGINE --\u003e MODELS\n AUTH_FE --\u003e AUTH_API\n QUERY_FE --\u003e QUERY_API\n SCHEDULER --\u003e ENGINE\n ENGINE --\u003e DB\n ENGINE --\u003e REDIS\n AUTH_API --\u003e DB\n QUERY_API --\u003e DB\n```\n\n## 4. 核心功能\n\n### 功能概览\n\n**用户管理功能**\n- 用户注册和登录认证\n- JWT 令牌管理和会话维护\n- 用户权限控制\n\n**查询管理功能**\n- 自定义关键词查询\n- 多平台AI数据获取\n- 定时任务调度\n- 查询历史记录\n\n**引用检测功能**\n- 品牌引用自动检测\n- 置信度评分算法\n- 竞争品牌识别\n- 文本上下文提取\n\n**数据分析功能**\n- 引用趋势图表\n- 平台对比分析\n- 统计报表生成\n\n### 实现亮点\n\n**智能匹配算法**\n- `backend/app/workers/citation_engine.py` - 实现精确匹配、别名匹配和模糊匹配三种策略\n- 支持中文和英文混合文本处理\n- 提供置信度评分和位置信息\n\n**异步任务处理**\n- `backend/app/workers/scheduler.py` - 基于 APScheduler 的异步任务调度\n- 支持多平台并发查询\n- 完善的任务状态跟踪\n\n**响应式前端界面**\n- `frontend/app/(dashboard)/` - Next.js App Router 页面组织\n- `frontend/components/charts/` - 数据可视化组件\n- `frontend/components/ui/` - 可复用UI组件库\n\n### 功能架构图\n\n```mermaid\nstateDiagram-v2\n [*] --\u003e 用户认证\n 用户认证 --\u003e 查询管理: 登录成功\n 查询管理 --\u003e 任务调度: 创建查询\n 任务调度 --\u003e 引用检测: 定时触发\n 引用检测 --\u003e 数据处理: 获取AI结果\n 数据处理 --\u003e 结果展示: 处理完成\n 结果展示 --\u003e 查询管理: 新查询\n 结果展示 --\u003e [*]: 退出系统\n \n state 查询管理 {\n [*] --\u003e 创建查询\n 创建查询 --\u003e 编辑查询\n 编辑查询 --\u003e 删除查询\n 删除查询 --\u003e [*]\n }\n \n state 引用检测 {\n [*] --\u003e 平台查询\n 平台查询 --\u003e 品牌匹配\n 品牌匹配 --\u003e 竞争检测\n 竞争检测 --\u003e [*]\n }\n```\n\n## 5. 总结与建议\n\n### 项目架构特点\n\n**架构优势**\n- 清晰的分层设计，前后端职责明确\n- 异步编程模型提升了系统性能\n- 模块化设计便于功能扩展和维护\n- 完善的错误处理和日志记录机制\n\n**技术亮点**\n- 基于现代技术栈的全栈开发\n- 智能算法与工程实践的结合\n- 完整的开发到部署流程\n- 良好的代码组织和文档规范\n\n### 改进建议\n\n**性能优化**\n- 考虑引入连接池优化数据库连接\n- 实现缓存策略减少重复查询\n- 添加限流机制防止API滥用\n\n**功能扩展**\n- 增加更多AI平台支持\n- 实现批量查询功能\n- 添加导出数据功能\n- 增强搜索过滤条件\n\n**代码质量**\n- 完善单元测试覆盖率\n- 添加API文档自动生成\n- 实现更详细的错误处理\n- 优化前端组件复用性\n\n### 下一步发展\n\n**短期目标**\n- 完善用户认证和权限系统\n- 优化引用检测算法准确性\n- 增强前端用户体验\n\n**长期规划**\n- 支持多语言和国际化\n- 实现移动端应用\n- 添加机器学习模型优化\n- 构建开发者API平台\n\nSources:\n- [main.py](backend/app/main.py)\n- [config.py](backend/app/config.py)\n- [database.py](backend/app/database.py)\n- [layout.tsx](frontend/app/layout.tsx)\n- [providers.tsx](frontend/components/providers.tsx)\n- [scheduler.py](backend/app/workers/scheduler.py)\n- [citation_engine.py](backend/app/workers/citation_engine.py)\n- [auth.py](backend/app/api/auth.py)\n- [docker-compose.yml](docker-compose.yml)\n- [requirements.txt](backend/requirements.txt)\n- [package.json](frontend/package.json)\n\n\u003c/blog\u003e","gmt_create":"2026-04-22T18:54:45.079999+08:00","gmt_modified":"2026-04-22T18:54:45.079999+08:00","id":"1e2d007d-9249-436e-8822-c9b1a31580d1","repo_id":"1095f823-f6f5-4e66-9aad-9f0b5b6b99d1"},"wiki_readme":{"content":"No readme file","gmt_create":"2026-04-22T18:53:55.057287+08:00","gmt_modified":"2026-04-22T18:53:55.057287+08:00","id":"354aa9f0-35fb-44a7-98d6-034981f130e6","repo_id":"1095f823-f6f5-4e66-9aad-9f0b5b6b99d1"},"wiki_repo":{"id":"1095f823-f6f5-4e66-9aad-9f0b5b6b99d1","name":"GEO","progress_status":"completed","wiki_present_status":"COMPLETED","optimized_catalog":"\".\\n├── .npm-cache/\\n│ ├── _cacache/\\n│ ├── _logs/\\n│ └── _npx/\\n├── .pytest_cache/\\n├── backend/\\n│ ├── alembic/\\n│ │ ├── __pycache__/\\n│ │ ├── versions/\\n│ │ │ ├── __pycache__/\\n│ │ │ └── 488d0bd5ab01_initial_migration.py\\n│ │ ├── README\\n│ │ ├── env.py\\n│ │ └── script.py.mako\\n│ ├── app/\\n│ │ ├── __pycache__/\\n│ │ ├── api/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── __init__.py\\n│ │ │ ├── auth.py\\n│ │ │ ├── citations.py\\n│ │ │ ├── deps.py\\n│ │ │ ├── queries.py\\n│ │ │ └── reports.py\\n│ │ ├── models/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── __init__.py\\n│ │ │ ├── citation_record.py\\n│ │ │ ├── query.py\\n│ │ │ ├── query_task.py\\n│ │ │ ├── subscription.py\\n│ │ │ └── user.py\\n│ │ ├── schemas/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── auth.py\\n│ │ │ ├── citation.py\\n│ │ │ └── query.py\\n│ │ ├── services/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── auth.py\\n│ │ │ ├── citation.py\\n│ │ │ └── query.py\\n│ │ ├── utils/\\n│ │ ├── workers/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── platforms/\\n│ │ │ │ ├── __pycache__/\\n│ │ │ │ ├── base.py\\n│ │ │ │ ├── kimi.py\\n│ │ │ │ └── wenxin.py\\n│ │ │ ├── __init__.py\\n│ │ │ ├── citation_engine.py\\n│ │ │ └── scheduler.py\\n│ │ ├── config.py\\n│ │ ├── database.py\\n│ │ └── main.py\\n│ ├── venv/\\n│ ├── Dockerfile\\n│ ├── alembic.ini\\n│ └── requirements.txt\\n├── docs/\\n├── frontend/\\n│ ├── .next/\\n│ ├── app/\\n│ │ ├── (auth)/\\n│ │ │ ├── login/\\n│ │ │ │ └── page.tsx\\n│ │ │ ├── register/\\n│ │ │ │ └── page.tsx\\n│ │ │ └── layout.tsx\\n│ │ ├── (dashboard)/\\n│ │ │ ├── dashboard/\\n│ │ │ │ ├── citations/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ ├── queries/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ ├── reports/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ ├── settings/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ └── page.tsx\\n│ │ │ └── layout.tsx\\n│ │ ├── api/auth/[...nextauth]/\\n│ │ │ └── route.ts\\n│ │ ├── fonts/\\n│ │ ├── globals.css\\n│ │ ├── layout.tsx\\n│ │ └── page.tsx\\n│ ├── components/\\n│ │ ├── charts/\\n│ │ │ ├── platform-chart.tsx\\n│ │ │ └── trend-chart.tsx\\n│ │ ├── layout/\\n│ │ │ ├── header.tsx\\n│ │ │ └── sidebar.tsx\\n│ │ ├── ui/\\n│ │ │ ├── badge.tsx\\n│ │ │ ├── button.tsx\\n│ │ │ ├── card.tsx\\n│ │ │ ├── dialog.tsx\\n│ │ │ ├── dropdown-menu.tsx\\n│ │ │ ├── input.tsx\\n│ │ │ ├── label.tsx\\n│ │ │ ├── select.tsx\\n│ │ │ ├── table.tsx\\n│ │ │ └── tabs.tsx\\n│ │ └── providers.tsx\\n│ ├── lib/\\n│ │ ├── api.ts\\n│ │ ├── auth.ts\\n│ │ ├── platforms.ts\\n│ │ └── utils.ts\\n│ ├── node_modules/\\n│ ├── types/\\n│ │ └── next-auth.d.ts\\n│ ├── .eslintrc.json\\n│ ├── .gitignore\\n│ ├── Dockerfile\\n│ ├── README.md\\n│ ├── next-env.d.ts\\n│ ├── next.config.mjs\\n│ ├── package-lock.json\\n│ ├── package.json\\n│ ├── postcss.config.mjs\\n│ ├── tailwind.config.ts\\n│ ├── tsconfig.json\\n│ └── tsconfig.tsbuildinfo\\n├── tests/\\n│ ├── __pycache__/\\n│ ├── conftest.py\\n│ ├── test_auth.py\\n│ ├── test_citation_engine.py\\n│ ├── test_citations.py\\n│ └── test_queries.py\\n└── docker-compose.yml\\n\"","current_document_structure":"WikiEncrypted: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","catalogue_think_content":"WikiEncrypted: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GEO 平台项目全面分析\n\n## 1. 项目介绍\n\n### 目标与愿景\nGEO 平台是一个基于人工智能技术的学术查询与引用管理系统，旨在为用户提供智能化的品牌引用检测和数据分析服务。该项目通过集成多个AI平台，实现对网络内容中特定品牌引用的自动检测和统计分析。\n\n### 核心目标\n- **智能引用检测**：自动识别网络内容中对特定品牌的引用情况\n- **多平台集成**：支持多个AI平台的数据获取和处理\n- **实时监控**：提供定时查询和实时更新功能\n- **数据可视化**：通过图表展示引用趋势和统计数据\n\n### 目标用户\n- 学术研究人员\n- 市场分析师\n- 品牌监测机构\n- 内容创作者\n\n## 2. 技术架构\n\n### 整体架构设计\n\n```mermaid\ngraph TB\n subgraph \"前端层\"\n FE[Next.js 前端]\n UI[React 组件]\n Auth[认证系统]\n end\n \n subgraph \"后端层\"\n API[FastAPI API]\n WS[工作器]\n SCH[调度器]\n end\n \n subgraph \"数据层\"\n DB[(PostgreSQL)]\n RD[Redis 缓存]\n end\n \n subgraph \"AI平台\"\n WX[Wenxin 平台]\n KM[Kimi 平台]\n end\n \n FE --\u003e API\n UI --\u003e FE\n Auth --\u003e FE\n API --\u003e DB\n API --\u003e RD\n WS --\u003e WX\n WS --\u003e KM\n SCH --\u003e WS\n API --\u003e WS\n```\n\n### 核心设计模式\n- **分层架构**：清晰的前后端分离和业务逻辑分层\n- **异步编程**：基于 asyncio 的高性能异步处理\n- **依赖注入**：通过 FastAPI 的依赖系统管理服务\n- **适配器模式**：统一不同AI平台的接口调用\n\n### 系统关系图\n\n```mermaid\nsequenceDiagram\n participant U as 用户\n participant F as 前端\n participant B as 后端API\n participant S as 调度器\n participant W as 引用引擎\n participant P as AI平台\n \n U-\u003e\u003eF: 发起查询请求\n F-\u003e\u003eB: HTTP请求\n B-\u003e\u003eS: 触发查询任务\n S-\u003e\u003eW: 执行查询\n W-\u003e\u003eP: 调用AI平台\n P--\u003e\u003eW: 返回结果\n W--\u003e\u003eB: 处理后的数据\n B--\u003e\u003eF: 响应结果\n F--\u003e\u003eU: 展示数据\n```\n\n## 3. 关键实现\n\n### 主要入口点\n\n**后端主入口**\n- `backend/app/main.py` - FastAPI 应用主入口，包含路由注册和中间件配置\n\n**前端主入口**\n- `frontend/app/layout.tsx` - Next.js 应用布局组件，包含全局样式和提供者配置\n\n### 核心模块\n\n**数据库配置**\n- `backend/app/database.py` - SQLAlchemy 异步数据库配置和会话管理\n\n**配置管理**\n- `backend/app/config.py` - Pydantic 设置类，管理环境变量和配置参数\n\n**工作器系统**\n- `backend/app/workers/scheduler.py` - APScheduler 定时任务调度器\n- `backend/app/workers/citation_engine.py` - 引用检测引擎核心\n\n**API 路由**\n- `backend/app/api/auth.py` - 用户认证相关接口\n- `backend/app/api/citations.py` - 引用数据相关接口\n- `backend/app/api/queries.py` - 查询任务相关接口\n\n### 配置方法\n\n**Docker 配置**\n- `docker-compose.yml` - 多容器部署配置，包含数据库、缓存和应用服务\n\n**依赖管理**\n- `backend/requirements.txt` - Python 后端依赖包\n- `frontend/package.json` - Node.js 前端依赖包\n\n### 外部依赖\n\n**后端关键技术栈**\n- FastAPI + Uvicorn：高性能异步Web框架\n- SQLAlchemy 2.0：异步ORM框架\n- APScheduler：任务调度框架\n- Redis：缓存和队列存储\n- Playwright：浏览器自动化\n\n**前端关键技术栈**\n- Next.js 14：React 框架\n- Radix UI：可访问性UI组件库\n- Recharts：数据可视化图表\n- Tailwind CSS：CSS框架\n\n### 集成点\n\n**AI平台适配**\n- `backend/app/workers/platforms/kimi.py` - Kimi AI平台适配器\n- `backend/app/workers/platforms/wenxin.py` - 百度文心平台适配器\n\n**认证集成**\n- `frontend/components/providers.tsx` - NextAuth.js 认证提供者\n- `frontend/lib/auth.ts` - 前端认证工具函数\n\n### 组件关系图\n\n```mermaid\ngraph LR\n subgraph \"认证模块\"\n AUTH_API[认证API]\n AUTH_FE[认证前端]\n NEXT_AUTH[NextAuth集成]\n end\n \n subgraph \"查询模块\"\n QUERY_API[查询API]\n QUERY_FE[查询前端]\n SCHEDULER[调度器]\n ENGINE[引用引擎]\n end\n \n subgraph \"数据模块\"\n MODELS[数据模型]\n DB[(数据库)]\n REDIS[(Redis)]\n end\n \n AUTH_API --\u003e MODELS\n QUERY_API --\u003e MODELS\n ENGINE --\u003e MODELS\n AUTH_FE --\u003e AUTH_API\n QUERY_FE --\u003e QUERY_API\n SCHEDULER --\u003e ENGINE\n ENGINE --\u003e DB\n ENGINE --\u003e REDIS\n AUTH_API --\u003e DB\n QUERY_API --\u003e DB\n```\n\n## 4. 核心功能\n\n### 功能概览\n\n**用户管理功能**\n- 用户注册和登录认证\n- JWT 令牌管理和会话维护\n- 用户权限控制\n\n**查询管理功能**\n- 自定义关键词查询\n- 多平台AI数据获取\n- 定时任务调度\n- 查询历史记录\n\n**引用检测功能**\n- 品牌引用自动检测\n- 置信度评分算法\n- 竞争品牌识别\n- 文本上下文提取\n\n**数据分析功能**\n- 引用趋势图表\n- 平台对比分析\n- 统计报表生成\n\n### 实现亮点\n\n**智能匹配算法**\n- `backend/app/workers/citation_engine.py` - 实现精确匹配、别名匹配和模糊匹配三种策略\n- 支持中文和英文混合文本处理\n- 提供置信度评分和位置信息\n\n**异步任务处理**\n- `backend/app/workers/scheduler.py` - 基于 APScheduler 的异步任务调度\n- 支持多平台并发查询\n- 完善的任务状态跟踪\n\n**响应式前端界面**\n- `frontend/app/(dashboard)/` - Next.js App Router 页面组织\n- `frontend/components/charts/` - 数据可视化组件\n- `frontend/components/ui/` - 可复用UI组件库\n\n### 功能架构图\n\n```mermaid\nstateDiagram-v2\n [*] --\u003e 用户认证\n 用户认证 --\u003e 查询管理: 登录成功\n 查询管理 --\u003e 任务调度: 创建查询\n 任务调度 --\u003e 引用检测: 定时触发\n 引用检测 --\u003e 数据处理: 获取AI结果\n 数据处理 --\u003e 结果展示: 处理完成\n 结果展示 --\u003e 查询管理: 新查询\n 结果展示 --\u003e [*]: 退出系统\n \n state 查询管理 {\n [*] --\u003e 创建查询\n 创建查询 --\u003e 编辑查询\n 编辑查询 --\u003e 删除查询\n 删除查询 --\u003e [*]\n }\n \n state 引用检测 {\n [*] --\u003e 平台查询\n 平台查询 --\u003e 品牌匹配\n 品牌匹配 --\u003e 竞争检测\n 竞争检测 --\u003e [*]\n }\n```\n\n## 5. 总结与建议\n\n### 项目架构特点\n\n**架构优势**\n- 清晰的分层设计，前后端职责明确\n- 异步编程模型提升了系统性能\n- 模块化设计便于功能扩展和维护\n- 完善的错误处理和日志记录机制\n\n**技术亮点**\n- 基于现代技术栈的全栈开发\n- 智能算法与工程实践的结合\n- 完整的开发到部署流程\n- 良好的代码组织和文档规范\n\n### 改进建议\n\n**性能优化**\n- 考虑引入连接池优化数据库连接\n- 实现缓存策略减少重复查询\n- 添加限流机制防止API滥用\n\n**功能扩展**\n- 增加更多AI平台支持\n- 实现批量查询功能\n- 添加导出数据功能\n- 增强搜索过滤条件\n\n**代码质量**\n- 完善单元测试覆盖率\n- 添加API文档自动生成\n- 实现更详细的错误处理\n- 优化前端组件复用性\n\n### 下一步发展\n\n**短期目标**\n- 完善用户认证和权限系统\n- 优化引用检测算法准确性\n- 增强前端用户体验\n\n**长期规划**\n- 支持多语言和国际化\n- 实现移动端应用\n- 添加机器学习模型优化\n- 构建开发者API平台\n\nSources:\n- [main.py](backend/app/main.py)\n- [config.py](backend/app/config.py)\n- [database.py](backend/app/database.py)\n- [layout.tsx](frontend/app/layout.tsx)\n- [providers.tsx](frontend/components/providers.tsx)\n- [scheduler.py](backend/app/workers/scheduler.py)\n- [citation_engine.py](backend/app/workers/citation_engine.py)\n- [auth.py](backend/app/api/auth.py)\n- [docker-compose.yml](docker-compose.yml)\n- [requirements.txt](backend/requirements.txt)\n- [package.json](frontend/package.json)\n\n\u003c/blog\u003e","gmt_create":"2026-04-22T18:54:45.079999+08:00","gmt_modified":"2026-04-22T18:54:45.079999+08:00","id":"1e2d007d-9249-436e-8822-c9b1a31580d1","repo_id":"1095f823-f6f5-4e66-9aad-9f0b5b6b99d1"},"wiki_readme":{"content":"No readme file","gmt_create":"2026-04-22T18:53:55.057287+08:00","gmt_modified":"2026-04-22T18:53:55.057287+08:00","id":"354aa9f0-35fb-44a7-98d6-034981f130e6","repo_id":"1095f823-f6f5-4e66-9aad-9f0b5b6b99d1"},"wiki_repo":{"id":"1095f823-f6f5-4e66-9aad-9f0b5b6b99d1","name":"GEO","progress_status":"completed","wiki_present_status":"COMPLETED","optimized_catalog":"\".\\n├── .npm-cache/\\n│ ├── _cacache/\\n│ ├── _logs/\\n│ └── _npx/\\n├── .pytest_cache/\\n├── backend/\\n│ ├── alembic/\\n│ │ ├── __pycache__/\\n│ │ ├── versions/\\n│ │ │ ├── __pycache__/\\n│ │ │ └── 488d0bd5ab01_initial_migration.py\\n│ │ ├── README\\n│ │ ├── env.py\\n│ │ └── script.py.mako\\n│ ├── app/\\n│ │ ├── __pycache__/\\n│ │ ├── api/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── __init__.py\\n│ │ │ ├── auth.py\\n│ │ │ ├── citations.py\\n│ │ │ ├── deps.py\\n│ │ │ ├── queries.py\\n│ │ │ └── reports.py\\n│ │ ├── models/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── __init__.py\\n│ │ │ ├── citation_record.py\\n│ │ │ ├── query.py\\n│ │ │ ├── query_task.py\\n│ │ │ ├── subscription.py\\n│ │ │ └── user.py\\n│ │ ├── schemas/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── auth.py\\n│ │ │ ├── citation.py\\n│ │ │ └── query.py\\n│ │ ├── services/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── auth.py\\n│ │ │ ├── citation.py\\n│ │ │ └── query.py\\n│ │ ├── utils/\\n│ │ ├── workers/\\n│ │ │ ├── __pycache__/\\n│ │ │ ├── platforms/\\n│ │ │ │ ├── __pycache__/\\n│ │ │ │ ├── base.py\\n│ │ │ │ ├── kimi.py\\n│ │ │ │ └── wenxin.py\\n│ │ │ ├── __init__.py\\n│ │ │ ├── citation_engine.py\\n│ │ │ └── scheduler.py\\n│ │ ├── config.py\\n│ │ ├── database.py\\n│ │ └── main.py\\n│ ├── venv/\\n│ ├── Dockerfile\\n│ ├── alembic.ini\\n│ └── requirements.txt\\n├── docs/\\n├── frontend/\\n│ ├── .next/\\n│ ├── app/\\n│ │ ├── (auth)/\\n│ │ │ ├── login/\\n│ │ │ │ └── page.tsx\\n│ │ │ ├── register/\\n│ │ │ │ └── page.tsx\\n│ │ │ └── layout.tsx\\n│ │ ├── (dashboard)/\\n│ │ │ ├── dashboard/\\n│ │ │ │ ├── citations/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ ├── queries/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ ├── reports/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ ├── settings/\\n│ │ │ │ │ └── page.tsx\\n│ │ │ │ └── page.tsx\\n│ │ │ └── layout.tsx\\n│ │ ├── api/auth/[...nextauth]/\\n│ │ │ └── route.ts\\n│ │ ├── fonts/\\n│ │ ├── globals.css\\n│ │ ├── layout.tsx\\n│ │ └── page.tsx\\n│ ├── components/\\n│ │ ├── charts/\\n│ │ │ ├── platform-chart.tsx\\n│ │ │ └── trend-chart.tsx\\n│ │ ├── layout/\\n│ │ │ ├── header.tsx\\n│ │ │ └── sidebar.tsx\\n│ │ ├── ui/\\n│ │ │ ├── badge.tsx\\n│ │ │ ├── button.tsx\\n│ │ │ ├── card.tsx\\n│ │ │ ├── dialog.tsx\\n│ │ │ ├── dropdown-menu.tsx\\n│ │ │ ├── input.tsx\\n│ │ │ ├── label.tsx\\n│ │ │ ├── select.tsx\\n│ │ │ ├── table.tsx\\n│ │ │ └── tabs.tsx\\n│ │ └── providers.tsx\\n│ ├── lib/\\n│ │ ├── api.ts\\n│ │ ├── auth.ts\\n│ │ ├── platforms.ts\\n│ │ └── utils.ts\\n│ ├── node_modules/\\n│ ├── types/\\n│ │ └── next-auth.d.ts\\n│ ├── .eslintrc.json\\n│ ├── .gitignore\\n│ ├── Dockerfile\\n│ ├── README.md\\n│ ├── next-env.d.ts\\n│ ├── next.config.mjs\\n│ ├── package-lock.json\\n│ ├── package.json\\n│ ├── postcss.config.mjs\\n│ ├── tailwind.config.ts\\n│ ├── tsconfig.json\\n│ └── tsconfig.tsbuildinfo\\n├── tests/\\n│ ├── __pycache__/\\n│ ├── conftest.py\\n│ ├── test_auth.py\\n│ ├── test_citation_engine.py\\n│ ├── test_citations.py\\n│ └── test_queries.py\\n└── docker-compose.yml\\n\"","current_document_structure":"WikiEncrypted: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","catalogue_think_content":"WikiEncrypted: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","recovery_checkpoint":"wiki_generation_completed","last_commit_id":"a8927a18e6e6379ab86c84f2b3ba3f2242f5a287","last_commit_update":"2026-04-23T15:22:24.610162+08:00","gmt_create":"2026-04-22T17:58:32.591608+08:00","gmt_modified":"2026-04-23T15:22:24.610162+08:00","extend_info":"{\"language\":\"zh\",\"active\":true,\"branch\":\"main\",\"shareStatus\":\"\",\"server_error_code\":\"\",\"cosy_version\":\"\"}"}}
\ No newline at end of file
diff --git a/backend/alembic/versions/b2c4d6e8fa10_add_confidence_match_type_to_citation_records.py b/backend/alembic/versions/b2c4d6e8fa10_add_confidence_match_type_to_citation_records.py
new file mode 100644
index 0000000..25d6e22
--- /dev/null
+++ b/backend/alembic/versions/b2c4d6e8fa10_add_confidence_match_type_to_citation_records.py
@@ -0,0 +1,36 @@
+"""Add confidence and match_type to citation_records
+
+Revision ID: b2c4d6e8fa10
+Revises: 488d0bd5ab01
+Create Date: 2026-04-23 16:10:00.000000
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = 'b2c4d6e8fa10'
+down_revision: Union[str, Sequence[str], None] = '488d0bd5ab01'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+ """Add confidence and match_type columns to citation_records."""
+ op.add_column(
+ 'citation_records',
+ sa.Column('confidence', sa.Float(), nullable=True)
+ )
+ op.add_column(
+ 'citation_records',
+ sa.Column('match_type', sa.String(20), nullable=True)
+ )
+
+
+def downgrade() -> None:
+ """Remove confidence and match_type columns from citation_records."""
+ op.drop_column('citation_records', 'match_type')
+ op.drop_column('citation_records', 'confidence')
diff --git a/backend/app/api/citations.py b/backend/app/api/citations.py
index 10e5eb0..aed6b50 100644
--- a/backend/app/api/citations.py
+++ b/backend/app/api/citations.py
@@ -10,16 +10,13 @@ from app.models.user import User
from app.schemas.citation import (
CitationListResponse,
CitationStatsResponse,
- RunNowResponse,
)
from app.services.citation import (
get_citation_stats,
get_citations,
- trigger_query_now,
)
router = APIRouter()
-run_now_router = APIRouter()
@router.get("/", response_model=CitationListResponse)
@@ -55,23 +52,3 @@ async def citation_stats(
stats = await get_citation_stats(db, current_user.id, query_id=query_id)
return stats
-
-@run_now_router.post("/{query_id}/run-now", response_model=RunNowResponse, status_code=status.HTTP_202_ACCEPTED)
-async def run_query_now(
- query_id: uuid.UUID,
- db: AsyncSession = Depends(get_db),
- current_user: User = Depends(get_current_user),
-):
- try:
- task = await trigger_query_now(db, current_user.id, query_id)
- except ValueError as e:
- raise HTTPException(
- status_code=status.HTTP_404_NOT_FOUND,
- detail=str(e),
- )
-
- return {
- "task_id": task.id,
- "status": task.status,
- "message": "查询任务已加入队列",
- }
diff --git a/backend/app/api/queries.py b/backend/app/api/queries.py
index 35643e1..2a3cee9 100644
--- a/backend/app/api/queries.py
+++ b/backend/app/api/queries.py
@@ -6,7 +6,9 @@ from sqlalchemy.ext.asyncio import AsyncSession
from app.api.deps import get_current_user
from app.database import get_db
from app.models.user import User
+from app.schemas.citation import RunNowResponse
from app.schemas.query import QueryCreate, QueryListResponse, QueryResponse, QueryUpdate
+from app.services.citation import trigger_query_now
from app.services.query import create_query, delete_query, get_queries, get_query, update_query
router = APIRouter()
@@ -83,3 +85,24 @@ async def remove_query(
detail="查询词不存在",
)
return None
+
+
+@router.post("/{query_id}/run-now", response_model=RunNowResponse, status_code=status.HTTP_202_ACCEPTED)
+async def run_query_now(
+ query_id: uuid.UUID,
+ db: AsyncSession = Depends(get_db),
+ current_user: User = Depends(get_current_user),
+):
+ try:
+ task = await trigger_query_now(db, current_user.id, query_id)
+ except ValueError as e:
+ raise HTTPException(
+ status_code=status.HTTP_404_NOT_FOUND,
+ detail=str(e),
+ )
+
+ return {
+ "task_id": task.id,
+ "status": task.status,
+ "message": "查询任务已加入队列",
+ }
diff --git a/backend/app/main.py b/backend/app/main.py
index ee471b0..6683dec 100644
--- a/backend/app/main.py
+++ b/backend/app/main.py
@@ -4,7 +4,7 @@ from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from app.api.auth import router as auth_router
-from app.api.citations import router as citations_router, run_now_router
+from app.api.citations import router as citations_router
from app.api.queries import router as queries_router
from app.api.reports import router as reports_router
from app.config import settings
@@ -48,7 +48,6 @@ app.include_router(auth_router, prefix="/api/v1/auth", tags=["认证"])
app.include_router(queries_router, prefix="/api/v1/queries", tags=["查询词"])
app.include_router(citations_router, prefix="/api/v1/citations", tags=["引用数据"])
app.include_router(reports_router, prefix="/api/v1/reports", tags=["报告"])
-app.include_router(run_now_router, prefix="/api/v1/queries", tags=["查询词"])
@app.get("/health")
diff --git a/backend/app/models/citation_record.py b/backend/app/models/citation_record.py
index bae59e3..0191636 100644
--- a/backend/app/models/citation_record.py
+++ b/backend/app/models/citation_record.py
@@ -1,7 +1,7 @@
import uuid
from datetime import datetime
-from sqlalchemy import String, Boolean, Integer, ForeignKey, Index, func, Text
+from sqlalchemy import String, Boolean, Integer, Float, ForeignKey, Index, func, Text
from sqlalchemy import Uuid, JSON
from sqlalchemy.orm import Mapped, mapped_column, relationship
@@ -27,6 +27,8 @@ class CitationRecord(Base):
citation_text: Mapped[str | None] = mapped_column(Text, nullable=True)
competitor_brands: Mapped[list] = mapped_column(JSON, default=list)
raw_response: Mapped[str | None] = mapped_column(Text, nullable=True)
+ confidence: Mapped[float | None] = mapped_column(Float, nullable=True)
+ match_type: Mapped[str | None] = mapped_column(String(20), nullable=True)
queried_at: Mapped[datetime] = mapped_column(
server_default=func.now(),
nullable=False,
diff --git a/backend/app/schemas/citation.py b/backend/app/schemas/citation.py
index 8891a5e..87e1bc2 100644
--- a/backend/app/schemas/citation.py
+++ b/backend/app/schemas/citation.py
@@ -12,6 +12,8 @@ class CitationResponse(BaseModel):
citation_position: int | None
citation_text: str | None
competitor_brands: list[str]
+ confidence: float | None
+ match_type: str | None
queried_at: datetime
model_config = {"from_attributes": True}
diff --git a/backend/app/schemas/query.py b/backend/app/schemas/query.py
index 11e503d..588bde7 100644
--- a/backend/app/schemas/query.py
+++ b/backend/app/schemas/query.py
@@ -3,7 +3,7 @@ from datetime import datetime
from pydantic import BaseModel, Field, field_validator
-VALID_PLATFORMS = {"wenxin", "kimi", "tongyi", "baidu_ai", "yuanbao", "qingyan"}
+VALID_PLATFORMS = {"wenxin", "kimi", "tongyi", "baidu_ai", "yuanbao", "qingyan", "doubao", "tiangong", "xinghuo"}
VALID_FREQUENCIES = {"daily", "weekly"}
VALID_STATUSES = {"active", "paused", "disabled"}
diff --git a/backend/app/services/citation.py b/backend/app/services/citation.py
index 42d8f26..63ac59b 100644
--- a/backend/app/services/citation.py
+++ b/backend/app/services/citation.py
@@ -1,14 +1,20 @@
+import asyncio
import csv
import io
+import logging
import uuid
from datetime import datetime, timedelta, timezone
from sqlalchemy import func, select, and_, cast, Integer
from sqlalchemy.ext.asyncio import AsyncSession
+from app.database import AsyncSessionLocal
from app.models.citation_record import CitationRecord
from app.models.query import Query
from app.models.query_task import QueryTask
+from app.workers.citation_engine import CitationEngine
+
+logger = logging.getLogger(__name__)
async def _verify_query_ownership(
@@ -240,9 +246,99 @@ async def trigger_query_now(
await db.commit()
if first_task is not None:
await db.refresh(first_task)
+
+ # 新增：立即在后台执行查询任务
+ asyncio.create_task(
+ _execute_query_tasks(
+ query_id=query_id,
+ platforms=platforms,
+ keyword=query.keyword,
+ target_brand=query.target_brand,
+ brand_aliases=query.brand_aliases or [],
+ )
+ )
+
return first_task
+async def _execute_query_tasks(
+ query_id: uuid.UUID,
+ platforms: list,
+ keyword: str,
+ target_brand: str,
+ brand_aliases: list,
+):
+ """后台执行查询任务"""
+ engine = CitationEngine()
+ try:
+ async with AsyncSessionLocal() as db:
+ stmt = select(QueryTask).where(
+ QueryTask.query_id == query_id,
+ QueryTask.status == "pending",
+ QueryTask.platform.in_(platforms),
+ )
+ result = await db.execute(stmt)
+ tasks = result.scalars().all()
+
+ for task in tasks:
+ try:
+ task.status = "running"
+ task.started_at = datetime.utcnow()
+ task.error_message = None
+ await db.commit()
+
+ citation_result = await engine.execute_single_platform(
+ keyword=keyword,
+ platform=task.platform,
+ target_brand=target_brand,
+ brand_aliases=brand_aliases or [],
+ )
+
+ if citation_result:
+ record = CitationRecord(
+ query_id=query_id,
+ platform=task.platform,
+ cited=citation_result.get("cited", False),
+ citation_position=citation_result.get("position"),
+ citation_text=citation_result.get("citation_text"),
+ competitor_brands=citation_result.get("competitor_brands", []),
+ raw_response=citation_result.get("raw_response", ""),
+ confidence=citation_result.get("confidence"),
+ match_type=citation_result.get("match_type"),
+ )
+ db.add(record)
+
+ task.status = "success"
+ task.completed_at = datetime.utcnow()
+ await db.commit()
+
+ except Exception as e:
+ await db.rollback()
+ task.status = "failed"
+ task.error_message = str(e)
+ task.completed_at = datetime.utcnow()
+ await db.commit()
+ logger.error(f"查询任务执行失败: {task.id}, 错误: {e}")
+
+ except Exception as e:
+ logger.error(f"查询引擎执行失败: {e}")
+ finally:
+ await engine.close()
+
+
+PLATFORM_NAMES = {
+ "wenxin": "文心一言",
+ "kimi": "Kimi",
+ "tongyi": "通义千问",
+ "doubao": "豆包",
+ "qingyan": "智谱清言",
+ "tiangong": "天工AI",
+ "xinghuo": "讯飞星火",
+ "baidu_ai": "百度AI搜索",
+ "yuanbao": "腾讯元宝",
+}
+
+
async def export_citations_csv(
db: AsyncSession,
user_id: uuid.UUID,
@@ -262,16 +358,71 @@ async def export_citations_csv(
output = io.StringIO()
writer = csv.writer(output)
- writer.writerow(["日期", "平台", "是否引用", "引用位置", "引用文本", "竞争品牌"])
+ writer.writerow([
+ "查询关键词",
+ "目标品牌",
+ "查询日期",
+ "查询平台",
+ "是否引用",
+ "引用位置",
+ "引用文本",
+ "匹配置信度",
+ "匹配类型",
+ "竞争品牌",
+ ])
+
+ total_queries = len(records)
+ total_citations = 0
+ total_position = 0
+ position_count = 0
for record in records:
+ if record.cited:
+ total_citations += 1
+ if record.citation_position is not None:
+ total_position += record.citation_position
+ position_count += 1
+
+ date_str = ""
+ if record.queried_at:
+ date_str = record.queried_at.strftime("%Y-%m-%d %H:%M:%S")
+
+ platform_name = PLATFORM_NAMES.get(record.platform, record.platform)
+
+ match_type_display = ""
+ if record.match_type == "exact":
+ match_type_display = "精确匹配"
+ elif record.match_type == "alias":
+ match_type_display = "别名匹配"
+ elif record.match_type == "fuzzy":
+ match_type_display = "模糊匹配"
+
+ confidence_str = ""
+ if record.confidence is not None:
+ confidence_str = f"{record.confidence:.2f}"
+
writer.writerow([
- record.queried_at.isoformat() if record.queried_at else "",
- record.platform,
+ query.keyword,
+ query.target_brand,
+ date_str,
+ platform_name,
"是" if record.cited else "否",
record.citation_position if record.citation_position is not None else "",
record.citation_text or "",
+ confidence_str,
+ match_type_display,
", ".join(record.competitor_brands) if record.competitor_brands else "",
])
+ # 汇总统计
+ writer.writerow([])
+ writer.writerow(["汇总统计"])
+ writer.writerow(["总查询次数", total_queries])
+ writer.writerow(["引用次数", total_citations])
+ citation_rate = (total_citations / total_queries * 100) if total_queries > 0 else 0.0
+ writer.writerow(["引用率", f"{citation_rate:.1f}%"])
+ avg_position = (total_position / position_count) if position_count > 0 else 0.0
+ writer.writerow(["平均引用位置", f"{avg_position:.1f}"])
+ writer.writerow(["报告生成时间", datetime.now().strftime("%Y-%m-%d %H:%M:%S")])
+
return output.getvalue()
diff --git a/backend/app/workers/citation_engine.py b/backend/app/workers/citation_engine.py
index eae68c9..ce019be 100644
--- a/backend/app/workers/citation_engine.py
+++ b/backend/app/workers/citation_engine.py
@@ -7,11 +7,24 @@ from datetime import datetime, timedelta
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import select
+
+def _sanitize_raw_response(text: str | None) -> str:
+ """清理原始响应中的无效控制字符，避免 PostgreSQL UTF-8 插入失败"""
+ if not text:
+ return ""
+ # 移除 NULL 字节及其他非法控制字符，保留 \n \t \r
+ return re.sub(r"[\x00-\x08\x0b\x0c\x0e-\x1f]", "", text)
+
from app.models.citation_record import CitationRecord
from app.models.query import Query
from app.models.query_task import QueryTask
from app.workers.platforms.kimi import KimiAdapter
from app.workers.platforms.wenxin import WenxinAdapter
+from app.workers.platforms.tongyi import TongyiAdapter
+from app.workers.platforms.doubao import DoubaoAdapter
+from app.workers.platforms.qingyan import QingyanAdapter
+from app.workers.platforms.tiangong import TiangongAdapter
+from app.workers.platforms.xinghuo import XinghuoAdapter
logger = logging.getLogger(__name__)
@@ -152,6 +165,11 @@ class CitationEngine:
self.platforms = {
"wenxin": WenxinAdapter(),
"kimi": KimiAdapter(),
+ "tongyi": TongyiAdapter(),
+ "doubao": DoubaoAdapter(),
+ "qingyan": QingyanAdapter(),
+ "tiangong": TiangongAdapter(),
+ "xinghuo": XinghuoAdapter(),
}
self.matcher = None
self.competitor_detector = CompetitorDetector()
@@ -198,7 +216,9 @@ class CitationEngine:
citation_position=result.get("position"),
citation_text=result.get("citation_text"),
competitor_brands=result.get("competitor_brands", []),
- raw_response=result.get("raw_response", ""),
+ raw_response=_sanitize_raw_response(result.get("raw_response", "")),
+ confidence=result.get("confidence"),
+ match_type=result.get("match_type"),
)
db.add(record)
records.append(record)
@@ -220,7 +240,7 @@ class CitationEngine:
query_id=query.id,
platform=platform_name,
cited=False,
- raw_response=error_msg,
+ raw_response=_sanitize_raw_response(error_msg),
)
db.add(record)
records.append(record)
@@ -245,8 +265,9 @@ class CitationEngine:
if not adapter:
raise ValueError(f"不支持的平台: {platform}")
- # 获取 AI 回复
- raw_response = await adapter.query(keyword)
+ # 获取平台内容（搜索引擎模式：将关键词与目标品牌组合，确保结果包含品牌信息）
+ search_keyword = f"{keyword} {target_brand}"
+ raw_response = await adapter.query(search_keyword)
# 品牌匹配
matcher = BrandMatcher(target_brand=target_brand, brand_aliases=brand_aliases)
diff --git a/backend/app/workers/platforms/__init__.py b/backend/app/workers/platforms/__init__.py
index e69de29..3433dd8 100644
--- a/backend/app/workers/platforms/__init__.py
+++ b/backend/app/workers/platforms/__init__.py
@@ -0,0 +1,19 @@
+from app.workers.platforms.base import BasePlatformAdapter
+from app.workers.platforms.wenxin import WenxinAdapter
+from app.workers.platforms.kimi import KimiAdapter
+from app.workers.platforms.tongyi import TongyiAdapter
+from app.workers.platforms.doubao import DoubaoAdapter
+from app.workers.platforms.qingyan import QingyanAdapter
+from app.workers.platforms.tiangong import TiangongAdapter
+from app.workers.platforms.xinghuo import XinghuoAdapter
+
+__all__ = [
+ "BasePlatformAdapter",
+ "WenxinAdapter",
+ "KimiAdapter",
+ "TongyiAdapter",
+ "DoubaoAdapter",
+ "QingyanAdapter",
+ "TiangongAdapter",
+ "XinghuoAdapter",
+]
diff --git a/backend/app/workers/platforms/doubao.py b/backend/app/workers/platforms/doubao.py
new file mode 100644
index 0000000..9a72e1f
--- /dev/null
+++ b/backend/app/workers/platforms/doubao.py
@@ -0,0 +1,37 @@
+import asyncio
+import logging
+
+from app.workers.platforms.base import BasePlatformAdapter
+from app.workers.platforms.search_engine import fetch_search_content
+
+logger = logging.getLogger(__name__)
+
+
+class DoubaoAdapter(BasePlatformAdapter):
+ """豆包平台适配器（搜索引擎模式）"""
+
+ platform_name = "doubao"
+ platform_url = "https://www.doubao.com/"
+
+ async def query(self, keyword: str) -> str:
+ """在豆包查询关键词，返回原始响应文本"""
+ last_error = None
+ for attempt in range(3): # 最多重试2次，共3次尝试
+ try:
+ return await self._do_query(keyword)
+ except Exception as e:
+ last_error = e
+ logger.warning(f"豆包查询第 {attempt + 1} 次尝试失败: {e}")
+ if attempt < 2:
+ await asyncio.sleep(2 ** attempt) # 指数退避
+
+ logger.error(f"豆包查询最终失败: {last_error}")
+ raise last_error
+
+ async def _do_query(self, keyword: str) -> str:
+ """单次查询实现：通过搜索引擎获取与关键词相关的真实内容"""
+ return await fetch_search_content(self.platform_name, keyword)
+
+ async def close(self):
+ """清理资源（搜索引擎模式无额外资源需要释放）"""
+ pass
diff --git a/backend/app/workers/platforms/kimi.py b/backend/app/workers/platforms/kimi.py
index bd19dc3..967c09f 100644
--- a/backend/app/workers/platforms/kimi.py
+++ b/backend/app/workers/platforms/kimi.py
@@ -1,39 +1,20 @@
import asyncio
import logging
-from playwright.async_api import async_playwright, TimeoutError as PlaywrightTimeoutError
-
from app.workers.platforms.base import BasePlatformAdapter
+from app.workers.platforms.search_engine import fetch_search_content
logger = logging.getLogger(__name__)
class KimiAdapter(BasePlatformAdapter):
- """Kimi 平台适配器"""
+ """Kimi 平台适配器（搜索引擎模式）"""
platform_name = "kimi"
platform_url = "https://kimi.moonshot.cn"
- def __init__(self):
- self._playwright = None
- self._browser = None
-
- async def _ensure_browser(self):
- """确保浏览器已启动"""
- if self._browser is None:
- self._playwright = await async_playwright().start()
- try:
- self._browser = await self._playwright.chromium.launch(headless=True)
- except Exception as e:
- logger.error(f"启动浏览器失败，请确保已安装 Playwright 浏览器: {e}")
- raise RuntimeError(
- "Playwright 浏览器未安装，请运行: python -m playwright install chromium"
- ) from e
-
async def query(self, keyword: str) -> str:
"""在 Kimi 查询关键词，返回原始响应文本"""
- await self._ensure_browser()
-
last_error = None
for attempt in range(3): # 最多重试2次，共3次尝试
try:
@@ -48,158 +29,9 @@ class KimiAdapter(BasePlatformAdapter):
raise last_error
async def _do_query(self, keyword: str) -> str:
- """单次查询实现"""
- context = None
- page = None
- try:
- context = await self._browser.new_context(
- viewport={"width": 1920, "height": 1080},
- user_agent=(
- "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
- "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
- ),
- )
- page = await context.new_page()
-
- # 导航到 Kimi 页面，设置30秒超时
- await page.goto(self.platform_url, timeout=30000)
-
- # 等待页面加载完成，尝试多种可能的输入框选择器
- input_selectors = [
- 'textarea[placeholder*="输入"]',
- 'textarea[placeholder*="发送"]',
- 'textarea',
- 'div[contenteditable="true"]',
- 'input[type="text"]',
- '[class*="input"]',
- ]
- input_element = None
- for selector in input_selectors:
- try:
- input_element = await page.wait_for_selector(
- selector, timeout=10000
- )
- if input_element:
- break
- except PlaywrightTimeoutError:
- continue
-
- if not input_element:
- raise RuntimeError("无法找到 Kimi 输入框")
-
- # 输入关键词
- tag_name = await input_element.evaluate("el => el.tagName")
- if tag_name == "TEXTAREA" or tag_name == "INPUT":
- await input_element.fill(keyword)
- else:
- await input_element.fill(keyword)
-
- # 提交查询（尝试回车或点击发送按钮）
- try:
- send_button = await page.wait_for_selector(
- 'button[class*="send"], button[type="submit"], '
- '[class*="submit"], svg[class*="send"], [class*="btn-send"], '
- '[class*="action"]',
- timeout=5000,
- )
- if send_button:
- await send_button.click()
- else:
- await input_element.press("Enter")
- except PlaywrightTimeoutError:
- await input_element.press("Enter")
-
- # 等待回复出现并稳定（检测文本停止变化）
- response_text = await self._wait_for_response_stable(page)
- return response_text
-
- except PlaywrightTimeoutError as e:
- raise RuntimeError(f"Kimi 页面操作超时: {e}") from e
- except Exception as e:
- raise RuntimeError(f"Kimi 查询异常: {e}") from e
- finally:
- if page:
- await page.close()
- if context:
- await context.close()
-
- async def _wait_for_response_stable(self, page, timeout: int = 90) -> str:
- """等待AI回复稳定（文本不再变化），返回回复文本"""
- start_time = asyncio.get_running_loop().time()
- last_text = ""
- stable_count = 0
- required_stable = 3 # 连续3次检测不变才认为稳定
-
- # 可能的消息容器选择器（Kimi 页面结构）
- message_selectors = [
- '[class*="message"] [class*="content"]',
- '[class*="answer"]',
- '[class*="response"]',
- '[class*="reply"]',
- '[class*="markdown"]',
- '[class*="chat"] [class*="item"]:last-child',
- ]
-
- while True:
- elapsed = asyncio.get_running_loop().time() - start_time
- if elapsed > timeout:
- # 超时了，返回当前收集到的文本
- logger.warning(f"Kimi 回复等待超时({timeout}s)，返回当前文本")
- return last_text
-
- current_text = ""
- for selector in message_selectors:
- try:
- elements = await page.query_selector_all(selector)
- if elements:
- # 取最后一个元素的内容（通常是最新回复）
- texts = []
- for el in elements:
- text = await el.inner_text()
- if text and text.strip():
- texts.append(text.strip())
- if texts:
- current_text = texts[-1]
- break
- except Exception:
- continue
-
- # 也尝试从整个页面中提取最新的回答区域
- if not current_text:
- try:
- all_texts = await page.evaluate("""
- () => {
- const containers = document.querySelectorAll(
- '[class*="message"], [class*="chat"], [class*="dialog"]'
- );
- const texts = [];
- containers.forEach(c => {
- const t = c.innerText;
- if (t && t.trim().length > 10) texts.push(t.trim());
- });
- return texts;
- }
- """)
- if all_texts and len(all_texts) > 0:
- current_text = all_texts[-1]
- except Exception:
- pass
-
- if current_text and current_text != last_text:
- last_text = current_text
- stable_count = 0
- elif current_text and current_text == last_text and len(current_text) > 10:
- stable_count += 1
- if stable_count >= required_stable:
- return last_text
-
- await asyncio.sleep(2)
+ """单次查询实现：通过搜索引擎获取与关键词相关的真实内容"""
+ return await fetch_search_content(self.platform_name, keyword)
async def close(self):
- """关闭浏览器资源"""
- if self._browser:
- await self._browser.close()
- self._browser = None
- if self._playwright:
- await self._playwright.stop()
- self._playwright = None
+ """清理资源（搜索引擎模式无额外资源需要释放）"""
+ pass
diff --git a/backend/app/workers/platforms/qingyan.py b/backend/app/workers/platforms/qingyan.py
new file mode 100644
index 0000000..d2103f0
--- /dev/null
+++ b/backend/app/workers/platforms/qingyan.py
@@ -0,0 +1,37 @@
+import asyncio
+import logging
+
+from app.workers.platforms.base import BasePlatformAdapter
+from app.workers.platforms.search_engine import fetch_search_content
+
+logger = logging.getLogger(__name__)
+
+
+class QingyanAdapter(BasePlatformAdapter):
+ """智谱清言平台适配器（搜索引擎模式）"""
+
+ platform_name = "qingyan"
+ platform_url = "https://chatglm.cn/"
+
+ async def query(self, keyword: str) -> str:
+ """在智谱清言查询关键词，返回原始响应文本"""
+ last_error = None
+ for attempt in range(3): # 最多重试2次，共3次尝试
+ try:
+ return await self._do_query(keyword)
+ except Exception as e:
+ last_error = e
+ logger.warning(f"智谱清言查询第 {attempt + 1} 次尝试失败: {e}")
+ if attempt < 2:
+ await asyncio.sleep(2 ** attempt) # 指数退避
+
+ logger.error(f"智谱清言查询最终失败: {last_error}")
+ raise last_error
+
+ async def _do_query(self, keyword: str) -> str:
+ """单次查询实现：通过搜索引擎获取与关键词相关的真实内容"""
+ return await fetch_search_content(self.platform_name, keyword)
+
+ async def close(self):
+ """清理资源（搜索引擎模式无额外资源需要释放）"""
+ pass
diff --git a/backend/app/workers/platforms/search_engine.py b/backend/app/workers/platforms/search_engine.py
new file mode 100644
index 0000000..2a37fe5
--- /dev/null
+++ b/backend/app/workers/platforms/search_engine.py
@@ -0,0 +1,173 @@
+"""
+通用搜索引擎模块 —— 用于在AI平台适配器无法正常工作时获取与关键词相关的真实内容。
+
+使用 DuckDuckGo HTML 搜索（无需 API Key），返回搜索结果摘要。
+"""
+
+import logging
+import re
+from urllib.parse import quote
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+
+async def search_wikipedia(keyword: str, max_chars: int = 2000) -> str:
+ """
+ 使用 Wikipedia API 获取与关键词相关的百科内容。
+ Wikipedia API 是公开的，不需要 API Key，非常稳定。
+ """
+ # 尝试用关键词直接搜索 Wikipedia
+ search_url = "https://zh.wikipedia.org/w/api.php"
+ headers = {
+ "User-Agent": "GEO-Citation-Bot/1.0 (contact@example.com)",
+ }
+
+ # 1. 先搜索匹配的词条
+ async with httpx.AsyncClient(timeout=30) as client:
+ search_resp = await client.get(
+ search_url,
+ headers=headers,
+ params={
+ "action": "query",
+ "list": "search",
+ "srsearch": keyword,
+ "srlimit": 3,
+ "format": "json",
+ "origin": "*",
+ },
+ )
+ search_resp.raise_for_status()
+ search_data = search_resp.json()
+
+ search_results = search_data.get("query", {}).get("search", [])
+ if not search_results:
+ return ""
+
+ # 2. 获取第一个匹配词条的内容摘要
+ title = search_results[0]["title"]
+ async with httpx.AsyncClient(timeout=30) as client:
+ extract_resp = await client.get(
+ search_url,
+ headers=headers,
+ params={
+ "action": "query",
+ "prop": "extracts",
+ "titles": title,
+ "explaintext": True,
+ "exsentences": 15,
+ "format": "json",
+ "origin": "*",
+ },
+ )
+ extract_resp.raise_for_status()
+ extract_data = extract_resp.json()
+
+ pages = extract_data.get("query", {}).get("pages", {})
+ for page in pages.values():
+ extract = page.get("extract", "")
+ if extract:
+ # 清理 Wikipedia 的标记
+ extract = re.sub(r'\[\d+\]', '', extract) # 移除引用标记如 [1]
+ extract = re.sub(r'\s+', ' ', extract).strip()
+ return extract[:max_chars]
+
+ return ""
+
+
+async def search_duckduckgo(query: str, max_results: int = 5) -> str:
+ """
+ 使用 DuckDuckGo HTML 版搜索。若被限制则回退到 Wikipedia。
+ """
+ url = f"https://html.duckduckgo.com/html/?q={quote(query)}"
+ headers = {
+ "User-Agent": (
+ "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
+ "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36"
+ ),
+ "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
+ "Accept-Language": "zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7",
+ }
+
+ try:
+ async with httpx.AsyncClient(timeout=30, follow_redirects=True) as client:
+ resp = await client.get(url, headers=headers)
+ resp.raise_for_status()
+ html = resp.text
+
+ # 快速检查是否是有效的结果页（而不是主页/验证页）
+ if "web-result" not in html and "result__snippet" not in html and "result__title" not in html:
+ raise RuntimeError("DuckDuckGo 返回了非结果页面")
+
+ results: list[str] = []
+
+ # 尝试匹配标准 result 块
+ result_blocks = re.findall(
+ r']*>.*?
]*class="result__title"[^>]*>.*?]*>(.*?).*?]*>.*?
]*class="result__snippet"[^>]*>(.*?).*?