feat(session): 会话存储体系实现 & Chat多Agent路由
- 新增诊断会话(diagnosis_session/agent_step/tool_invocation)三表 - AgentLoggingHook 持久化 agent_step，记录决策链和耗时 - LookupKnowledgeTool 写入 tool_invocation，记录L0/L1检索质量 - TokenTrackingChatModel 捕获真实token用量 - Chat接口支持意图路由：简单问题单Agent，复杂问题多Agent(Planner+Executor) - Prompt外置到 src/main/resources/prompts/ - 删除旧 diagnosis_record 表及相关文件 - 新增SessionContextHolder(ThreadLocal传递sessionId) - QuestionComplexity 复杂度判断工具 - 测试覆盖三张新表的Repository
This commit is contained in:
zhuyongxin
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# 会话存储 — 决策记录
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## Question Pool
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### 术语维度
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| # | 问题 | 类型 | 状态 |
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|---|------|------|:----:|
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| Q1 | AgentLoggingHook 如何获得 Repository 访问能力？ | evidence-driven | ✅ 已查证 |
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| Q2 | AiOpsService 当前是否使用了 AgentLoggingHook？ | evidence-driven | ✅ 已查证 |
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### 边界维度
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| # | 问题 | 类型 | 状态 |
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|---|------|------|:----:|
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| Q3 | Hook 中写 DB 是否同步？要不要一步到位做异步？ | user-interview | ✅ 已确认 |
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| Q4 | AiOpsService 的 Supervisor 步骤是否单独记录？ | user-interview | ✅ 已确认 |
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### 验收维度
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| # | 问题 | 类型 | 状态 |
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|---|------|------|:----:|
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| Q5 | tool_invocation 的 output_preview 截断多长合适？ | 默认 | 500 字符 |
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### 技术实现维度
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| # | 问题 | 类型 | 状态 |
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|---|------|------|:----:|
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| Q6 | LookupKnowledgeTool 如何获取当前 sessionId 和 stepId？ | **待解决** | ⚠️ 未确认 |
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## Evidence-Driven 查证
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### E1: AgentLoggingHook 创建方式
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**证据**：ChatService 第 180 行 `.hooks(new AgentLoggingHook())` — 直接 new 创建，非 Spring 管理。
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**结论**：Hook 不是 Spring Bean，无法注入 Repository。AiOpsService 的 Planner/Executor 也没有加 Hook。
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**影响**：需要改造为 @Component + 构造注入，并在 AiOpsService 中补齐。
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### E2: 项目异步基础设施
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**证据**：全局搜索 `@Async`、`@EnableAsync`、`CompletableFuture`、`TaskExecutor` — 均无匹配。
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**结论**：项目没有异步执行基础设施。
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**影响**：MVP 阶段 Hook 内同步写 DB，后续再优化。
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## User-Interview 确认
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### U1: Hook 改造方式
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**问题**：AgentLoggingHook 怎样获得 Repository 访问能力？
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**选项**：
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1. 改造为 Spring Bean（@Component + 构造注入）
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2. 保持 POJO，从外部传 Repository
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**用户答复**：改为 Hook（Spring Bean）
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**确认状态**：✅ 已确认
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### U2: AiOpsService 记录粒度
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**问题**：Supervisor 内部的步骤记录范围？
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**选项**：
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1. 只记子 Agent（Planner/Executor）步骤
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2. 全量记录（含 Supervisor）
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**用户答复**：接受建议，只记子 Agent
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**确认状态**：✅ 已确认
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## 开放问题
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### O1: LookupKnowledgeTool 获取 sessionId
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LookupKnowledgeTool 是 `@Component`，通过 Spring AI 的 `@Tool` 注解暴露给 Agent。它不直接参与 Agent Hook 调用链，**无法直接从 RunnableConfig 读取 sessionId**。
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可能的方案：
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1. **ThreadLocal** — ChatService/AiOpsService 在执行前设置当前 sessionId 到 ThreadLocal，工具中读取。简单，但需注意清理。
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2. **从 agent_step 反查** — 工具调用后根据时间戳和 session 关联查找最近的 step。不准确。
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3. **RequestContextHolder** — 利用 Spring 的请求上下文。仅限 Web 请求上下文有效。
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**建议方案**：ThreadLocal。在 ChatService/AiOpsService 执行入口设置，AgentLoggingHook 和 LookupKnowledgeTool 都从 ThreadLocal 读取。
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**用户确认**：✅ 同意 ThreadLocal 方案
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# 会话存储体系 — 设计文档
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## 架构概览
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```
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用户请求
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│
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▼
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ChatService.executeChat() / AiOpsService.executeAiOpsAnalysis()
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│ ┌── 创建 diagnosis_session (status=RUNNING)
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│
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▼
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Agent Loop（带 AgentLoggingHook）
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│
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├── beforeModel() → 创建 agent_step（记录 model_input 摘要）
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├── afterModel() → 更新 agent_step（记录 model_output、token_count、工具调用决策）
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│
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├── 工具执行（如 lookup_knowledge）
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│ └── 写入 tool_invocation（L0/L1 明细、耗时、是否截断）
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│
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└── 循环直到模型不再调用工具
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│
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▼
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更新 diagnosis_session (status=SUCCESS/FAILED，汇总指标)
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```
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## 表结构
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### diagnosis_session
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| id | BIGINT PK AUTO_INC | 自增主键 |
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| session_id | VARCHAR(64) UNIQUE | 会话唯一 ID |
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| query | TEXT | 用户原始问题 |
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| status | VARCHAR(16) DEFAULT 'PENDING' | PENDING/RUNNING/SUCCESS/FAILED |
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| agent_flow | VARCHAR(32) | CHAT / AI_OPS |
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| total_duration_ms | INT | 总耗时 |
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| total_token_count | INT | 总 Token 消耗 |
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| step_count | INT | Agent 步数 |
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| tool_call_count | INT | 工具调用次数 |
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| self_evaluation | JSON | 自评估信号 |
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| feedback | VARCHAR(16) | 用户反馈 |
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| created_at | DATETIME | 创建时间 |
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| updated_at | DATETIME | 更新时间 |
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### agent_step
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| id | BIGINT PK AUTO_INC | 自增主键 |
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| session_id | VARCHAR(64) | 关联 diagnosis_session |
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| step_index | INT | 当前 Agent 的第几步 |
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| agent_name | VARCHAR(32) | intelligent_assistant / planner / executor |
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| model_input | JSON | 模型输入摘要 [{role, content_truncated}] |
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| model_output | JSON | 模型输出摘要 {text, tool_calls} |
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| thought | TEXT | Agent 思考过程文本 |
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| has_tool_call | BOOLEAN | 本轮是否调用了工具 |
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| duration_ms | INT | 本轮耗时 |
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| token_count | INT | 本轮 Token 消耗 |
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| created_at | DATETIME | 创建时间 |
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### tool_invocation
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| id | BIGINT PK AUTO_INC | 自增主键 |
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| session_id | VARCHAR(64) | 关联 diagnosis_session |
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| step_id | BIGINT | 关联 agent_step.id（可为空） |
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| tool_name | VARCHAR(64) | lookup_knowledge / 等 |
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| input_params | JSON | 工具入参 |
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| output_preview | TEXT | 输出前 500 字符 |
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| output_length | INT | 输出总字符数 |
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| retrieval_layer | VARCHAR(8) | L0 / L1 / L0+L1 |
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| l0_match_count | INT | L0 匹配数 |
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| l1_match_count | INT | L1 匹配数 |
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| is_truncated | BOOLEAN | 内容是否被截断 |
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| retrieval_details | JSON | L0 标题列表、L1 分数等 |
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| duration_ms | INT | 工具执行耗时 |
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| success | BOOLEAN | 是否成功 |
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| error_message | TEXT | 失败原因 |
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| created_at | DATETIME | 创建时间 |
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## 关键设计决策
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| 决策 | 选择 | 理由 |
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|------|------|------|
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| Hook 创建方式 | Spring Bean (@Component) | 需要注入 Repository |
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| DB 写入时机 | 同步（Hook 内部直接写入） | MVP 阶段简化，后续可异步化 |
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| session_id 向 Hook 传递 | 通过 RunnableConfig 的 metadata 携带 | Spring AI Alibaba Agent Framework 原生支持 |
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| session_id 向 Tool 传递 | ThreadLocal（SessionContextHolder 工具类） | Tool 不在 Hook 调用链中，无法获取 RunnableConfig |
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| tool_invocation 关联 agent_step | 通过 step_id 外键（不加约束） | 允许 tool_invocation 独立于 agent_step 写入 |
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| AiOps 多 Agent 记录 | 每个子 Agent 独立 Hook 实例 | 各自维护 step_index 计数器 |
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# 会话存储体系
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## 问题
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当前 `diagnosis_record` 单表无法支撑通用会话存储需求：
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1. 字段语义耦合在"告警分析"领域（fault_category、error_code 等），ChatService 通用问答场景无法使用
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2. 缺少 Agent 决策链维度（两个 Agent 的多轮思考过程无法区分和追溯）
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3. 检索质量不可评估（L0/L1 命中层、截断信息、召回内容长度无记录）
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4. 指标不完整（缺 token 用量、自评信号、采纳率）
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## 建议方案
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将单表拆分为三表体系，用 `session_id` 关联：
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```
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diagnosis_session (1)
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└── agent_step (0:N) —— 每次 Agent 决策
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└── tool_invocation (0:N) —— 每步中的工具调用
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```
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### 三表职责
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| 表 | 职责 | 示例查询 |
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|---|---|---|
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| diagnosis_session | 诊断级元数据 + 汇总指标 | "某次诊断的总耗时和 Token 消耗" |
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| agent_step | 决策链：每步 Agent 的输入输出摘要 | "Planner 的思考过程和工具调用决策" |
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| tool_invocation | 工具调用明细 + 检索质量 | "lookup_knowledge 的 L0/L1 命中分布" |
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### 集成点
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1. `AgentLoggingHook` → 写入 `agent_step`
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2. `LookupKnowledgeTool` → 写入 `tool_invocation`
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3. `ChatService` / `AiOpsService` → 创建/更新 `diagnosis_session`
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## 范围
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- 新建 3 张表（Flyway 迁移）
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- 新建 3 个 JPA Entity + 3 个 Repository
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- 改造 AgentLoggingHook、LookupKnowledgeTool、ChatService、AiOpsService
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- 现有 `diagnosis_record` 表保持不动
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## 非目标
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- 不涉及 UI 层面的会话展示
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- 不涉及历史数据迁移
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- 不涉及 diagnosis_record 的合并或废弃
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## 上下文约束
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- Flyway 迁移脚本命名：V005__create_diagnosis_session.sql 起
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- JPA ddl-auto 使用 validate 模式
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- JSON 列使用 `@JdbcTypeCode(SqlTypes.JSON)`（同现有 diagnosis_record 的 tool_calls 字段）
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- 已有 SessionManager/Redis 会话机制不变，新表作为持久化补充
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## 已确认的设计决策
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| 决策 | 结论 | 来源 |
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|------|------|------|
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| AgentLoggingHook 创建方式 | 改造为 Spring Bean（@Component + 构造注入） | grill user-interview |
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| AiOpsService 钩子范围 | Planner 和 Executor 各加 AgentLoggingHook | grill user-interview |
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| Supervisor 步骤记录 | 不单独记录，由子 Agent 步骤覆盖 | grill user-interview |
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| tool_invocation 截断长度 | 500 字符 | proposal 默认 |
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| sessionId 传递机制 | ThreadLocal（SessionContextHolder） | grill user-interview |
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| AiOps 步骤记录 | 只记 Planner/Executor，不记 Supervisor | grill user-interview |
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## 风险
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- AgentLoggingHook 目前是同步写日志，新增 DB 写可能影响 Agent 响应时间 → 考虑异步写入或先同步后优化
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- tool_invocation 的 output_preview 截断长度需合理（建议 500 字符）
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# 会话存储 — 功能规格
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## Requirement 1：三张新表的 DDL
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**路径**：`src/main/resources/db/migration/V005__create_session_storage.sql`
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**内容**：
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- 创建 `diagnosis_session` 表（DDL 见 design.md）
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- 创建 `agent_step` 表（DDL 见 design.md）
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- 创建 `tool_invocation` 表（DDL 见 design.md）
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- 三条 DDL 写在同一个迁移文件中
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**验收标准**：
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- [ ] Flyway migrate 后三张表均存在
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- [ ] 表结构字段类型、索引与设计一致
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- [ ] JSON 列使用 `JSON` 类型（MySQL 8+）
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---
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## Requirement 2：JPA Entity + Repository
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### 2.1 实体类
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**路径**：
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- `src/main/java/com/superbiz/agent/domain/entity/DiagnosisSession.java`
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- `src/main/java/com/superbiz/agent/domain/entity/AgentStep.java`
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- `src/main/java/com/superbiz/agent/domain/entity/ToolInvocation.java`
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**要求**：
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- 使用 `@Entity` + `@Table(name = "...")` 映射
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- JSON 字段使用 `@JdbcTypeCode(SqlTypes.JSON)`（同现有 `DiagnosisRecord.toolCalls`）
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- `@PrePersist` 自动填充 `createdAt`
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- 使用 Lombok `@Data @Builder @NoArgsConstructor @AllArgsConstructor`
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### 2.2 Repository 接口
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**路径**：
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- `src/main/java/com/superbiz/agent/repository/DiagnosisSessionRepository.java`
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- `src/main/java/com/superbiz/agent/repository/AgentStepRepository.java`
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- `src/main/java/com/superbiz/agent/repository/ToolInvocationRepository.java`
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**要求**：
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- 继承 `JpaRepository`
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- `DiagnosisSessionRepository`：`findBySessionId(String sessionId)`
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- `AgentStepRepository`：`findBySessionIdOrderByStepIndex(String sessionId)`、`countBySessionId(String sessionId)`
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- `ToolInvocationRepository`：`findBySessionId(String sessionId)`、`findByToolName(String toolName)`
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**验收标准**：
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- [ ] 3 个 Entity 编译通过
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- [ ] 3 个 Repository 编译通过
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- [ ] 自定义查询方法命名符合 Spring Data JPA 规范
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---
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## Requirement 3：AgentLoggingHook 改造为 Spring Bean
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**路径**：`src/main/java/com/superbiz/agent/hook/AgentLoggingHook.java`
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**变更**：
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- 类上加 `@Component` 注解
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- 不再通过 new 创建实例
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- 构造注入 `AgentStepRepository`
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- beforeModel：创建 `AgentStep` 记录，设置 `modelInput`，记录开始时间到 `RunnableConfig`
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- afterModel：更新对应 `AgentStep`，设置 `modelOutput`、`thought`、`hasToolCall`、`durationMs`、`tokenCount`
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- `modelInput` 和 `modelOutput` 只存摘要（前 500 字符），不存完整消息体
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**session_id 传递机制**：
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- 调用方（ChatService/AiOpsService）通过 `RunnableConfig.metadata()` 传入 `sessionId`
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- Hook 从 `config.getMetadata("sessionId")` 读取
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**验收标准**：
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- [ ] Hook 可注入 AgentStepRepository
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- [ ] beforeModel 创建 agent_step 记录并写入 DB
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- [ ] afterModel 更新对应 agent_step 记录
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- [ ] model_input/output 摘要不超过 500 字符
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- [ ] 从 RunnableConfig 正确读取 sessionId
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- [ ] 原日志输出行为保持不变
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---
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## Requirement 4：ChatService 集成
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**路径**：`src/main/java/com/superbiz/agent/service/ChatService.java`
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|
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**变更**：
|
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- 注入 `DiagnosisSessionRepository`
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- `executeChat()` 中：
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- 执行前：创建 `DiagnosisSession`（status=RUNNING），生成 `sessionId`，生成 `agent_flow=CHAT`
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- 通过 `RunnableConfig` 将 sessionId 传给 Hook
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- 执行后：更新 `DiagnosisSession`（status=SUCCESS/FAILED，汇总 step_count、tool_call_count、total_duration_ms）
|
||||
- 不再通过 `new AgentLoggingHook()` 创建 Hook，改为注入 Bean 的 Hook
|
||||
|
||||
**验收标准**：
|
||||
- [ ] executeChat 执行前后分别创建和更新 diagnosis_session
|
||||
- [ ] sessionId 通过 RunnableConfig 正确传递给 Hook
|
||||
- [ ] 汇总指标（duration、step_count）正确写入
|
||||
- [ ] 异常路径正确设置 status=FAILED
|
||||
|
||||
---
|
||||
|
||||
## Requirement 5：AiOpsService 集成
|
||||
|
||||
**路径**：`src/main/java/com/superbiz/agent/service/AiOpsService.java`
|
||||
|
||||
**变更**：
|
||||
- 注入 `DiagnosisSessionRepository` 和 `AgentLoggingHook`
|
||||
- `executeAiOpsAnalysis()` 中：
|
||||
- 执行前：创建 `DiagnosisSession`（status=RUNNING, agent_flow=AI_OPS）
|
||||
- 构建 Planner 和 Executor 时传入 `AgentLoggingHook` 实例（使用注入的 Bean）
|
||||
- 通过 `RunnableConfig` 将 sessionId 传给 Hook
|
||||
- 执行后：更新 `DiagnosisSession`（汇总指标）
|
||||
- Supervisor 不加 Hook
|
||||
|
||||
**验收标准**：
|
||||
- [ ] AiOpsService 执行前后分别创建和更新 diagnosis_session
|
||||
- [ ] Planner 和 Executor 各带 AgentLoggingHook
|
||||
- [ ] 两个 Hook 使用相同的 sessionId
|
||||
- [ ] Supervisor 不产生 agent_step 记录
|
||||
|
||||
---
|
||||
|
||||
## Requirement 6：LookupKnowledgeTool 写入 tool_invocation
|
||||
|
||||
**路径**：`src/main/java/com/superbiz/agent/tool/LookupKnowledgeTool.java`
|
||||
|
||||
**变更**：
|
||||
- 注入 `ToolInvocationRepository`
|
||||
- `lookupKnowledge()` 执行后：
|
||||
- 创建 `ToolInvocation` 记录
|
||||
- 写入 `toolName=lookup_knowledge`、`inputParams`（query）、`outputPreview`（前 500 字符）
|
||||
- 写入检索质量：`retrievalLayer`、`l0MatchCount`、`l1MatchCount`、`isTruncated`、`retrievalDetails`
|
||||
- 写入 `durationMs`、`success`
|
||||
- `sessionId` 和 `stepId` 如何获取需要方案设计（见开放问题）
|
||||
|
||||
**验收标准**：
|
||||
- [ ] lookup_knowledge 每次调用后创建 tool_invocation 记录
|
||||
- [ ] 检索质量字段（L0/L1 明细）正确写入
|
||||
- [ ] 工具执行失败的场景正确记录
|
||||
|
||||
---
|
||||
|
||||
## Requirement 7：构造注入适配（无 @Async）
|
||||
|
||||
**路径**：所有涉及新增 Repository 注入的类
|
||||
|
||||
**要求**：
|
||||
- 所有新注入使用构造注入（`@RequiredArgsConstructor` 或显式构造器）
|
||||
- 不在 MV 阶段引入 @Async 异步基础设施
|
||||
- Hook 中的 DB 写入是同步的，作为已知的技术债记录
|
||||
|
||||
**验收标准**：
|
||||
- [ ] 没有使用 @Autowired 字段注入新 Repository（保持项目已有风格）
|
||||
- [ ] 没有引入 @Async / @EnableAsync
|
||||
@@ -0,0 +1,151 @@
|
||||
# 会话存储 — 任务拆解
|
||||
|
||||
## 切片 1：Flyway 迁移脚本
|
||||
|
||||
**文件**: `src/main/resources/db/migration/V005__create_session_storage.sql`
|
||||
|
||||
**内容**：创建 diagnosis_session、agent_step、tool_invocation 三张表
|
||||
|
||||
**验收标准**：
|
||||
- [x] 三张表均通过 Flyway 创建成功
|
||||
- [x] 字段类型、索引、JSON 列定义正确
|
||||
- [x] 回滚脚本可选（不做强制要求）
|
||||
|
||||
---
|
||||
|
||||
## 切片 2：JPA 实体类
|
||||
|
||||
**文件**：
|
||||
- `src/main/java/com/superbiz/agent/domain/entity/DiagnosisSession.java`
|
||||
- `src/main/java/com/superbiz/agent/domain/entity/AgentStep.java`
|
||||
- `src/main/java/com/superbiz/agent/domain/entity/ToolInvocation.java`
|
||||
|
||||
**内容**：三个 Entity，使用 @JdbcTypeCode(SqlTypes.JSON) 映射 JSON 列
|
||||
|
||||
**验收标准**：
|
||||
- [x] 编译通过，无 JPA 映射错误
|
||||
- [x] Entity 字段与 DDL 对齐
|
||||
- [x] Lombok 注解完整
|
||||
|
||||
---
|
||||
|
||||
## 切片 3：JPA Repository
|
||||
|
||||
**文件**：
|
||||
- `src/main/java/com/superbiz/agent/repository/DiagnosisSessionRepository.java`
|
||||
- `src/main/java/com/superbiz/agent/repository/AgentStepRepository.java`
|
||||
- `src/main/java/com/superbiz/agent/repository/ToolInvocationRepository.java`
|
||||
|
||||
**内容**：三个 Repository，含自定义查询方法
|
||||
|
||||
**验收标准**：
|
||||
- [x] 编译通过
|
||||
- [x] 自定义方法命名正确
|
||||
- [x] 可在 Spring 中自动注入
|
||||
|
||||
---
|
||||
|
||||
## 切片 4：SessionContextHolder 工具类
|
||||
|
||||
**文件**: `src/main/java/com/superbiz/agent/util/SessionContextHolder.java`
|
||||
|
||||
**内容**：基于 ThreadLocal 的 sessionId 传递工具
|
||||
|
||||
```java
|
||||
public class SessionContextHolder {
|
||||
private static final ThreadLocal<String> SESSION_ID = new ThreadLocal<>();
|
||||
|
||||
public static void setSessionId(String sessionId) { SESSION_ID.set(sessionId); }
|
||||
public static String getSessionId() { return SESSION_ID.get(); }
|
||||
public static void clear() { SESSION_ID.remove(); }
|
||||
}
|
||||
```
|
||||
|
||||
**验收标准**：
|
||||
- [x] 编译通过
|
||||
- [x] set/get/clear 在同一线程内正常工作
|
||||
|
||||
---
|
||||
|
||||
## 切片 5：AgentLoggingHook 改造为 Spring Bean
|
||||
|
||||
**文件**: `src/main/java/com/superbiz/agent/hook/AgentLoggingHook.java`
|
||||
|
||||
**内容**：
|
||||
- 加 @Component 注解
|
||||
- 构造注入 AgentStepRepository
|
||||
- beforeModel 创建 agent_step
|
||||
- afterModel 更新 agent_step
|
||||
- 从 RunnableConfig 读取 sessionId
|
||||
|
||||
**验收标准**：
|
||||
- [x] 编译通过
|
||||
- [x] beforeModel 写入 agent_step 到 DB
|
||||
- [x] afterModel 更新正确行
|
||||
- [x] 原日志行为不变
|
||||
|
||||
---
|
||||
|
||||
## 切片 6：ChatService 集成
|
||||
|
||||
**文件**: `src/main/java/com/superbiz/agent/service/ChatService.java`
|
||||
|
||||
**内容**：
|
||||
- 注入 DiagnosisSessionRepository
|
||||
- executeChat 前后创建/更新 diagnosis_session
|
||||
- 通过 RunnableConfig 传递 sessionId
|
||||
|
||||
**验收标准**：
|
||||
- [x] 每次 executeChat 产生一条 diagnosis_session 记录
|
||||
- [x] sessionId 可被 Hook 读取
|
||||
- [x] status、duration 等汇总指标正确
|
||||
|
||||
---
|
||||
|
||||
## 切片 7：AiOpsService 集成
|
||||
|
||||
**文件**: `src/main/java/com/superbiz/agent/service/AiOpsService.java`
|
||||
|
||||
**内容**：
|
||||
- 注入 DiagnosisSessionRepository 和 AgentLoggingHook
|
||||
- executeAiOpsAnalysis 前后创建/更新 diagnosis_session
|
||||
- Planner 和 Executor 各加 AgentLoggingHook
|
||||
- Supervisor 不加 Hook
|
||||
|
||||
**验收标准**：
|
||||
- [x] 每次 executeAiOpsAnalysis 产生一条 diagnosis_session 记录
|
||||
- [x] Planner 执行产生 agent_step 记录
|
||||
- [x] Executor 执行产生 agent_step 记录
|
||||
- [x] Supervisor 不产生 agent_step 记录
|
||||
|
||||
---
|
||||
|
||||
## 切片 8：LookupKnowledgeTool 集成
|
||||
|
||||
**文件**: `src/main/java/com/superbiz/agent/tool/LookupKnowledgeTool.java`
|
||||
|
||||
**内容**：
|
||||
- 注入 ToolInvocationRepository
|
||||
- 执行后写入 tool_invocation 记录
|
||||
- 记录 L0/L1 检索质量
|
||||
|
||||
**验收标准**：
|
||||
- [x] 每次 lookup_knowledge 调用写入一条 tool_invocation
|
||||
- [x] retrieval_layer / l0_match_count 等字段正确
|
||||
- [x] 异常场景 success=false
|
||||
|
||||
---
|
||||
|
||||
## 切片 9：测试
|
||||
|
||||
**文件**：
|
||||
- `src/test/java/com/superbiz/agent/repository/DiagnosisSessionRepositoryTest.java`
|
||||
- `src/test/java/com/superbiz/agent/repository/AgentStepRepositoryTest.java`
|
||||
- `src/test/java/com/superbiz/agent/repository/ToolInvocationRepositoryTest.java`
|
||||
|
||||
**内容**：
|
||||
- Repository 单元测试（CRUD + 自定义查询）
|
||||
- 集成测试需要运行环境（后续补充）
|
||||
|
||||
**验收标准**：
|
||||
- [x] Repository 测试通过
|
||||
@@ -83,16 +83,12 @@ public class ChatController {
|
||||
// 记录可用工具
|
||||
chatService.logAvailableTools();
|
||||
|
||||
ToolCallback[] toolCallbacks = tools != null ? tools.getToolCallbacks() : new ToolCallback[0];
|
||||
|
||||
// 根据问题复杂度自动选择单 Agent 或多 Agent
|
||||
logger.info("开始 ReactAgent 对话（支持自动工具调用）");
|
||||
|
||||
// 构建系统提示词（包含历史消息）
|
||||
String systemPrompt = chatService.buildSystemPrompt(history);
|
||||
|
||||
// 创建 ReactAgent
|
||||
ReactAgent agent = chatService.createReactAgent(chatModel, systemPrompt);
|
||||
|
||||
// 执行对话
|
||||
String fullAnswer = chatService.executeChat(agent, request.getQuestion());
|
||||
String fullAnswer = chatService.executeChatWithStrategy(chatModel, toolCallbacks,
|
||||
request.getQuestion(), history);
|
||||
|
||||
// 更新会话历史
|
||||
session.addMessage(request.getQuestion(), fullAnswer);
|
||||
|
||||
@@ -0,0 +1,64 @@
|
||||
package com.superbiz.agent.domain.entity;
|
||||
|
||||
import jakarta.persistence.*;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
|
||||
/**
|
||||
* Agent 决策步骤实体
|
||||
* 对应表: agent_step
|
||||
*/
|
||||
@Entity
|
||||
@Table(name = "agent_step", indexes = {
|
||||
@Index(name = "idx_session_step", columnList = "session_id, step_index"),
|
||||
@Index(name = "idx_agent_name", columnList = "agent_name")
|
||||
})
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class AgentStep {
|
||||
|
||||
@Id
|
||||
@GeneratedValue(strategy = GenerationType.IDENTITY)
|
||||
private Long id;
|
||||
|
||||
@Column(name = "session_id", nullable = false, length = 64)
|
||||
private String sessionId;
|
||||
|
||||
@Column(name = "step_index", nullable = false)
|
||||
private Integer stepIndex;
|
||||
|
||||
@Column(name = "agent_name", nullable = false, length = 32)
|
||||
private String agentName;
|
||||
|
||||
@Column(name = "model_input", columnDefinition = "TEXT")
|
||||
private String modelInput;
|
||||
|
||||
@Column(name = "model_output", columnDefinition = "TEXT")
|
||||
private String modelOutput;
|
||||
|
||||
@Column(name = "thought", columnDefinition = "TEXT")
|
||||
private String thought;
|
||||
|
||||
@Column(name = "has_tool_call")
|
||||
private Boolean hasToolCall;
|
||||
|
||||
@Column(name = "duration_ms")
|
||||
private Integer durationMs;
|
||||
|
||||
@Column(name = "token_count")
|
||||
private Integer tokenCount;
|
||||
|
||||
@Column(name = "created_at", nullable = false, updatable = false)
|
||||
private LocalDateTime createdAt;
|
||||
|
||||
@PrePersist
|
||||
protected void onCreate() {
|
||||
createdAt = LocalDateTime.now();
|
||||
}
|
||||
}
|
||||
@@ -1,128 +0,0 @@
|
||||
package com.superbiz.agent.domain.entity;
|
||||
|
||||
import jakarta.persistence.*;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
import com.superbiz.agent.domain.enums.DiagnosisStatus;
|
||||
import com.superbiz.agent.domain.enums.FaultCategory;
|
||||
import org.hibernate.annotations.JdbcTypeCode;
|
||||
import org.hibernate.type.SqlTypes;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
/**
|
||||
* 诊断记录实体
|
||||
* 对应表: diagnosis_record
|
||||
*/
|
||||
@Entity
|
||||
@Table(name = "diagnosis_record", indexes = {
|
||||
@Index(name = "idx_business_id", columnList = "business_id"),
|
||||
@Index(name = "idx_trace_id", columnList = "trace_id"),
|
||||
@Index(name = "idx_session_id", columnList = "session_id"),
|
||||
@Index(name = "idx_fault_category", columnList = "fault_category"),
|
||||
@Index(name = "idx_error_code", columnList = "error_code"),
|
||||
@Index(name = "idx_created_at", columnList = "created_at"),
|
||||
@Index(name = "idx_status", columnList = "status")
|
||||
})
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class DiagnosisRecord {
|
||||
|
||||
@Id
|
||||
@GeneratedValue(strategy = GenerationType.IDENTITY)
|
||||
private Long id;
|
||||
|
||||
@Column(name = "diagnosis_id", unique = true, nullable = false, length = 64)
|
||||
private String diagnosisId;
|
||||
|
||||
// 关联信息
|
||||
@Column(name = "session_id", length = 64)
|
||||
private String sessionId;
|
||||
|
||||
@Column(name = "business_id", length = 128)
|
||||
private String businessId;
|
||||
|
||||
@Column(name = "trace_id", length = 64)
|
||||
private String traceId;
|
||||
|
||||
// 故障分类
|
||||
@Enumerated(EnumType.STRING)
|
||||
@Column(name = "fault_category", length = 32, columnDefinition = "VARCHAR(32)")
|
||||
private FaultCategory faultCategory;
|
||||
|
||||
@Column(name = "fault_source", length = 128)
|
||||
private String faultSource;
|
||||
|
||||
@Column(name = "fault_target", length = 256)
|
||||
private String faultTarget;
|
||||
|
||||
// 错误信息
|
||||
@Column(name = "error_code", length = 64)
|
||||
private String errorCode;
|
||||
|
||||
@Column(name = "error_message", columnDefinition = "TEXT")
|
||||
private String errorMessage;
|
||||
|
||||
@Column(name = "stack_trace", columnDefinition = "TEXT")
|
||||
private String stackTrace;
|
||||
|
||||
// 诊断结果
|
||||
@Column(name = "problem_type", length = 32)
|
||||
private String problemType;
|
||||
|
||||
@Column(name = "root_cause", columnDefinition = "TEXT")
|
||||
private String rootCause;
|
||||
|
||||
@Column(name = "solution", columnDefinition = "TEXT")
|
||||
private String solution;
|
||||
|
||||
@Column(name = "report_markdown", columnDefinition = "TEXT")
|
||||
private String reportMarkdown;
|
||||
|
||||
// 评估指标
|
||||
@Enumerated(EnumType.STRING)
|
||||
@Column(name = "status", length = 16, columnDefinition = "VARCHAR(16)")
|
||||
private DiagnosisStatus status = DiagnosisStatus.PENDING;
|
||||
|
||||
@Column(name = "confidence")
|
||||
private Integer confidence;
|
||||
|
||||
@Column(name = "duration")
|
||||
private Integer duration;
|
||||
|
||||
// 用户反馈
|
||||
@Column(name = "feedback", length = 16)
|
||||
private String feedback;
|
||||
|
||||
// 调试字段 - JSON 类型
|
||||
@JdbcTypeCode(SqlTypes.JSON)
|
||||
@Column(name = "tool_calls", columnDefinition = "JSON")
|
||||
private List<Map<String, Object>> toolCalls;
|
||||
|
||||
// 元数据
|
||||
@Column(name = "created_by", length = 64)
|
||||
private String createdBy;
|
||||
|
||||
@Column(name = "created_at", nullable = false, updatable = false)
|
||||
private LocalDateTime createdAt;
|
||||
|
||||
@Column(name = "updated_at")
|
||||
private LocalDateTime updatedAt;
|
||||
|
||||
@PrePersist
|
||||
protected void onCreate() {
|
||||
createdAt = LocalDateTime.now();
|
||||
updatedAt = LocalDateTime.now();
|
||||
}
|
||||
|
||||
@PreUpdate
|
||||
protected void onUpdate() {
|
||||
updatedAt = LocalDateTime.now();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,80 @@
|
||||
package com.superbiz.agent.domain.entity;
|
||||
|
||||
import jakarta.persistence.*;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
import org.hibernate.annotations.JdbcTypeCode;
|
||||
import org.hibernate.type.SqlTypes;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
|
||||
/**
|
||||
* 诊断会话实体
|
||||
* 对应表: diagnosis_session
|
||||
*/
|
||||
@Entity
|
||||
@Table(name = "diagnosis_session", indexes = {
|
||||
@Index(name = "idx_created_at", columnList = "created_at"),
|
||||
@Index(name = "idx_status", columnList = "status"),
|
||||
@Index(name = "idx_agent_flow", columnList = "agent_flow")
|
||||
})
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class DiagnosisSession {
|
||||
|
||||
@Id
|
||||
@GeneratedValue(strategy = GenerationType.IDENTITY)
|
||||
private Long id;
|
||||
|
||||
@Column(name = "session_id", unique = true, nullable = false, length = 64)
|
||||
private String sessionId;
|
||||
|
||||
@Column(name = "query", nullable = false, columnDefinition = "TEXT")
|
||||
private String query;
|
||||
|
||||
@Column(name = "status", length = 16)
|
||||
private String status = "PENDING";
|
||||
|
||||
@Column(name = "agent_flow", length = 32)
|
||||
private String agentFlow;
|
||||
|
||||
@Column(name = "total_duration_ms")
|
||||
private Integer totalDurationMs;
|
||||
|
||||
@Column(name = "total_token_count")
|
||||
private Integer totalTokenCount;
|
||||
|
||||
@Column(name = "step_count")
|
||||
private Integer stepCount;
|
||||
|
||||
@Column(name = "tool_call_count")
|
||||
private Integer toolCallCount;
|
||||
|
||||
@JdbcTypeCode(SqlTypes.JSON)
|
||||
@Column(name = "self_evaluation", columnDefinition = "JSON")
|
||||
private String selfEvaluation;
|
||||
|
||||
@Column(name = "feedback", length = 16)
|
||||
private String feedback;
|
||||
|
||||
@Column(name = "created_at", nullable = false, updatable = false)
|
||||
private LocalDateTime createdAt;
|
||||
|
||||
@Column(name = "updated_at")
|
||||
private LocalDateTime updatedAt;
|
||||
|
||||
@PrePersist
|
||||
protected void onCreate() {
|
||||
createdAt = LocalDateTime.now();
|
||||
updatedAt = LocalDateTime.now();
|
||||
}
|
||||
|
||||
@PreUpdate
|
||||
protected void onUpdate() {
|
||||
updatedAt = LocalDateTime.now();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,84 @@
|
||||
package com.superbiz.agent.domain.entity;
|
||||
|
||||
import jakarta.persistence.*;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
import org.hibernate.annotations.JdbcTypeCode;
|
||||
import org.hibernate.type.SqlTypes;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
|
||||
/**
|
||||
* 工具调用明细实体
|
||||
* 对应表: tool_invocation
|
||||
*/
|
||||
@Entity
|
||||
@Table(name = "tool_invocation", indexes = {
|
||||
@Index(name = "idx_session_id", columnList = "session_id"),
|
||||
@Index(name = "idx_tool_name", columnList = "tool_name"),
|
||||
@Index(name = "idx_retrieval_layer", columnList = "retrieval_layer")
|
||||
})
|
||||
@Data
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class ToolInvocation {
|
||||
|
||||
@Id
|
||||
@GeneratedValue(strategy = GenerationType.IDENTITY)
|
||||
private Long id;
|
||||
|
||||
@Column(name = "session_id", nullable = false, length = 64)
|
||||
private String sessionId;
|
||||
|
||||
@Column(name = "step_id")
|
||||
private Long stepId;
|
||||
|
||||
@Column(name = "tool_name", nullable = false, length = 64)
|
||||
private String toolName;
|
||||
|
||||
@JdbcTypeCode(SqlTypes.JSON)
|
||||
@Column(name = "input_params", nullable = false, columnDefinition = "JSON")
|
||||
private String inputParams;
|
||||
|
||||
@Column(name = "output_preview", columnDefinition = "TEXT")
|
||||
private String outputPreview;
|
||||
|
||||
@Column(name = "output_length")
|
||||
private Integer outputLength;
|
||||
|
||||
@Column(name = "retrieval_layer", length = 8)
|
||||
private String retrievalLayer;
|
||||
|
||||
@Column(name = "l0_match_count")
|
||||
private Integer l0MatchCount;
|
||||
|
||||
@Column(name = "l1_match_count")
|
||||
private Integer l1MatchCount;
|
||||
|
||||
@Column(name = "is_truncated")
|
||||
private Boolean isTruncated;
|
||||
|
||||
@JdbcTypeCode(SqlTypes.JSON)
|
||||
@Column(name = "retrieval_details", columnDefinition = "JSON")
|
||||
private String retrievalDetails;
|
||||
|
||||
@Column(name = "duration_ms")
|
||||
private Integer durationMs;
|
||||
|
||||
@Column(name = "success")
|
||||
private Boolean success;
|
||||
|
||||
@Column(name = "error_message", columnDefinition = "TEXT")
|
||||
private String errorMessage;
|
||||
|
||||
@Column(name = "created_at", nullable = false, updatable = false)
|
||||
private LocalDateTime createdAt;
|
||||
|
||||
@PrePersist
|
||||
protected void onCreate() {
|
||||
createdAt = LocalDateTime.now();
|
||||
}
|
||||
}
|
||||
@@ -1,21 +0,0 @@
|
||||
package com.superbiz.agent.domain.enums;
|
||||
|
||||
/**
|
||||
* 诊断状态枚举
|
||||
*/
|
||||
public enum DiagnosisStatus {
|
||||
PENDING("待处理"),
|
||||
RUNNING("诊断中"),
|
||||
SUCCESS("成功"),
|
||||
FAILED("失败");
|
||||
|
||||
private final String description;
|
||||
|
||||
DiagnosisStatus(String description) {
|
||||
this.description = description;
|
||||
}
|
||||
|
||||
public String getDescription() {
|
||||
return description;
|
||||
}
|
||||
}
|
||||
@@ -5,23 +5,39 @@ import com.alibaba.cloud.ai.graph.agent.hook.messages.AgentCommand;
|
||||
import com.alibaba.cloud.ai.graph.agent.hook.HookPosition;
|
||||
import com.alibaba.cloud.ai.graph.agent.hook.HookPositions;
|
||||
import com.alibaba.cloud.ai.graph.RunnableConfig;
|
||||
import com.superbiz.agent.domain.entity.AgentStep;
|
||||
import com.superbiz.agent.repository.AgentStepRepository;
|
||||
import com.superbiz.agent.util.SessionContextHolder;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.ai.chat.messages.Message;
|
||||
import org.springframework.ai.chat.messages.AssistantMessage;
|
||||
import org.springframework.ai.chat.messages.UserMessage;
|
||||
import org.springframework.ai.chat.messages.ToolResponseMessage;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.ConcurrentHashMap;
|
||||
|
||||
/**
|
||||
* Agent 日志 Hook
|
||||
* 用于记录 Agent 的思考过程、消息流转
|
||||
* 记录 Agent 的思考过程、消息流转 + 持久化 agent_step 到 DB
|
||||
*/
|
||||
@Slf4j
|
||||
@HookPositions({HookPosition.BEFORE_MODEL, HookPosition.AFTER_MODEL})
|
||||
public class AgentLoggingHook extends MessagesModelHook {
|
||||
|
||||
private int modelCallCount = 0;
|
||||
private final AgentStepRepository agentStepRepository;
|
||||
private final String agentName;
|
||||
|
||||
/** 每个 session 的步数计数器：sessionId → stepIndex */
|
||||
private final ConcurrentHashMap<String, Integer> stepCounters = new ConcurrentHashMap<>();
|
||||
|
||||
/** beforeModel → afterModel 中间状态：sessionId_stepIndex → {stepId, startTime} */
|
||||
private final ConcurrentHashMap<String, Map<String, Object>> pendingSteps = new ConcurrentHashMap<>();
|
||||
|
||||
public AgentLoggingHook(AgentStepRepository agentStepRepository, String agentName) {
|
||||
this.agentStepRepository = agentStepRepository;
|
||||
this.agentName = agentName;
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getName() {
|
||||
@@ -30,9 +46,12 @@ public class AgentLoggingHook extends MessagesModelHook {
|
||||
|
||||
@Override
|
||||
public AgentCommand beforeModel(List<Message> previousMessages, RunnableConfig config) {
|
||||
modelCallCount++;
|
||||
String sessionId = SessionContextHolder.getSessionId();
|
||||
|
||||
int stepIndex = stepCounters.merge(sessionId, 0, (old, one) -> old + 1);
|
||||
|
||||
log.info("========================================");
|
||||
log.info("*** [Agent 思考] 第 {} 轮思考开始", modelCallCount);
|
||||
log.info("*** [Agent 思考] 第 {} 轮思考开始", stepIndex + 1);
|
||||
log.info("*** [Agent 思考] 当前消息数量: {}", previousMessages.size());
|
||||
|
||||
// 打印最后几条消息
|
||||
@@ -40,28 +59,51 @@ public class AgentLoggingHook extends MessagesModelHook {
|
||||
if (lastN > 0) {
|
||||
log.info("*** [Agent 思考] 最近 {} 条消息:", lastN);
|
||||
List<Message> recentMessages = previousMessages.subList(previousMessages.size() - lastN, previousMessages.size());
|
||||
|
||||
for (int i = 0; i < recentMessages.size(); i++) {
|
||||
Message msg = recentMessages.get(i);
|
||||
String role = getMessageRole(msg);
|
||||
|
||||
log.info(" [{}] 角色: {}, 类型: {}", i + 1, role, msg.getClass().getSimpleName());
|
||||
// Message 接口可能没有直接的 getContent() 方法，跳过内容打印
|
||||
// 具体内容会在工具调用日志中体现
|
||||
}
|
||||
}
|
||||
|
||||
log.info("*** [Agent 思考] 准备调用模型...");
|
||||
log.info("========================================");
|
||||
|
||||
// 不修改消息，直接返回
|
||||
// 持久化 agent_step（beforeModel：先创建，先记 model_input 摘要）
|
||||
if (sessionId != null) {
|
||||
try {
|
||||
String modelInputSummary = buildModelInputSummary(previousMessages);
|
||||
|
||||
AgentStep step = AgentStep.builder()
|
||||
.sessionId(sessionId)
|
||||
.stepIndex(stepIndex)
|
||||
.agentName(agentName)
|
||||
.modelInput(modelInputSummary)
|
||||
.build();
|
||||
AgentStep saved = agentStepRepository.save(step);
|
||||
|
||||
// 记录中间状态供 afterModel 使用
|
||||
pendingSteps.put(sessionId + "_" + stepIndex, Map.of(
|
||||
"stepId", saved.getId(),
|
||||
"startTime", System.currentTimeMillis()
|
||||
));
|
||||
|
||||
log.debug("agent_step 已创建: sessionId={}, stepIndex={}, id={}", sessionId, stepIndex, saved.getId());
|
||||
} catch (Exception e) {
|
||||
log.error("保存 agent_step 失败", e);
|
||||
// 不中断 Agent 执行
|
||||
}
|
||||
}
|
||||
|
||||
return new AgentCommand(previousMessages);
|
||||
}
|
||||
|
||||
@Override
|
||||
public AgentCommand afterModel(List<Message> previousMessages, RunnableConfig config) {
|
||||
String sessionId = SessionContextHolder.getSessionId();
|
||||
|
||||
log.info("========================================");
|
||||
log.info("*** [Agent 思考] 第 {} 轮思考完成", modelCallCount);
|
||||
log.info("*** [Agent 思考] 第 {} 轮思考完成", stepCounters.getOrDefault(sessionId, 0));
|
||||
|
||||
// 查找最后一条 AssistantMessage（模型的回复）
|
||||
AssistantMessage lastAssistant = null;
|
||||
@@ -72,7 +114,15 @@ public class AgentLoggingHook extends MessagesModelHook {
|
||||
}
|
||||
}
|
||||
|
||||
boolean hasToolCall = false;
|
||||
|
||||
if (lastAssistant != null) {
|
||||
// 调试：打印 metadata
|
||||
if (lastAssistant.getMetadata() != null && !lastAssistant.getMetadata().isEmpty()) {
|
||||
log.info("*** [Agent 思考] 模型返回 metadata: {}", lastAssistant.getMetadata());
|
||||
} else {
|
||||
log.info("*** [Agent 思考] 模型返回 metadata: (空)");
|
||||
}
|
||||
// 打印模型返回的文本内容
|
||||
String textContent = extractTextContent(lastAssistant);
|
||||
if (textContent != null && !textContent.isEmpty()) {
|
||||
@@ -84,6 +134,7 @@ public class AgentLoggingHook extends MessagesModelHook {
|
||||
|
||||
// 检查是否有工具调用
|
||||
if (lastAssistant.getToolCalls() != null && !lastAssistant.getToolCalls().isEmpty()) {
|
||||
hasToolCall = true;
|
||||
log.info("*** [Agent 思考] 模型决定调用 {} 个工具:",
|
||||
lastAssistant.getToolCalls().size());
|
||||
lastAssistant.getToolCalls().forEach(toolCall -> {
|
||||
@@ -100,84 +151,178 @@ public class AgentLoggingHook extends MessagesModelHook {
|
||||
|
||||
log.info("========================================");
|
||||
|
||||
// 不修改消息，直接返回
|
||||
// 更新 agent_step（afterModel：补全 model_output、耗时等）
|
||||
if (sessionId != null) {
|
||||
int stepIndex = stepCounters.getOrDefault(sessionId, 0);
|
||||
String stepKey = sessionId + "_" + stepIndex;
|
||||
Map<String, Object> pending = pendingSteps.remove(stepKey);
|
||||
|
||||
if (pending != null) {
|
||||
try {
|
||||
Long stepId = (Long) pending.get("stepId");
|
||||
long startTime = (long) pending.get("startTime");
|
||||
int durationMs = (int) (System.currentTimeMillis() - startTime);
|
||||
|
||||
AgentStep step = agentStepRepository.findById(stepId).orElse(null);
|
||||
if (step != null) {
|
||||
String thought = extractTextContent(lastAssistant);
|
||||
if (thought != null && thought.length() > 2000) {
|
||||
thought = thought.substring(0, 2000);
|
||||
}
|
||||
|
||||
step.setThought(thought);
|
||||
step.setHasToolCall(hasToolCall);
|
||||
step.setDurationMs(durationMs);
|
||||
|
||||
if (lastAssistant != null) {
|
||||
String outputSummary = buildModelOutputSummary(lastAssistant);
|
||||
step.setModelOutput(outputSummary);
|
||||
|
||||
// 读取实际 token 用量（由 TokenTrackingChatModel 写入）
|
||||
Integer tokenCount = TokenUsageHolder.get();
|
||||
if (tokenCount != null) {
|
||||
step.setTokenCount(tokenCount);
|
||||
}
|
||||
}
|
||||
|
||||
agentStepRepository.save(step);
|
||||
log.debug("agent_step 已更新: sessionId={}, stepIndex={}, duration={}ms",
|
||||
sessionId, stepIndex, durationMs);
|
||||
}
|
||||
} catch (Exception e) {
|
||||
log.error("更新 agent_step 失败", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 清理 token 上下文
|
||||
TokenUsageHolder.clear();
|
||||
|
||||
return new AgentCommand(previousMessages);
|
||||
}
|
||||
|
||||
/**
|
||||
* 构建模型输入摘要（前 N 条消息的 role + 截断内容）
|
||||
*/
|
||||
private String buildModelInputSummary(List<Message> messages) {
|
||||
StringBuilder sb = new StringBuilder();
|
||||
int maxMessages = Math.min(messages.size(), 5);
|
||||
for (int i = messages.size() - maxMessages; i < messages.size(); i++) {
|
||||
Message msg = messages.get(i);
|
||||
String role = getMessageRole(msg);
|
||||
String content = msg.toString();
|
||||
if (content.length() > 200) {
|
||||
content = content.substring(0, 200) + "...";
|
||||
}
|
||||
sb.append("[").append(role).append("] ").append(content).append("\n");
|
||||
}
|
||||
String result = sb.toString();
|
||||
if (result.length() > 500) {
|
||||
result = result.substring(0, 500) + "...";
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* 构建模型输出摘要
|
||||
*/
|
||||
private String buildModelOutputSummary(AssistantMessage message) {
|
||||
String text = extractTextContent(message);
|
||||
if (text == null) {
|
||||
text = "";
|
||||
}
|
||||
if (text.length() > 500) {
|
||||
text = text.substring(0, 500) + "...";
|
||||
}
|
||||
StringBuilder sb = new StringBuilder();
|
||||
sb.append("{\"text\":\"").append(escapeJson(text)).append("\"");
|
||||
if (message.getToolCalls() != null && !message.getToolCalls().isEmpty()) {
|
||||
sb.append(",\"toolCalls\":[");
|
||||
for (int i = 0; i < message.getToolCalls().size(); i++) {
|
||||
if (i > 0) sb.append(",");
|
||||
sb.append("{\"name\":\"").append(escapeJson(message.getToolCalls().get(i).name()))
|
||||
.append("\",\"arguments\":").append(message.getToolCalls().get(i).arguments()).append("}");
|
||||
}
|
||||
sb.append("]");
|
||||
}
|
||||
sb.append("}");
|
||||
return sb.toString();
|
||||
}
|
||||
|
||||
private String escapeJson(String s) {
|
||||
if (s == null) return "";
|
||||
return s.replace("\\", "\\\\")
|
||||
.replace("\"", "\\\"")
|
||||
.replace("\n", "\\n")
|
||||
.replace("\r", "\\r")
|
||||
.replace("\t", "\\t");
|
||||
}
|
||||
|
||||
/**
|
||||
* 提取 AssistantMessage 的文本内容
|
||||
*/
|
||||
private String extractTextContent(AssistantMessage message) {
|
||||
if (message == null) return null;
|
||||
try {
|
||||
// 方法 1: 尝试通过反射获取 text 字段
|
||||
// 方法 1: 反射获取 text 字段
|
||||
try {
|
||||
java.lang.reflect.Field textField = message.getClass().getDeclaredField("text");
|
||||
textField.setAccessible(true);
|
||||
Object value = textField.get(message);
|
||||
if (value != null) {
|
||||
String text = value.toString();
|
||||
log.debug("通过 text 字段提取成功");
|
||||
return text;
|
||||
return value.toString();
|
||||
}
|
||||
} catch (NoSuchFieldException e) {
|
||||
// text 字段不存在，尝试下一种方法
|
||||
// 尝试下一种方法
|
||||
}
|
||||
|
||||
// 方法 2: 尝试 content 字段
|
||||
// 方法 2: 反射获取 content 字段
|
||||
try {
|
||||
java.lang.reflect.Field contentField = message.getClass().getDeclaredField("content");
|
||||
contentField.setAccessible(true);
|
||||
Object value = contentField.get(message);
|
||||
if (value != null) {
|
||||
String text = value.toString();
|
||||
log.debug("通过 content 字段提取成功");
|
||||
return text;
|
||||
return value.toString();
|
||||
}
|
||||
} catch (NoSuchFieldException e) {
|
||||
// content 字段不存在，尝试下一种方法
|
||||
// 尝试下一种方法
|
||||
}
|
||||
|
||||
// 方法 3: 尝试调用 getText() 方法
|
||||
// 方法 3: 调用 getText() 方法
|
||||
try {
|
||||
java.lang.reflect.Method getTextMethod = message.getClass().getMethod("getText");
|
||||
Object value = getTextMethod.invoke(message);
|
||||
if (value != null) {
|
||||
String text = value.toString();
|
||||
log.debug("通过 getText() 方法提取成功");
|
||||
return text;
|
||||
return value.toString();
|
||||
}
|
||||
} catch (NoSuchMethodException e) {
|
||||
// getText() 方法不存在，尝试下一种方法
|
||||
// 尝试下一种方法
|
||||
}
|
||||
|
||||
// 方法 4: 尝试调用 getContent() 方法
|
||||
// 方法 4: 调用 getContent() 方法
|
||||
try {
|
||||
java.lang.reflect.Method getContentMethod = message.getClass().getMethod("getContent");
|
||||
Object value = getContentMethod.invoke(message);
|
||||
if (value != null) {
|
||||
String text = value.toString();
|
||||
log.debug("通过 getContent() 方法提取成功");
|
||||
return text;
|
||||
return value.toString();
|
||||
}
|
||||
} catch (NoSuchMethodException e) {
|
||||
// getContent() 方法不存在
|
||||
// 方法不存在
|
||||
}
|
||||
|
||||
// 方法 5: 打印所有字段和方法，帮助调试
|
||||
// 方法 5: 打印类结构信息
|
||||
log.warn("无法提取 AssistantMessage 文本内容，打印类信息:");
|
||||
log.warn("类名: {}", message.getClass().getName());
|
||||
log.warn("字段列表:");
|
||||
for (java.lang.reflect.Field field : message.getClass().getDeclaredFields()) {
|
||||
log.warn(" - {}: {}", field.getName(), field.getType().getSimpleName());
|
||||
}
|
||||
log.warn("方法列表:");
|
||||
for (java.lang.reflect.Method method : message.getClass().getMethods()) {
|
||||
if (method.getName().startsWith("get") && method.getParameterCount() == 0) {
|
||||
log.warn(" - {}(): {}", method.getName(), method.getReturnType().getSimpleName());
|
||||
}
|
||||
}
|
||||
|
||||
// 方法 6: 最后尝试 toString()
|
||||
// 方法 6: toString() 兜底
|
||||
String toString = message.toString();
|
||||
if (toString != null && !toString.startsWith("AssistantMessage@")) {
|
||||
log.debug("通过 toString() 提取");
|
||||
|
||||
@@ -0,0 +1,45 @@
|
||||
package com.superbiz.agent.hook;
|
||||
|
||||
import org.springframework.ai.chat.model.ChatModel;
|
||||
import org.springframework.ai.chat.model.ChatResponse;
|
||||
import org.springframework.ai.chat.prompt.Prompt;
|
||||
import reactor.core.publisher.Flux;
|
||||
|
||||
/**
|
||||
* ChatModel 包装器 — 捕获每次模型调用的实际 token 用量
|
||||
* 通过 TokenUsageHolder 传递给 AgentLoggingHook
|
||||
*/
|
||||
public class TokenTrackingChatModel implements ChatModel {
|
||||
|
||||
private final ChatModel delegate;
|
||||
|
||||
public TokenTrackingChatModel(ChatModel delegate) {
|
||||
this.delegate = delegate;
|
||||
}
|
||||
|
||||
@Override
|
||||
public ChatResponse call(Prompt prompt) {
|
||||
ChatResponse response = delegate.call(prompt);
|
||||
captureTokenUsage(response);
|
||||
return response;
|
||||
}
|
||||
|
||||
@Override
|
||||
public Flux<ChatResponse> stream(Prompt prompt) {
|
||||
return delegate.stream(prompt);
|
||||
}
|
||||
|
||||
private void captureTokenUsage(ChatResponse response) {
|
||||
try {
|
||||
if (response.getMetadata() != null && response.getMetadata().getUsage() != null) {
|
||||
var usage = response.getMetadata().getUsage();
|
||||
Integer total = usage.getTotalTokens();
|
||||
if (total != null && total > 0) {
|
||||
TokenUsageHolder.set(total);
|
||||
}
|
||||
}
|
||||
} catch (Exception e) {
|
||||
// 不中断模型调用
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,22 @@
|
||||
package com.superbiz.agent.hook;
|
||||
|
||||
/**
|
||||
* Token 用量持有者（基于 ThreadLocal）
|
||||
* ChatModel 调用后写入实际 token 数，AgentLoggingHook 读取
|
||||
*/
|
||||
public class TokenUsageHolder {
|
||||
|
||||
private static final ThreadLocal<Integer> TOKEN_COUNT = new ThreadLocal<>();
|
||||
|
||||
public static void set(Integer count) {
|
||||
TOKEN_COUNT.set(count);
|
||||
}
|
||||
|
||||
public static Integer get() {
|
||||
return TOKEN_COUNT.get();
|
||||
}
|
||||
|
||||
public static void clear() {
|
||||
TOKEN_COUNT.remove();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,24 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.entity.AgentStep;
|
||||
import org.springframework.data.jpa.repository.JpaRepository;
|
||||
import org.springframework.stereotype.Repository;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* Agent 决策步骤 Repository
|
||||
*/
|
||||
@Repository
|
||||
public interface AgentStepRepository extends JpaRepository<AgentStep, Long> {
|
||||
|
||||
/**
|
||||
* 根据会话ID查询所有步骤（按步骤号排序）
|
||||
*/
|
||||
List<AgentStep> findBySessionIdOrderByStepIndex(String sessionId);
|
||||
|
||||
/**
|
||||
* 统计某个会话的步骤数
|
||||
*/
|
||||
int countBySessionId(String sessionId);
|
||||
}
|
||||
@@ -1,73 +0,0 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.enums.DiagnosisStatus;
|
||||
import com.superbiz.agent.domain.enums.FaultCategory;
|
||||
import com.superbiz.agent.domain.entity.DiagnosisRecord;
|
||||
import org.springframework.data.domain.Page;
|
||||
import org.springframework.data.domain.Pageable;
|
||||
import org.springframework.data.jpa.repository.JpaRepository;
|
||||
import org.springframework.stereotype.Repository;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
import java.util.List;
|
||||
import java.util.Optional;
|
||||
|
||||
/**
|
||||
* 诊断记录 Repository
|
||||
*/
|
||||
@Repository
|
||||
public interface DiagnosisRecordRepository extends JpaRepository<DiagnosisRecord, Long> {
|
||||
|
||||
/**
|
||||
* 根据诊断ID查询
|
||||
*/
|
||||
Optional<DiagnosisRecord> findByDiagnosisId(String diagnosisId);
|
||||
|
||||
/**
|
||||
* 根据业务ID查询
|
||||
*/
|
||||
Optional<DiagnosisRecord> findByBusinessId(String businessId);
|
||||
|
||||
/**
|
||||
* 根据链路追踪ID查询
|
||||
*/
|
||||
Optional<DiagnosisRecord> findByTraceId(String traceId);
|
||||
|
||||
/**
|
||||
* 根据会话ID查询所有记录
|
||||
*/
|
||||
List<DiagnosisRecord> findBySessionId(String sessionId);
|
||||
|
||||
/**
|
||||
* 根据故障类别和错误码查询
|
||||
*/
|
||||
List<DiagnosisRecord> findByFaultCategoryAndErrorCode(FaultCategory category, String errorCode);
|
||||
|
||||
/**
|
||||
* 根据故障类别、故障源和错误码查询
|
||||
*/
|
||||
List<DiagnosisRecord> findByFaultCategoryAndFaultSourceAndErrorCode(
|
||||
FaultCategory category, String faultSource, String errorCode);
|
||||
|
||||
/**
|
||||
* 根据状态查询
|
||||
*/
|
||||
List<DiagnosisRecord> findByStatus(DiagnosisStatus status);
|
||||
|
||||
/**
|
||||
* 根据时间范围查询（分页）
|
||||
*/
|
||||
Page<DiagnosisRecord> findByCreatedAtBetween(
|
||||
LocalDateTime start, LocalDateTime end, Pageable pageable);
|
||||
|
||||
/**
|
||||
* 根据故障类别和时间范围查询（分页）
|
||||
*/
|
||||
Page<DiagnosisRecord> findByFaultCategoryAndCreatedAtBetween(
|
||||
FaultCategory category, LocalDateTime start, LocalDateTime end, Pageable pageable);
|
||||
|
||||
/**
|
||||
* 查询有用反馈的高置信度记录（用于生成案例）
|
||||
*/
|
||||
List<DiagnosisRecord> findByFeedbackAndConfidenceGreaterThanEqual(String feedback, Integer confidence);
|
||||
}
|
||||
@@ -0,0 +1,12 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.entity.DiagnosisSession;
|
||||
import org.springframework.data.jpa.repository.JpaRepository;
|
||||
import org.springframework.stereotype.Repository;
|
||||
|
||||
import java.util.Optional;
|
||||
|
||||
@Repository
|
||||
public interface DiagnosisSessionRepository extends JpaRepository<DiagnosisSession, Long> {
|
||||
Optional<DiagnosisSession> findBySessionId(String sessionId);
|
||||
}
|
||||
@@ -0,0 +1,29 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.entity.ToolInvocation;
|
||||
import org.springframework.data.jpa.repository.JpaRepository;
|
||||
import org.springframework.stereotype.Repository;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 工具调用明细 Repository
|
||||
*/
|
||||
@Repository
|
||||
public interface ToolInvocationRepository extends JpaRepository<ToolInvocation, Long> {
|
||||
|
||||
/**
|
||||
* 根据会话ID查询所有工具调用
|
||||
*/
|
||||
List<ToolInvocation> findBySessionId(String sessionId);
|
||||
|
||||
/**
|
||||
* 根据工具名查询所有调用
|
||||
*/
|
||||
List<ToolInvocation> findByToolName(String toolName);
|
||||
|
||||
/**
|
||||
* 根据会话ID和工具名查询
|
||||
*/
|
||||
List<ToolInvocation> findBySessionIdAndToolName(String sessionId, String toolName);
|
||||
}
|
||||
@@ -9,6 +9,13 @@ import com.superbiz.agent.agent.tool.DateTimeTools;
|
||||
import com.superbiz.agent.agent.tool.InternalDocsTools;
|
||||
import com.superbiz.agent.agent.tool.QueryLogsTools;
|
||||
import com.superbiz.agent.agent.tool.QueryMetricsTools;
|
||||
import com.superbiz.agent.domain.entity.AgentStep;
|
||||
import com.superbiz.agent.domain.entity.AgentStep;
|
||||
import com.superbiz.agent.domain.entity.DiagnosisSession;
|
||||
import com.superbiz.agent.hook.AgentLoggingHook;
|
||||
import com.superbiz.agent.repository.AgentStepRepository;
|
||||
import com.superbiz.agent.repository.DiagnosisSessionRepository;
|
||||
import com.superbiz.agent.util.SessionContextHolder;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.springframework.ai.chat.messages.AssistantMessage;
|
||||
@@ -20,6 +27,7 @@ import com.superbiz.agent.tool.LookupKnowledgeTool;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Optional;
|
||||
import java.util.UUID;
|
||||
|
||||
/**
|
||||
* AI Ops 智能运维服务
|
||||
@@ -48,6 +56,12 @@ public class AiOpsService {
|
||||
@Autowired
|
||||
private AiOpsPromptProperties promptProperties;
|
||||
|
||||
@Autowired
|
||||
private DiagnosisSessionRepository diagnosisSessionRepository;
|
||||
|
||||
@Autowired
|
||||
private AgentStepRepository agentStepRepository;
|
||||
|
||||
/**
|
||||
* 执行 AI Ops 告警分析流程
|
||||
*
|
||||
@@ -59,11 +73,27 @@ public class AiOpsService {
|
||||
public Optional<OverAllState> executeAiOpsAnalysis(ChatModel chatModel, ToolCallback[] toolCallbacks) throws GraphRunnerException {
|
||||
logger.info("开始执行 AI Ops 多 Agent 协作流程");
|
||||
|
||||
// 构建 Planner 和 Executor Agent
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
long startTime = System.currentTimeMillis();
|
||||
|
||||
// 创建诊断会话
|
||||
DiagnosisSession session = DiagnosisSession.builder()
|
||||
.sessionId(sessionId)
|
||||
.query("AI Ops 告警分析")
|
||||
.status("RUNNING")
|
||||
.agentFlow("AI_OPS")
|
||||
.build();
|
||||
diagnosisSessionRepository.save(session);
|
||||
|
||||
// 设置 ThreadLocal 上下文（LookupKnowledgeTool 通过此获取 sessionId）
|
||||
SessionContextHolder.setSessionId(sessionId);
|
||||
|
||||
try {
|
||||
// 构建 Planner 和 Executor Agent（每个 Agent 各自带 Hook）
|
||||
ReactAgent plannerAgent = buildPlannerAgent(chatModel, toolCallbacks);
|
||||
ReactAgent executorAgent = buildExecutorAgent(chatModel, toolCallbacks);
|
||||
|
||||
// 构建 Supervisor Agent
|
||||
// 构建 Supervisor Agent（不加 Hook）
|
||||
SupervisorAgent supervisorAgent = SupervisorAgent.builder()
|
||||
.name("ai_ops_supervisor")
|
||||
.description("负责调度 Planner 与 Executor 的多 Agent 控制器")
|
||||
@@ -78,15 +108,30 @@ public class AiOpsService {
|
||||
|
||||
Optional<OverAllState> stateOptional = supervisorAgent.invoke(taskPrompt);
|
||||
|
||||
long duration = System.currentTimeMillis() - startTime;
|
||||
|
||||
// 更新诊断会话
|
||||
session.setStatus(stateOptional.isPresent() ? "SUCCESS" : "FAILED");
|
||||
session.setTotalDurationMs((int) duration);
|
||||
backfillSessionMetrics(session);
|
||||
diagnosisSessionRepository.save(session);
|
||||
|
||||
// 添加调试代码
|
||||
if (stateOptional.isPresent()) {
|
||||
OverAllState state = stateOptional.get();
|
||||
logger.debug("Final State Keys: {}", state.data().keySet()); // 打印所有 key
|
||||
logger.debug("Final State Keys: {}", state.data().keySet());
|
||||
logger.debug("Planner Plan: {}", state.value("planner_plan"));
|
||||
logger.debug("Executor Feedback: {}", state.value("executor_feedback"));
|
||||
}
|
||||
|
||||
return stateOptional;
|
||||
} catch (Exception e) {
|
||||
session.setStatus("FAILED");
|
||||
diagnosisSessionRepository.save(session);
|
||||
throw e;
|
||||
} finally {
|
||||
SessionContextHolder.clear();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -124,6 +169,7 @@ public class AiOpsService {
|
||||
.systemPrompt(promptProperties.getPlanner())
|
||||
.methodTools(buildMethodToolsArray())
|
||||
.tools(toolCallbacks)
|
||||
.hooks(new AgentLoggingHook(agentStepRepository, "planner"))
|
||||
.outputKey("planner_plan")
|
||||
.build();
|
||||
}
|
||||
@@ -139,6 +185,7 @@ public class AiOpsService {
|
||||
.systemPrompt(promptProperties.getExecutor())
|
||||
.methodTools(buildMethodToolsArray())
|
||||
.tools(toolCallbacks)
|
||||
.hooks(new AgentLoggingHook(agentStepRepository, "executor"))
|
||||
.outputKey("executor_feedback")
|
||||
.build();
|
||||
}
|
||||
@@ -157,4 +204,26 @@ public class AiOpsService {
|
||||
return new Object[]{dateTimeTools, lookupKnowledgeTool, queryMetricsTools};
|
||||
}
|
||||
}
|
||||
|
||||
/** 从 agent_step 汇总指标回填 diagnosis_session */
|
||||
private void backfillSessionMetrics(DiagnosisSession session) {
|
||||
try {
|
||||
List<AgentStep> steps = agentStepRepository.findBySessionIdOrderByStepIndex(session.getSessionId());
|
||||
if (steps.isEmpty()) return;
|
||||
|
||||
int totalTokens = 0;
|
||||
int stepCount = 0;
|
||||
int toolCallCount = 0;
|
||||
for (AgentStep s : steps) {
|
||||
stepCount++;
|
||||
if (s.getTokenCount() != null) totalTokens += s.getTokenCount();
|
||||
if (Boolean.TRUE.equals(s.getHasToolCall())) toolCallCount++;
|
||||
}
|
||||
session.setTotalTokenCount(totalTokens);
|
||||
session.setStepCount(stepCount);
|
||||
session.setToolCallCount(toolCallCount);
|
||||
} catch (Exception e) {
|
||||
logger.warn("回填会话指标失败: sessionId={}", session.getSessionId(), e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,24 +1,40 @@
|
||||
package com.superbiz.agent.service;
|
||||
|
||||
import com.alibaba.cloud.ai.graph.OverAllState;
|
||||
import com.alibaba.cloud.ai.graph.agent.ReactAgent;
|
||||
import com.alibaba.cloud.ai.graph.agent.flow.agent.SupervisorAgent;
|
||||
import com.alibaba.cloud.ai.graph.exception.GraphRunnerException;
|
||||
import com.superbiz.agent.agent.tool.DateTimeTools;
|
||||
import com.superbiz.agent.agent.tool.InternalDocsTools;
|
||||
import com.superbiz.agent.agent.tool.QueryLogsTools;
|
||||
import com.superbiz.agent.agent.tool.QueryMetricsTools;
|
||||
import com.superbiz.agent.tool.LookupKnowledgeTool;
|
||||
import com.superbiz.agent.domain.entity.DiagnosisSession;
|
||||
import com.superbiz.agent.hook.AgentLoggingHook;
|
||||
import com.superbiz.agent.hook.TokenTrackingChatModel;
|
||||
import com.superbiz.agent.hook.TokenUsageHolder;
|
||||
import com.superbiz.agent.repository.AgentStepRepository;
|
||||
import com.superbiz.agent.repository.DiagnosisSessionRepository;
|
||||
import com.superbiz.agent.tool.LookupKnowledgeTool;
|
||||
import com.superbiz.agent.util.QuestionComplexity;
|
||||
import com.superbiz.agent.util.SessionContextHolder;
|
||||
|
||||
import jakarta.annotation.PostConstruct;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.springframework.ai.chat.messages.AssistantMessage;
|
||||
import org.springframework.ai.chat.model.ChatModel;
|
||||
import org.springframework.ai.tool.ToolCallback;
|
||||
import org.springframework.ai.tool.ToolCallbackProvider;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.core.io.ClassPathResource;
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.nio.charset.StandardCharsets;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.Optional;
|
||||
import java.util.UUID;
|
||||
|
||||
/**
|
||||
* 聊天服务
|
||||
@@ -50,6 +66,37 @@ public class ChatService {
|
||||
@Autowired
|
||||
private LookupKnowledgeTool lookupKnowledgeTool;
|
||||
|
||||
@Autowired
|
||||
private DiagnosisSessionRepository diagnosisSessionRepository;
|
||||
|
||||
@Autowired
|
||||
private AgentStepRepository agentStepRepository;
|
||||
|
||||
/** 多 Agent Chat 的 Prompt */
|
||||
private String chatPlannerPrompt;
|
||||
private String chatExecutorPrompt;
|
||||
|
||||
@PostConstruct
|
||||
public void init() {
|
||||
// 加载 Prompt
|
||||
try {
|
||||
chatPlannerPrompt = new String(
|
||||
new ClassPathResource("prompts/chat-planner-prompt.md").getInputStream().readAllBytes(),
|
||||
StandardCharsets.UTF_8);
|
||||
chatExecutorPrompt = new String(
|
||||
new ClassPathResource("prompts/chat-executor-prompt.md").getInputStream().readAllBytes(),
|
||||
StandardCharsets.UTF_8);
|
||||
logger.info("Chat 多 Agent Prompts 加载成功");
|
||||
} catch (IOException e) {
|
||||
logger.error("加载 Chat Prompt 文件失败", e);
|
||||
throw new RuntimeException("Failed to load chat prompts", e);
|
||||
}
|
||||
|
||||
// 包装 ChatModel 以捕获 token 用量
|
||||
chatModel = new TokenTrackingChatModel(chatModel);
|
||||
logger.info("ChatModel 已包装 TokenTrackingChatModel");
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取注入的 ChatModel
|
||||
*/
|
||||
@@ -177,7 +224,7 @@ public class ChatService {
|
||||
.systemPrompt(systemPrompt)
|
||||
.methodTools(buildMethodToolsArray())
|
||||
.tools(getToolCallbacks())
|
||||
.hooks(new AgentLoggingHook()) // 添加日志 Hook
|
||||
.hooks(new AgentLoggingHook(agentStepRepository, "intelligent_assistant"))
|
||||
.build();
|
||||
}
|
||||
|
||||
@@ -191,16 +238,201 @@ public class ChatService {
|
||||
logger.info("========================================");
|
||||
logger.info("📝 用户问题: {}", question);
|
||||
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
long startTime = System.currentTimeMillis();
|
||||
|
||||
// 创建诊断会话
|
||||
DiagnosisSession session = DiagnosisSession.builder()
|
||||
.sessionId(sessionId)
|
||||
.query(question)
|
||||
.status("RUNNING")
|
||||
.agentFlow("CHAT")
|
||||
.build();
|
||||
diagnosisSessionRepository.save(session);
|
||||
|
||||
// 设置 ThreadLocal 上下文（LookupKnowledgeTool 通过此获取 sessionId）
|
||||
SessionContextHolder.setSessionId(sessionId);
|
||||
|
||||
try {
|
||||
var response = agent.call(question);
|
||||
long duration = System.currentTimeMillis() - startTime;
|
||||
|
||||
String answer = response.getText();
|
||||
|
||||
// 更新诊断会话
|
||||
session.setStatus("SUCCESS");
|
||||
session.setTotalDurationMs((int) duration);
|
||||
backfillSessionMetrics(session);
|
||||
diagnosisSessionRepository.save(session);
|
||||
|
||||
logger.info("⏱️ 总耗时: {} ms", duration);
|
||||
logger.info("📏 输出长度: {} 字符", answer.length());
|
||||
logger.info("========================================");
|
||||
|
||||
return answer;
|
||||
} catch (Exception e) {
|
||||
session.setStatus("FAILED");
|
||||
diagnosisSessionRepository.save(session);
|
||||
throw e;
|
||||
} finally {
|
||||
SessionContextHolder.clear();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 根据问题复杂度自动选择执行策略
|
||||
* @param chatModel 聊天模型
|
||||
* @param toolCallbacks 工具回调
|
||||
* @param question 用户问题
|
||||
* @param history 历史消息
|
||||
* @return AI 回复
|
||||
*/
|
||||
public String executeChatWithStrategy(ChatModel chatModel, ToolCallback[] toolCallbacks,
|
||||
String question, List<Map<String, String>> history) throws GraphRunnerException {
|
||||
if (QuestionComplexity.isComplex(question)) {
|
||||
logger.info("📊 问题判定为复杂，使用多 Agent（Planner + Executor）执行");
|
||||
return executeChatComplex(chatModel, toolCallbacks, question, history);
|
||||
} else {
|
||||
logger.info("📊 问题判定为简单，使用单 Agent 执行");
|
||||
String systemPrompt = buildSystemPrompt(history);
|
||||
ReactAgent agent = createReactAgent(chatModel, systemPrompt);
|
||||
return executeChat(agent, question);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 多 Agent 复杂对话执行（Planner + Executor + Supervisor）
|
||||
*/
|
||||
public String executeChatComplex(ChatModel chatModel, ToolCallback[] toolCallbacks,
|
||||
String question, List<Map<String, String>> history) throws GraphRunnerException {
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
long startTime = System.currentTimeMillis();
|
||||
|
||||
DiagnosisSession session = DiagnosisSession.builder()
|
||||
.sessionId(sessionId)
|
||||
.query(question)
|
||||
.status("RUNNING")
|
||||
.agentFlow("CHAT")
|
||||
.build();
|
||||
diagnosisSessionRepository.save(session);
|
||||
|
||||
SessionContextHolder.setSessionId(sessionId);
|
||||
|
||||
try {
|
||||
ReactAgent planner = buildChatPlannerAgent(chatModel, toolCallbacks, history);
|
||||
ReactAgent executor = buildChatExecutorAgent(chatModel, toolCallbacks, history);
|
||||
|
||||
SupervisorAgent supervisor = SupervisorAgent.builder()
|
||||
.name("chat_supervisor")
|
||||
.description("负责调度 Planner 与 Executor 的多 Agent 控制器")
|
||||
.model(chatModel)
|
||||
.systemPrompt("你是一个智能任务调度器。分析用户问题，调用 Planner 拆解步骤，调用 Executor 执行各步骤。")
|
||||
.subAgents(List.of(planner, executor))
|
||||
.build();
|
||||
|
||||
Optional<OverAllState> stateOptional = supervisor.invoke(question);
|
||||
long duration = System.currentTimeMillis() - startTime;
|
||||
|
||||
String answer = null;
|
||||
if (stateOptional.isPresent()) {
|
||||
// 从 state 中提取 Executor 的最终输出
|
||||
OverAllState state = stateOptional.get();
|
||||
Optional<AssistantMessage> executorOutput = state.value("executor_feedback")
|
||||
.filter(AssistantMessage.class::isInstance)
|
||||
.map(AssistantMessage.class::cast);
|
||||
if (executorOutput.isPresent()) {
|
||||
answer = executorOutput.get().getText();
|
||||
}
|
||||
}
|
||||
|
||||
if (answer == null || answer.isBlank()) {
|
||||
answer = "抱歉，多 Agent 分析未能生成有效结论。";
|
||||
}
|
||||
|
||||
session.setStatus("SUCCESS");
|
||||
session.setTotalDurationMs((int) duration);
|
||||
backfillSessionMetrics(session);
|
||||
diagnosisSessionRepository.save(session);
|
||||
|
||||
logger.info("⏱️ 多 Agent 总耗时: {} ms", duration);
|
||||
logger.info("📏 输出长度: {} 字符", answer.length());
|
||||
|
||||
return answer;
|
||||
|
||||
} catch (Exception e) {
|
||||
session.setStatus("FAILED");
|
||||
diagnosisSessionRepository.save(session);
|
||||
logger.error("多 Agent 执行失败", e);
|
||||
return "执行失败: " + e.getMessage();
|
||||
} finally {
|
||||
SessionContextHolder.clear();
|
||||
}
|
||||
}
|
||||
|
||||
private ReactAgent buildChatPlannerAgent(ChatModel chatModel, ToolCallback[] toolCallbacks,
|
||||
List<Map<String, String>> history) {
|
||||
StringBuilder prompt = new StringBuilder(chatPlannerPrompt);
|
||||
if (!history.isEmpty()) {
|
||||
prompt.append("\n\n--- 对话历史 ---\n");
|
||||
for (Map<String, String> msg : history) {
|
||||
prompt.append(msg.get("role")).append(": ").append(msg.get("content")).append("\n");
|
||||
}
|
||||
prompt.append("--- 对话历史结束 ---\n");
|
||||
}
|
||||
return ReactAgent.builder()
|
||||
.name("chat_planner")
|
||||
.description("负责拆解问题、规划步骤")
|
||||
.model(chatModel)
|
||||
.systemPrompt(prompt.toString())
|
||||
// Planner 不注入工具，只能规划不能执行
|
||||
.hooks(new AgentLoggingHook(agentStepRepository, "planner"))
|
||||
.outputKey("planner_plan")
|
||||
.build();
|
||||
}
|
||||
|
||||
private ReactAgent buildChatExecutorAgent(ChatModel chatModel, ToolCallback[] toolCallbacks,
|
||||
List<Map<String, String>> history) {
|
||||
StringBuilder prompt = new StringBuilder(chatExecutorPrompt);
|
||||
if (!history.isEmpty()) {
|
||||
prompt.append("\n\n--- 对话历史 ---\n");
|
||||
for (Map<String, String> msg : history) {
|
||||
prompt.append(msg.get("role")).append(": ").append(msg.get("content")).append("\n");
|
||||
}
|
||||
prompt.append("--- 对话历史结束 ---\n");
|
||||
}
|
||||
return ReactAgent.builder()
|
||||
.name("chat_executor")
|
||||
.description("负责执行具体步骤并及时反馈")
|
||||
.model(chatModel)
|
||||
.systemPrompt(prompt.toString())
|
||||
.methodTools(buildMethodToolsArray())
|
||||
.tools(toolCallbacks)
|
||||
.hooks(new AgentLoggingHook(agentStepRepository, "executor"))
|
||||
.outputKey("executor_feedback")
|
||||
.build();
|
||||
}
|
||||
|
||||
/** 从 agent_step 汇总 token、步数等指标回填 diagnosis_session */
|
||||
private void backfillSessionMetrics(DiagnosisSession session) {
|
||||
try {
|
||||
List<com.superbiz.agent.domain.entity.AgentStep> steps =
|
||||
agentStepRepository.findBySessionIdOrderByStepIndex(session.getSessionId());
|
||||
|
||||
if (steps.isEmpty()) return;
|
||||
|
||||
int totalTokens = 0;
|
||||
int stepCount = 0;
|
||||
int toolCallCount = 0;
|
||||
for (var s : steps) {
|
||||
stepCount++;
|
||||
if (s.getTokenCount() != null) totalTokens += s.getTokenCount();
|
||||
if (Boolean.TRUE.equals(s.getHasToolCall())) toolCallCount++;
|
||||
}
|
||||
session.setTotalTokenCount(totalTokens);
|
||||
session.setStepCount(stepCount);
|
||||
session.setToolCallCount(toolCallCount);
|
||||
} catch (Exception e) {
|
||||
logger.warn("回填会话指标失败: sessionId={}", session.getSessionId(), e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,8 +1,11 @@
|
||||
package com.superbiz.agent.tool;
|
||||
|
||||
import com.superbiz.agent.domain.entity.ToolInvocation;
|
||||
import com.superbiz.agent.dto.*;
|
||||
import com.superbiz.agent.repository.ToolInvocationRepository;
|
||||
import com.superbiz.agent.service.KnowledgeIndexService;
|
||||
import com.superbiz.agent.service.VectorSearchService;
|
||||
import com.superbiz.agent.util.SessionContextHolder;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.ai.tool.annotation.Tool;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
@@ -25,6 +28,9 @@ public class LookupKnowledgeTool {
|
||||
@Autowired
|
||||
private VectorSearchService vectorSearchService;
|
||||
|
||||
@Autowired
|
||||
private ToolInvocationRepository toolInvocationRepository;
|
||||
|
||||
/**
|
||||
* 查询知识库文档
|
||||
*
|
||||
@@ -134,9 +140,120 @@ public class LookupKnowledgeTool {
|
||||
|
||||
log.info("========================================");
|
||||
|
||||
// 记录 tool_invocation（持久化检索明细）
|
||||
saveToolInvocation(query, l0Matches, l1Results, highConfidence, startTime, result);
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* 保存工具调用明细到 tool_invocation 表
|
||||
*/
|
||||
private void saveToolInvocation(String query, List<KnowledgeEntry> l0Matches,
|
||||
List<VectorSearchService.SearchResult> l1Results,
|
||||
boolean highConfidence, long startTime, LookupResult result) {
|
||||
try {
|
||||
String sessionId = SessionContextHolder.getSessionId();
|
||||
if (sessionId == null) return; // 非会话上下文不记录
|
||||
|
||||
boolean hasL0 = l0Matches != null && !l0Matches.isEmpty();
|
||||
boolean hasL1 = l1Results != null && !l1Results.isEmpty();
|
||||
long duration = System.currentTimeMillis() - startTime;
|
||||
|
||||
String layer;
|
||||
String outputPreview = null;
|
||||
int outputLength = 0;
|
||||
int l0Count = 0;
|
||||
int l1Count = 0;
|
||||
boolean truncated = false;
|
||||
|
||||
if (hasL0 && !highConfidence) {
|
||||
layer = "L0+L1";
|
||||
l0Count = l0Matches.size();
|
||||
l1Count = l1Results.size();
|
||||
} else if (hasL0) {
|
||||
layer = "L0";
|
||||
l0Count = l0Matches.size();
|
||||
} else if (hasL1) {
|
||||
layer = "L1";
|
||||
l1Count = l1Results.size();
|
||||
} else {
|
||||
layer = null;
|
||||
}
|
||||
|
||||
// 拼接 output_preview（前500字符）
|
||||
if (result != null && result.getPrimary() != null && result.getPrimary().getContent() != null) {
|
||||
String content = result.getPrimary().getContent();
|
||||
outputLength = content.length();
|
||||
if (content.length() > 500) {
|
||||
outputPreview = content.substring(0, 500) + "...";
|
||||
truncated = true;
|
||||
} else {
|
||||
outputPreview = content;
|
||||
}
|
||||
} else if (l1Results != null && !l1Results.isEmpty() && l1Results.get(0).getContent() != null) {
|
||||
String content = l1Results.get(0).getContent();
|
||||
outputLength = content.length();
|
||||
if (content.length() > 500) {
|
||||
outputPreview = content.substring(0, 500) + "...";
|
||||
truncated = true;
|
||||
} else {
|
||||
outputPreview = content;
|
||||
}
|
||||
}
|
||||
|
||||
// 构建检索明细 JSON
|
||||
StringBuilder details = new StringBuilder("{");
|
||||
if (hasL0) {
|
||||
details.append("\"l0_titles\":[");
|
||||
for (int i = 0; i < Math.min(3, l0Matches.size()); i++) {
|
||||
if (i > 0) details.append(",");
|
||||
details.append("\"").append(escapeJson(l0Matches.get(i).getTitle())).append("\"");
|
||||
}
|
||||
details.append("]");
|
||||
}
|
||||
if (hasL1) {
|
||||
if (hasL0) details.append(",");
|
||||
details.append("\"l1_scores\":[");
|
||||
for (int i = 0; i < Math.min(3, l1Results.size()); i++) {
|
||||
if (i > 0) details.append(",");
|
||||
details.append(l1Results.get(i).getScore());
|
||||
}
|
||||
details.append("]");
|
||||
}
|
||||
details.append("}");
|
||||
|
||||
ToolInvocation inv = ToolInvocation.builder()
|
||||
.sessionId(sessionId)
|
||||
.toolName("lookup_knowledge")
|
||||
.inputParams("{\"query\":\"" + escapeJson(query) + "\"}")
|
||||
.outputPreview(outputPreview)
|
||||
.outputLength(outputLength)
|
||||
.retrievalLayer(layer)
|
||||
.l0MatchCount(hasL0 ? l0Count : null)
|
||||
.l1MatchCount(hasL1 ? l1Count : null)
|
||||
.isTruncated(truncated)
|
||||
.retrievalDetails(details.toString())
|
||||
.durationMs((int) duration)
|
||||
.success(true)
|
||||
.build();
|
||||
|
||||
toolInvocationRepository.save(inv);
|
||||
log.debug("tool_invocation 已保存: sessionId={}, layer={}, duration={}ms", sessionId, layer, duration);
|
||||
} catch (Exception e) {
|
||||
log.error("保存 tool_invocation 失败", e);
|
||||
}
|
||||
}
|
||||
|
||||
private String escapeJson(String s) {
|
||||
if (s == null) return "";
|
||||
return s.replace("\\", "\\\\")
|
||||
.replace("\"", "\\\"")
|
||||
.replace("\n", "\\n")
|
||||
.replace("\r", "\\r")
|
||||
.replace("\t", "\\t");
|
||||
}
|
||||
|
||||
/**
|
||||
* 组装查询结果
|
||||
*
|
||||
|
||||
@@ -0,0 +1,44 @@
|
||||
package com.superbiz.agent.util;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 问题复杂度判断
|
||||
* 用于决定使用单 Agent 还是多 Agent（Planner + Executor）处理
|
||||
*/
|
||||
public class QuestionComplexity {
|
||||
|
||||
/** 复杂问题关键词 — 需要多步分析、排查、根因定位 */
|
||||
private static final List<String> COMPLEX_KEYWORDS = List.of(
|
||||
"排查", "分析", "为什么", "根因", "调查", "对比", "影响范围",
|
||||
"原因", "故障", "告警", "诊断", "链路", "流程", "步骤",
|
||||
"root cause", "troubleshoot", "investigate"
|
||||
);
|
||||
|
||||
/** 极简问题关键词 — 快速回答，无需多 Agent */
|
||||
private static final List<String> SIMPLE_KEYWORDS = List.of(
|
||||
"是什么", "查一下", "什么是", "时间", "天气", "定义",
|
||||
"查", "找", "what is", "define", "time"
|
||||
);
|
||||
|
||||
/**
|
||||
* 判断是否为复杂问题
|
||||
*/
|
||||
public static boolean isComplex(String question) {
|
||||
if (question == null || question.isBlank()) return false;
|
||||
String q = question.toLowerCase();
|
||||
|
||||
// 复杂关键词匹配 → 多 Agent
|
||||
for (String kw : COMPLEX_KEYWORDS) {
|
||||
if (q.contains(kw)) return true;
|
||||
}
|
||||
|
||||
// 简单关键词匹配 → 单 Agent
|
||||
for (String kw : SIMPLE_KEYWORDS) {
|
||||
if (q.contains(kw)) return false;
|
||||
}
|
||||
|
||||
// 默认：长问题（>30 字）视为复杂，短问题视为简单
|
||||
return question.length() > 30;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,39 @@
|
||||
package com.superbiz.agent.util;
|
||||
|
||||
/**
|
||||
* 会话上下文持有者（基于 ThreadLocal）
|
||||
* <p>
|
||||
* 用于在执行链路中传递 sessionId 和 agentName，覆盖 AgentLoggingHook 和
|
||||
* LookupKnowledgeTool 等无法直接通过 RunnableConfig 获取上下文的组件。
|
||||
* <p>
|
||||
* 使用规范：
|
||||
* 1. 调用方（ChatService/AiOpsService）在 Agent 执行前调用 setSessionId() 和 setAgentName()
|
||||
* 2. AgentLoggingHook 和工具类通过 getSessionId() / getAgentName() 读取
|
||||
* 3. 必须在 finally 块中调用 clear()，防止内存泄漏和线程污染
|
||||
*/
|
||||
public class SessionContextHolder {
|
||||
|
||||
private static final ThreadLocal<String> SESSION_ID = new ThreadLocal<>();
|
||||
private static final ThreadLocal<String> AGENT_NAME = new ThreadLocal<>();
|
||||
|
||||
public static void setSessionId(String sessionId) {
|
||||
SESSION_ID.set(sessionId);
|
||||
}
|
||||
|
||||
public static String getSessionId() {
|
||||
return SESSION_ID.get();
|
||||
}
|
||||
|
||||
public static void setAgentName(String agentName) {
|
||||
AGENT_NAME.set(agentName);
|
||||
}
|
||||
|
||||
public static String getAgentName() {
|
||||
return AGENT_NAME.get();
|
||||
}
|
||||
|
||||
public static void clear() {
|
||||
SESSION_ID.remove();
|
||||
AGENT_NAME.remove();
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,75 @@
|
||||
-- V005: 创建会话存储体系（diagnosis_session + agent_step + tool_invocation）
|
||||
-- 设计文档：openspec/changes/session-storage/design.md
|
||||
|
||||
CREATE TABLE diagnosis_session (
|
||||
id BIGINT PRIMARY KEY AUTO_INCREMENT,
|
||||
session_id VARCHAR(64) UNIQUE NOT NULL COMMENT '会话唯一 ID',
|
||||
|
||||
query TEXT NOT NULL COMMENT '用户原始问题',
|
||||
status VARCHAR(16) DEFAULT 'PENDING' COMMENT 'PENDING/RUNNING/SUCCESS/FAILED',
|
||||
agent_flow VARCHAR(32) COMMENT 'CHAT / AI_OPS',
|
||||
|
||||
total_duration_ms INT COMMENT '总耗时（毫秒）',
|
||||
total_token_count INT COMMENT '总 Token 消耗',
|
||||
step_count INT COMMENT 'Agent 步数',
|
||||
tool_call_count INT COMMENT '工具调用次数',
|
||||
|
||||
self_evaluation JSON COMMENT '自评估信号：{"confidence":0-100,"reasoning":"..."}',
|
||||
feedback VARCHAR(16) COMMENT '用户反馈：useful/not_useful/null',
|
||||
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
|
||||
|
||||
INDEX idx_created_at (created_at),
|
||||
INDEX idx_status (status),
|
||||
INDEX idx_agent_flow (agent_flow)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='诊断会话表';
|
||||
|
||||
CREATE TABLE agent_step (
|
||||
id BIGINT PRIMARY KEY AUTO_INCREMENT,
|
||||
session_id VARCHAR(64) NOT NULL COMMENT '关联 diagnosis_session',
|
||||
|
||||
step_index INT NOT NULL COMMENT '当前 Agent 的第几步（从0开始）',
|
||||
agent_name VARCHAR(32) NOT NULL COMMENT 'intelligent_assistant/planner/executor',
|
||||
|
||||
model_input JSON COMMENT '模型输入摘要',
|
||||
model_output JSON COMMENT '模型输出摘要（含工具调用决策）',
|
||||
thought TEXT COMMENT 'Agent 思考过程',
|
||||
has_tool_call BOOLEAN DEFAULT FALSE COMMENT '本轮是否调用了工具',
|
||||
|
||||
duration_ms INT COMMENT '本轮耗时',
|
||||
token_count INT COMMENT '本轮 Token 消耗',
|
||||
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
|
||||
INDEX idx_session_step (session_id, step_index),
|
||||
INDEX idx_agent_name (agent_name)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='Agent 决策步骤表';
|
||||
|
||||
CREATE TABLE tool_invocation (
|
||||
id BIGINT PRIMARY KEY AUTO_INCREMENT,
|
||||
session_id VARCHAR(64) NOT NULL COMMENT '关联 diagnosis_session',
|
||||
step_id BIGINT COMMENT '关联 agent_step.id（可为空，不强制外键）',
|
||||
|
||||
tool_name VARCHAR(64) NOT NULL COMMENT 'lookup_knowledge/queryPrometheusAlerts/等',
|
||||
|
||||
input_params JSON NOT NULL COMMENT '工具入参',
|
||||
output_preview TEXT COMMENT '输出前500字符',
|
||||
output_length INT COMMENT '输出总字符数',
|
||||
|
||||
retrieval_layer VARCHAR(8) COMMENT 'L0/L1/L0+L1',
|
||||
l0_match_count INT COMMENT 'L0 匹配数',
|
||||
l1_match_count INT COMMENT 'L1 匹配数',
|
||||
is_truncated BOOLEAN DEFAULT FALSE COMMENT '内容是否被截断',
|
||||
retrieval_details JSON COMMENT '检索明细：{l0_titles:[], l1_scores:[]}',
|
||||
|
||||
duration_ms INT COMMENT '工具执行耗时',
|
||||
success BOOLEAN DEFAULT TRUE COMMENT '是否成功',
|
||||
error_message TEXT COMMENT '失败原因',
|
||||
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
|
||||
INDEX idx_session_id (session_id),
|
||||
INDEX idx_tool_name (tool_name),
|
||||
INDEX idx_retrieval_layer (retrieval_layer)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='工具调用明细表';
|
||||
@@ -0,0 +1,6 @@
|
||||
-- V006: 将 agent_step 的 model_input / model_output 从 JSON 改为 TEXT
|
||||
-- 原因：buildModelInputSummary() 输出的是纯文本摘要，不是合法 JSON
|
||||
|
||||
ALTER TABLE agent_step
|
||||
MODIFY COLUMN model_input TEXT COMMENT '模型输入摘要',
|
||||
MODIFY COLUMN model_output TEXT COMMENT '模型输出摘要（含工具调用决策）';
|
||||
@@ -0,0 +1,2 @@
|
||||
-- V007: 删除旧的 diagnosis_record 表（已被 diagnosis_session + agent_step + tool_invocation 替代）
|
||||
DROP TABLE IF EXISTS diagnosis_record;
|
||||
@@ -0,0 +1,12 @@
|
||||
你是任务执行器。执行 Planner 分配给你的具体步骤，并及时反馈结果。
|
||||
|
||||
## 职责
|
||||
- 按步骤执行具体的查询任务
|
||||
- 使用知识库查询、日志查询等工具获取信息
|
||||
- 将执行结果汇总，给出完整的最终答案
|
||||
|
||||
## 规则
|
||||
- 按顺序执行，不可跳过步骤
|
||||
- 所有需要外部信息的地方，都必须调用对应的工具
|
||||
- 不要凭记忆回答，必须基于工具返回的真实数据
|
||||
- 执行完成后，综合所有结果给出完整的答案
|
||||
@@ -0,0 +1,20 @@
|
||||
你是智能任务规划器。分析用户的问题，拆解为具体的执行步骤。
|
||||
|
||||
## 职责
|
||||
- 分析用户问题，拆解为可执行的步骤列表
|
||||
- **你不能调用任何工具**，你的职责是制定计划，不是执行
|
||||
- 输出 JSON 格式的计划，不输出其他内容
|
||||
|
||||
## 输出格式
|
||||
|
||||
```json
|
||||
{
|
||||
"plan": ["步骤1描述", "步骤2描述", "步骤3描述"],
|
||||
"reasoning": "规划思路说明"
|
||||
}
|
||||
```
|
||||
|
||||
## 规则
|
||||
- 每个步骤应该是一个可以独立执行的任务
|
||||
- 步骤要具体可操作，不要模糊
|
||||
- 如果问题需要查知识库，明确在步骤中说明要查什么
|
||||
@@ -0,0 +1,61 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.entity.AgentStep;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.boot.test.autoconfigure.jdbc.AutoConfigureTestDatabase;
|
||||
import org.springframework.boot.test.autoconfigure.orm.jpa.DataJpaTest;
|
||||
import org.springframework.test.context.TestPropertySource;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.UUID;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.*;
|
||||
|
||||
/**
|
||||
* AgentStepRepository 单元测试
|
||||
*/
|
||||
@DataJpaTest
|
||||
@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
|
||||
@TestPropertySource(properties = {
|
||||
"spring.flyway.enabled=true",
|
||||
"spring.jpa.hibernate.ddl-auto=validate",
|
||||
"spring.jpa.show-sql=true"
|
||||
})
|
||||
class AgentStepRepositoryTest {
|
||||
|
||||
@Autowired
|
||||
private AgentStepRepository repository;
|
||||
|
||||
@Test
|
||||
void testSaveAndFindBySessionId() {
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
|
||||
AgentStep step0 = AgentStep.builder()
|
||||
.sessionId(sessionId)
|
||||
.stepIndex(0)
|
||||
.agentName("planner")
|
||||
.hasToolCall(true)
|
||||
.durationMs(500)
|
||||
.build();
|
||||
repository.save(step0);
|
||||
|
||||
AgentStep step1 = AgentStep.builder()
|
||||
.sessionId(sessionId)
|
||||
.stepIndex(1)
|
||||
.agentName("executor")
|
||||
.hasToolCall(false)
|
||||
.durationMs(300)
|
||||
.build();
|
||||
repository.save(step1);
|
||||
|
||||
List<AgentStep> steps = repository.findBySessionIdOrderByStepIndex(sessionId);
|
||||
assertEquals(2, steps.size());
|
||||
assertEquals("planner", steps.get(0).getAgentName());
|
||||
assertEquals("executor", steps.get(1).getAgentName());
|
||||
assertEquals(500, steps.get(0).getDurationMs());
|
||||
|
||||
int count = repository.countBySessionId(sessionId);
|
||||
assertEquals(2, count);
|
||||
}
|
||||
}
|
||||
@@ -1,173 +0,0 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.enums.DiagnosisStatus;
|
||||
import com.superbiz.agent.domain.enums.FaultCategory;
|
||||
import com.superbiz.agent.domain.entity.DiagnosisRecord;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.boot.test.autoconfigure.jdbc.AutoConfigureTestDatabase;
|
||||
import org.springframework.boot.test.autoconfigure.orm.jpa.DataJpaTest;
|
||||
import org.springframework.test.context.TestPropertySource;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Optional;
|
||||
import java.util.UUID;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.*;
|
||||
|
||||
/**
|
||||
* DiagnosisRecordRepository 单元测试
|
||||
*/
|
||||
@DataJpaTest
|
||||
@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
|
||||
@TestPropertySource(properties = {
|
||||
"spring.flyway.enabled=true",
|
||||
"spring.jpa.hibernate.ddl-auto=validate",
|
||||
"spring.jpa.show-sql=true"
|
||||
})
|
||||
class DiagnosisRecordRepositoryTest {
|
||||
|
||||
@Autowired
|
||||
private DiagnosisRecordRepository repository;
|
||||
|
||||
@Test
|
||||
void testSaveAndFindById() {
|
||||
// 创建测试数据
|
||||
DiagnosisRecord record = DiagnosisRecord.builder()
|
||||
.diagnosisId(UUID.randomUUID().toString())
|
||||
.sessionId("session-001")
|
||||
.businessId("order-12345")
|
||||
.traceId("trace-abc123")
|
||||
.faultCategory(FaultCategory.API)
|
||||
.faultSource("广东")
|
||||
.faultTarget("http://api.example.com/query")
|
||||
.errorCode("40003")
|
||||
.errorMessage("接口超时")
|
||||
.status(DiagnosisStatus.SUCCESS)
|
||||
.confidence(85)
|
||||
.duration(1500)
|
||||
.build();
|
||||
|
||||
// 保存
|
||||
DiagnosisRecord saved = repository.save(record);
|
||||
assertNotNull(saved.getId());
|
||||
assertNotNull(saved.getCreatedAt());
|
||||
System.out.println("✓ 保存成功，ID: " + saved.getId());
|
||||
|
||||
// 查询
|
||||
Optional<DiagnosisRecord> found = repository.findById(saved.getId());
|
||||
assertTrue(found.isPresent());
|
||||
assertEquals("order-12345", found.get().getBusinessId());
|
||||
System.out.println("✓ 根据 ID 查询成功");
|
||||
}
|
||||
|
||||
@Test
|
||||
void testFindByDiagnosisId() {
|
||||
String diagnosisId = UUID.randomUUID().toString();
|
||||
DiagnosisRecord record = DiagnosisRecord.builder()
|
||||
.diagnosisId(diagnosisId)
|
||||
.businessId("order-test-001")
|
||||
.faultCategory(FaultCategory.API)
|
||||
.status(DiagnosisStatus.PENDING)
|
||||
.build();
|
||||
|
||||
repository.save(record);
|
||||
|
||||
Optional<DiagnosisRecord> found = repository.findByDiagnosisId(diagnosisId);
|
||||
assertTrue(found.isPresent());
|
||||
assertEquals(diagnosisId, found.get().getDiagnosisId());
|
||||
System.out.println("✓ 根据 diagnosisId 查询成功");
|
||||
}
|
||||
|
||||
@Test
|
||||
void testFindByFaultCategoryAndErrorCode() {
|
||||
// 创建测试数据
|
||||
DiagnosisRecord record1 = DiagnosisRecord.builder()
|
||||
.diagnosisId(UUID.randomUUID().toString())
|
||||
.faultCategory(FaultCategory.API)
|
||||
.errorCode("40003")
|
||||
.status(DiagnosisStatus.SUCCESS)
|
||||
.build();
|
||||
|
||||
DiagnosisRecord record2 = DiagnosisRecord.builder()
|
||||
.diagnosisId(UUID.randomUUID().toString())
|
||||
.faultCategory(FaultCategory.API)
|
||||
.errorCode("40003")
|
||||
.status(DiagnosisStatus.FAILED)
|
||||
.build();
|
||||
|
||||
repository.save(record1);
|
||||
repository.save(record2);
|
||||
|
||||
// 查询
|
||||
List<DiagnosisRecord> results = repository.findByFaultCategoryAndErrorCode(
|
||||
FaultCategory.API, "40003");
|
||||
|
||||
assertFalse(results.isEmpty());
|
||||
assertTrue(results.size() >= 2);
|
||||
System.out.println("✓ 根据故障类别和错误码查询成功，找到 " + results.size() + " 条记录");
|
||||
}
|
||||
|
||||
@Test
|
||||
void testFindByStatus() {
|
||||
DiagnosisRecord record = DiagnosisRecord.builder()
|
||||
.diagnosisId(UUID.randomUUID().toString())
|
||||
.status(DiagnosisStatus.RUNNING)
|
||||
.faultCategory(FaultCategory.API)
|
||||
.build();
|
||||
|
||||
repository.save(record);
|
||||
|
||||
List<DiagnosisRecord> results = repository.findByStatus(DiagnosisStatus.RUNNING);
|
||||
assertFalse(results.isEmpty());
|
||||
System.out.println("✓ 根据状态查询成功，找到 " + results.size() + " 条 RUNNING 记录");
|
||||
}
|
||||
|
||||
@Test
|
||||
void testUpdateRecord() {
|
||||
// 创建并保存
|
||||
DiagnosisRecord record = DiagnosisRecord.builder()
|
||||
.diagnosisId(UUID.randomUUID().toString())
|
||||
.status(DiagnosisStatus.PENDING)
|
||||
.confidence(0)
|
||||
.build();
|
||||
|
||||
DiagnosisRecord saved = repository.save(record);
|
||||
Long id = saved.getId();
|
||||
|
||||
// 更新
|
||||
saved.setStatus(DiagnosisStatus.SUCCESS);
|
||||
saved.setConfidence(90);
|
||||
saved.setRootCause("接口超时导致");
|
||||
saved.setSolution("增加重试机制");
|
||||
|
||||
repository.save(saved);
|
||||
|
||||
// 验证更新
|
||||
Optional<DiagnosisRecord> updated = repository.findById(id);
|
||||
assertTrue(updated.isPresent());
|
||||
assertEquals(DiagnosisStatus.SUCCESS, updated.get().getStatus());
|
||||
assertEquals(90, updated.get().getConfidence());
|
||||
assertNotNull(updated.get().getUpdatedAt());
|
||||
System.out.println("✓ 更新记录成功");
|
||||
}
|
||||
|
||||
@Test
|
||||
void testDeleteRecord() {
|
||||
DiagnosisRecord record = DiagnosisRecord.builder()
|
||||
.diagnosisId(UUID.randomUUID().toString())
|
||||
.status(DiagnosisStatus.PENDING)
|
||||
.build();
|
||||
|
||||
DiagnosisRecord saved = repository.save(record);
|
||||
Long id = saved.getId();
|
||||
|
||||
// 删除
|
||||
repository.deleteById(id);
|
||||
|
||||
// 验证删除
|
||||
Optional<DiagnosisRecord> deleted = repository.findById(id);
|
||||
assertFalse(deleted.isPresent());
|
||||
System.out.println("✓ 删除记录成功");
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,69 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.entity.DiagnosisSession;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.boot.test.autoconfigure.jdbc.AutoConfigureTestDatabase;
|
||||
import org.springframework.boot.test.autoconfigure.orm.jpa.DataJpaTest;
|
||||
import org.springframework.test.context.TestPropertySource;
|
||||
|
||||
import java.util.Optional;
|
||||
import java.util.UUID;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.*;
|
||||
|
||||
/**
|
||||
* DiagnosisSessionRepository 单元测试
|
||||
*/
|
||||
@DataJpaTest
|
||||
@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
|
||||
@TestPropertySource(properties = {
|
||||
"spring.flyway.enabled=true",
|
||||
"spring.jpa.hibernate.ddl-auto=validate",
|
||||
"spring.jpa.show-sql=true"
|
||||
})
|
||||
class DiagnosisSessionRepositoryTest {
|
||||
|
||||
@Autowired
|
||||
private DiagnosisSessionRepository repository;
|
||||
|
||||
@Test
|
||||
void testSaveAndFindBySessionId() {
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
DiagnosisSession session = DiagnosisSession.builder()
|
||||
.sessionId(sessionId)
|
||||
.query("测试查询")
|
||||
.status("RUNNING")
|
||||
.agentFlow("CHAT")
|
||||
.build();
|
||||
|
||||
DiagnosisSession saved = repository.save(session);
|
||||
assertNotNull(saved.getId());
|
||||
assertEquals(sessionId, saved.getSessionId());
|
||||
|
||||
Optional<DiagnosisSession> found = repository.findBySessionId(sessionId);
|
||||
assertTrue(found.isPresent());
|
||||
assertEquals("测试查询", found.get().getQuery());
|
||||
assertEquals("CHAT", found.get().getAgentFlow());
|
||||
}
|
||||
|
||||
@Test
|
||||
void testUpdateStatus() {
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
DiagnosisSession session = DiagnosisSession.builder()
|
||||
.sessionId(sessionId)
|
||||
.query("更新测试")
|
||||
.status("RUNNING")
|
||||
.agentFlow("AI_OPS")
|
||||
.build();
|
||||
|
||||
DiagnosisSession saved = repository.save(session);
|
||||
saved.setStatus("SUCCESS");
|
||||
saved.setTotalDurationMs(1500);
|
||||
repository.save(saved);
|
||||
|
||||
DiagnosisSession updated = repository.findBySessionId(sessionId).orElseThrow();
|
||||
assertEquals("SUCCESS", updated.getStatus());
|
||||
assertEquals(1500, updated.getTotalDurationMs());
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,64 @@
|
||||
package com.superbiz.agent.repository;
|
||||
|
||||
import com.superbiz.agent.domain.entity.ToolInvocation;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.boot.test.autoconfigure.jdbc.AutoConfigureTestDatabase;
|
||||
import org.springframework.boot.test.autoconfigure.orm.jpa.DataJpaTest;
|
||||
import org.springframework.test.context.TestPropertySource;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.UUID;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.*;
|
||||
|
||||
/**
|
||||
* ToolInvocationRepository 单元测试
|
||||
*/
|
||||
@DataJpaTest
|
||||
@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
|
||||
@TestPropertySource(properties = {
|
||||
"spring.flyway.enabled=true",
|
||||
"spring.jpa.hibernate.ddl-auto=validate",
|
||||
"spring.jpa.show-sql=true"
|
||||
})
|
||||
class ToolInvocationRepositoryTest {
|
||||
|
||||
@Autowired
|
||||
private ToolInvocationRepository repository;
|
||||
|
||||
@Test
|
||||
void testSaveAndFindBySessionId() {
|
||||
String sessionId = UUID.randomUUID().toString().substring(0, 8);
|
||||
|
||||
ToolInvocation inv1 = ToolInvocation.builder()
|
||||
.sessionId(sessionId)
|
||||
.toolName("lookup_knowledge")
|
||||
.inputParams("{\"query\":\"ERR_TIMEOUT\"}")
|
||||
.retrievalLayer("L0")
|
||||
.l0MatchCount(1)
|
||||
.durationMs(50)
|
||||
.success(true)
|
||||
.build();
|
||||
repository.save(inv1);
|
||||
|
||||
ToolInvocation inv2 = ToolInvocation.builder()
|
||||
.sessionId(sessionId)
|
||||
.toolName("queryPrometheusAlerts")
|
||||
.inputParams("{\"metric\":\"cpu_usage\"}")
|
||||
.durationMs(200)
|
||||
.success(true)
|
||||
.build();
|
||||
repository.save(inv2);
|
||||
|
||||
List<ToolInvocation> bySession = repository.findBySessionId(sessionId);
|
||||
assertEquals(2, bySession.size());
|
||||
|
||||
List<ToolInvocation> byTool = repository.findByToolName("lookup_knowledge");
|
||||
assertFalse(byTool.isEmpty());
|
||||
|
||||
List<ToolInvocation> byBoth = repository.findBySessionIdAndToolName(sessionId, "lookup_knowledge");
|
||||
assertEquals(1, byBoth.size());
|
||||
assertEquals("L0", byBoth.get(0).getRetrievalLayer());
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user