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@@ -31,6 +31,7 @@ ONLYOFFICE_PUBLIC_URL=http://127.0.0.1:8082
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ONLYOFFICE_BACKEND_URL=http://127.0.0.1:8000
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ONLYOFFICE_JWT_SECRET=change-me-onlyoffice
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HERMES_AGENT_SHARED_TOKEN=change-me-hermes
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STEWARD_AGENT_RUNTIME=langgraph
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POSTGRES_HOST=127.0.0.1
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POSTGRES_PORT=5432
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vendored
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.omc/
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.omx/
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.claude/
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*.egg-info/
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.codex/*
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!.codex/skills/
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.codex/skills/*
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146
document/development/AI意图规划器/CONCEPT.md
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146
document/development/AI意图规划器/CONCEPT.md
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# AI 意图规划器
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||||
## 功能一句话
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||||
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把用户一句自然语言先交给大模型识别成“动作和步骤”的结构化计划，再由前端/后端确定性执行器逐步校验和执行；规则只作为模型不可用或结构非法时的兜底。
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||||
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||||
## 背景
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||||
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用户真实表达往往不是一个简单关键词，而是一个目标：
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||||
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||||
```text
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||||
去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交
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||||
```
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||||
|
||||
这句话包含至少四层语义：
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||||
|
||||
- 业务对象：差旅费用申请。
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||||
- 已给字段：地点、事由、交通方式。
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||||
- 用户动作：直接提交，不只是生成草稿。
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- 执行步骤：生成申请核对表、校验必填字段、查重、提交审批。
|
||||
|
||||
如果继续用前端规则直接判断，会越来越像关键词路由；正确方向是让大模型先拆成结构化计划，系统只执行经过白名单校验的步骤。
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## 目标
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||||
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- 大模型作为复杂意图的主识别器，输出结构化 `intent plan`。
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- `intent plan` 明确描述用户要执行的动作、业务字段、缺失字段和步骤列表。
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- 执行器只认计划中的白名单步骤，不直接相信模型文本。
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- 字段齐全且用户明确“直接提交”时，系统自动走完整链路。
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- 字段缺失、风险阻断、重复申请或低置信度时，系统停在核对表或风险提示。
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- 本地规则只作为 `rule_fallback`，不得伪装成模型判断。
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## 非目标
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||||
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||||
- 不让大模型直接写数据库、提交审批或绑定附件。
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||||
- 不引入 LangChain 高层 Agent 来替代现有业务服务。
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||||
- 不让 LangGraph 直接接管模型供应商密钥、数据库写入或审批副作用。
|
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- 不绕过已有申请预览、规则测算、重复申请核查和提交接口。
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- 不把所有财务场景一次性改完；第一阶段先覆盖个人工作台 AI 模式里的差旅申请链路。
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||||
|
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## 结构化计划契约
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前端执行器消费统一结构：
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```json
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||||
{
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"source": "llm_function_call",
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"intent": "create_travel_application",
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"requestedAction": "submit",
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"confidence": 0.91,
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"sourceText": "去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交",
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"slots": {
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"location": "上海",
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"reason": "辅助国网仿生产服务器部署",
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"transportMode": "火车"
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},
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"missingFields": [],
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"steps": [
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"build_application_preview",
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"validate_required_fields",
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"run_duplicate_precheck",
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"submit_application"
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]
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||||
}
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```
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||||
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||||
## 步骤白名单
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||||
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- `build_application_preview`：生成申请核对表，复用现有申请预览能力。
|
||||
- `validate_required_fields`：用确定性代码校验必填字段和字段格式。
|
||||
- `run_duplicate_precheck`：提交前查询同日期或重叠申请单。
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||||
- `submit_application`：调用现有申请提交动作；只有用户明确要求提交且前置校验通过才执行。
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||||
- `save_application_draft`：调用现有申请草稿保存能力。
|
||||
- `create_reimbursement_draft`：调用现有报销草稿创建能力。
|
||||
- `associate_attachments`：调用现有附件关联 runner；缺少 `receipt_ids` 或匹配不唯一时阻断，不能假成功。
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||||
- `link_existing_application`：调用现有报销草稿创建链路并写入申请关联 flag；申请单不存在、未审批或已被报销时阻断。
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||||
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||||
## 数据流
|
||||
|
||||
```text
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||||
用户输入
|
||||
↓
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||||
steward LLM function calling
|
||||
↓
|
||||
模型计划归一化与白名单校验
|
||||
↓
|
||||
可执行 intent plan
|
||||
↓
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||||
申请/报销/附件等确定性执行器
|
||||
↓
|
||||
核对表、风险提示、草稿或提交结果
|
||||
```
|
||||
|
||||
当模型不可用、超时或返回不可执行结构时：
|
||||
|
||||
```text
|
||||
模型失败
|
||||
↓
|
||||
本地 rule_fallback 生成保守计划
|
||||
↓
|
||||
同一个执行器继续处理
|
||||
```
|
||||
|
||||
## 安全边界
|
||||
|
||||
- 模型只负责“理解”和“拆步骤”，不拥有副作用权限。
|
||||
- 执行器必须校验 `intent` 和 `steps` 是否在白名单内；未知 action 必须阻断，不能调用业务服务。
|
||||
- 提交前必须走 `readyToSubmit` 和重复申请 precheck。
|
||||
- 提交类副作用必须带用户确认和 precheck 通过证据。
|
||||
- 地点、日期、事由等字段仍由现有申请预览和规则校验模块判断。
|
||||
- 模型置信度低、流程冲突或必填字段缺失时，不自动提交。
|
||||
|
||||
## 第一阶段落地
|
||||
|
||||
- 新增前端 planner model，把后端 `StewardPlanResponse` 映射成前端 `intent plan`。
|
||||
- 个人工作台 AI 模式在命中差旅申请候选时，优先调用现有 `/steward/plans` 获取模型计划。
|
||||
- 模型计划可执行时，按 `steps` 生成申请核对表并在条件满足时自动提交。
|
||||
- 模型不可用或计划不可执行时，使用本地 `rule_fallback` 保持体验不倒退。
|
||||
- 保留既有普通小财管家路径，用来处理无法直接执行或更复杂的多任务场景。
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||||
|
||||
## LangGraph 迁移方向
|
||||
|
||||
后端小财管家的规划入口、槽位决策入口和运行时动作决策入口已经开始迁入 LangGraph。
|
||||
后续不再继续把感知、规划、补字段、运行时动作判断堆进自研 `if/else` 编排，而是按 node 拆分：
|
||||
|
||||
- `model_intent_node`：模型 function calling 规划。
|
||||
- `slot_tool_decision_node`：字段缺口与追问判断，失败时进入规则兜底。
|
||||
- `runtime_memory_context_node`：合并前端运行时状态和持久化 `steward_state`。
|
||||
- `runtime_tool_decision_node`：用户补充、确认、取消、继续执行等运行时判断。
|
||||
- `runtime_action_decision_node`：已选流程确认等不需要模型的确定性行动路由。
|
||||
- `action_plan_node`：生成白名单 `StewardActionStep`，当前已覆盖申请预览、保存草稿、直接提交和报销草稿。
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||||
- `human_review_node`：保存草稿、提交审批、关联申请单前的确认点。
|
||||
- `action_execute_node`：调用现有确定性业务服务；当前已由 `/steward/actions/execute`、`StewardGraphActionRuntime` 和 `StewardActionExecutor` 提供 checkpoint、pending interrupt 和幂等重放。
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||||
- `persist_state_node`：合并 conversation state 和 steward state。
|
||||
|
||||
当前 `plans` 已返回服务端 `action_steps`，`slot-decisions` / `runtime-decisions` 已默认走 `StewardGraphRuntime`。
|
||||
如果 LangGraph 图节点异常，服务端会退回原有 Agent 和规则兜底，避免框架层故障影响用户会话。
|
||||
|
||||
详细迁移计划见 `LANGGRAPH_RUNTIME_MIGRATION.md`。
|
||||
|
||||
## 测试策略
|
||||
|
||||
- planner model 单元测试：模型计划归一化、rule fallback、政策咨询排除。
|
||||
- 前端静态接线测试：主流程必须先请求 steward plan，再 fallback。
|
||||
- 申请预览回归测试：`直接提交` 不得污染事由；缺日期不得伪造字段。
|
||||
- 构建验证：`npm --prefix web run build`。
|
||||
420
document/development/AI意图规划器/LANGGRAPH_RUNTIME_MIGRATION.md
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420
document/development/AI意图规划器/LANGGRAPH_RUNTIME_MIGRATION.md
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||||
# 小财管家 LangGraph Runtime 迁移计划
|
||||
|
||||
> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
|
||||
|
||||
**Goal:** 把小财管家的感知、规划、记忆、确认和行动逐步迁到 LangGraph runtime，减少自研流程编排里的隐藏状态和分支 bug。
|
||||
|
||||
**Architecture:** 保留现有 FastAPI API、Pydantic schema、`RuntimeChatService` 模型供应商抽象和业务服务；LangGraph 只接管 agent 编排。副作用动作必须通过白名单 action node 调用现有业务服务，保存草稿、提交和关联单据都不能由模型文本直接触发。
|
||||
|
||||
**Tech Stack:** Python 3.11、FastAPI、Pydantic、LangGraph 1.x、SQLAlchemy、现有 `AgentConversationService` / `StewardFlowStateService`。
|
||||
|
||||
---
|
||||
|
||||
## 当前状态
|
||||
|
||||
已经完成第一阶段接入：
|
||||
|
||||
- `server/src/app/services/steward_graph_planner.py`
|
||||
- 已新增 `StewardGraphPlannerService`。
|
||||
- 已用 LangGraph `StateGraph` 编排 `prepare_context -> detect_model_intent -> done/off_topic/rule_fallback`。
|
||||
- `server/src/app/services/steward_graph_runtime.py`
|
||||
- 已新增 `StewardGraphRuntime`。
|
||||
- 槽位决策已编排为 `slot_prepare_context -> slot_tool_decision -> done/rule_fallback`。
|
||||
- 运行时决策已编排为 `runtime_memory_context -> runtime_action_decision/runtime_tool_decision -> done/rule_fallback`。
|
||||
- 图内失败会降级到原有规则兜底；端点层图运行异常会回退旧 Agent。
|
||||
- `server/src/app/services/steward_action_contracts.py`
|
||||
- 已新增 `StewardActionPlanBuilder`。
|
||||
- 已把申请、报销、保存草稿、直接提交规划成 `StewardActionStep` 白名单动作。
|
||||
- `StewardGraphPlannerService` 已增加 `attach_action_steps` 节点，计划返回前统一补全动作列表。
|
||||
- `server/src/app/services/steward_action_executor.py`
|
||||
- 已新增 `StewardActionExecutor`。
|
||||
- 已接入 `/steward/actions/execute`，支持未知动作拒绝、缺字段阻断、提交确认门禁、重复申请 precheck、申请/报销草稿真实执行、关联申请单和附件关联。
|
||||
- 申请动作复用 `UserAgentService` 的申请保存/提交能力，报销草稿复用 `ExpenseClaimService.save_or_submit_from_ontology()`。
|
||||
- `server/src/app/services/steward_graph_action_runtime.py`
|
||||
- 已新增 `StewardGraphActionRuntime`。
|
||||
- 已用 LangGraph `StateGraph` 编排 `action_checkpoint_load -> action_execute_node -> action_checkpoint_persist`。
|
||||
- 已通过 `conversation_id + client_trace_id` 在 `AgentConversation.state_json` 中记录 checkpoint、pending interrupt 和幂等重放结果。
|
||||
- `web/src/services/steward.js` / `web/src/views/scripts/stewardPlanModel.js`
|
||||
- 前端已新增 `executeStewardAction()` 服务方法。
|
||||
- steward suggested action 已携带服务端可执行 action step，旧申请预览流仍保留兜底。
|
||||
- `web/src/composables/workbenchAiMode/useWorkbenchAiActionRouter.js`
|
||||
- AI 工作台点击 `steward_execute_action` 时会调用 `/steward/actions/execute`。
|
||||
- 直接提交会先执行 `run_duplicate_precheck`，precheck 通过后再提交申请。
|
||||
- `server/src/app/api/v1/endpoints/steward.py`
|
||||
- `/steward/plans` 和 `/steward/plans/stream` 默认使用 `StewardGraphPlannerService`。
|
||||
- `/steward/slot-decisions` 和 `/steward/runtime-decisions` 默认使用 `StewardGraphRuntime`。
|
||||
- `STEWARD_AGENT_RUNTIME=legacy` 可回退旧 `StewardPlannerService`。
|
||||
- `server/pyproject.toml` / `server/uv.lock`
|
||||
- 已加入 `langgraph>=1.2.0,<2.0.0`。
|
||||
- `server/tests/test_steward_graph_planner.py`
|
||||
- 已覆盖默认 LangGraph、显式 LangGraph、legacy 回退、模型成功计划和模型失败后规则兜底。
|
||||
- `server/tests/test_steward_graph_runtime.py`
|
||||
- 已覆盖槽位工具节点、图内规则兜底、运行时记忆合并、确定性行动选择和端点级 legacy 兜底。
|
||||
- `server/tests/test_application_fact_resolver.py`
|
||||
- 已覆盖 `交通火车` 不污染申请事由，以及 `高铁往返` 这类业务描述仍保留。
|
||||
|
||||
当前已完成规划入口、slot decision、runtime decision、基础 action contract、第一版 action executor、前端点击执行闭环，以及 action runtime 的 checkpoint / interrupt / 幂等重放。
|
||||
真实外部模型连通性仍需要用当前 MiniMax / backup 配置再回放确认。
|
||||
|
||||
## 官方能力边界
|
||||
|
||||
LangGraph 官方文档强调它是低层 agent orchestration runtime，重点能力是 durable execution、streaming、human-in-the-loop 和 persistence。
|
||||
|
||||
本项目只采用这些底层编排能力：
|
||||
|
||||
- Graph API：用 state、node、edge 表达流程，node 可以是 LLM 调用，也可以是普通业务代码。
|
||||
- Persistence：用 checkpointer 保存 thread scoped state，用 store 保存跨线程长期信息。
|
||||
- Interrupt：在需要用户确认时暂停 graph，等待外部输入后恢复。
|
||||
|
||||
参考：
|
||||
|
||||
- <https://docs.langchain.com/oss/python/langgraph/overview>
|
||||
- <https://docs.langchain.com/oss/python/langgraph/graph-api>
|
||||
- <https://docs.langchain.com/oss/python/langgraph/persistence>
|
||||
- <https://docs.langchain.com/oss/python/langgraph/interrupts>
|
||||
|
||||
## 总体目标架构
|
||||
|
||||
```text
|
||||
用户输入 / 前端上下文 / 附件
|
||||
↓
|
||||
StewardGraphRuntime
|
||||
├── prepare_context_node
|
||||
├── model_intent_node
|
||||
├── slot_decision_node
|
||||
├── flow_guard_node
|
||||
├── action_plan_node
|
||||
├── human_review_node
|
||||
├── action_execute_node
|
||||
├── persist_state_node
|
||||
└── response_adapter_node
|
||||
↓
|
||||
现有前端协议：StewardPlanResponse / StewardRuntimeDecisionResponse / StewardSlotDecisionResponse
|
||||
```
|
||||
|
||||
关键原则：
|
||||
|
||||
- API 响应协议稳定，前端不因为 runtime 替换被迫大改。
|
||||
- 模型只负责理解、拆步骤、给候选 action，不直接写库。
|
||||
- 所有副作用节点必须调用现有业务服务，并保留确认和审计。
|
||||
- `RuntimeChatService` 继续是唯一模型调用入口，LangGraph 不直接管理供应商密钥。
|
||||
- `StewardFlowStateService` 和 `AgentConversationService` 是 checkpoint 落库的第一候选，不另起一套状态源。
|
||||
|
||||
## Runtime State 草案
|
||||
|
||||
第一版 graph state 用 `TypedDict`，后续需要持久化时再评估 Pydantic schema。
|
||||
|
||||
```python
|
||||
class StewardGraphState(TypedDict, total=False):
|
||||
request: StewardPlanRequest
|
||||
conversation_id: str
|
||||
thread_id: str
|
||||
message: str
|
||||
base_date: date
|
||||
steward_state: dict[str, Any]
|
||||
model_call_traces: list[dict[str, Any]]
|
||||
intent_result: StewardIntentAgentResult | None
|
||||
slot_decision: StewardSlotDecisionResponse | None
|
||||
runtime_decision: StewardRuntimeDecisionResponse | None
|
||||
action_plan: list[StewardActionStep]
|
||||
pending_interrupt: dict[str, Any]
|
||||
action_result: dict[str, Any]
|
||||
response: StewardPlanResponse | StewardRuntimeDecisionResponse | StewardSlotDecisionResponse
|
||||
fallback_reason: str
|
||||
```
|
||||
|
||||
`thread_id` 推荐使用现有 `conversation_id`，这样 LangGraph checkpoint、业务会话和前端会话能对齐。
|
||||
|
||||
## 节点边界
|
||||
|
||||
### 感知节点
|
||||
|
||||
- `prepare_context_node`
|
||||
- 输入：`StewardPlanRequest` 或 runtime decision request。
|
||||
- 输出：清洗后的消息、base date、当前 conversation state。
|
||||
- 禁止：模型调用、数据库写入。
|
||||
|
||||
- `model_intent_node`
|
||||
- 调用：`StewardIntentAgent.detect()`。
|
||||
- 约束：保留 `timeout_seconds=10`、`max_attempts=3`、`use_failure_cooldown=False`。
|
||||
- 失败：只写入 `fallback_reason` 和 `model_call_traces`，不吞掉错误上下文。
|
||||
|
||||
### 决策节点
|
||||
|
||||
- `slot_decision_node`
|
||||
- 迁移对象：`StewardSlotDecisionAgent.decide()`。
|
||||
- 目标：让字段缺口判断进入同一个 graph state，不再由前端和后端多个入口各自推断。
|
||||
|
||||
- `runtime_decision_node`
|
||||
- 迁移对象：`StewardRuntimeDecisionAgent.decide()`。
|
||||
- 目标：用户补字段、确认流程、取消当前动作、继续下一任务都走 graph routing。
|
||||
|
||||
- `flow_guard_node`
|
||||
- 负责申请/报销歧义、重复单据、时间重叠、低置信度、off-topic。
|
||||
- 低置信度或强冲突必须进入确认或阻断，不允许继续 action 执行。
|
||||
|
||||
### 行动节点
|
||||
|
||||
- `action_plan_node`
|
||||
- 输出白名单步骤，例如 `build_application_preview`、`save_application_draft`、`submit_application`。
|
||||
- 禁止输出自由文本 action。
|
||||
|
||||
- `human_review_node`
|
||||
- 对保存草稿、提交审批、关联申请单等副作用动作生成 interrupt payload。
|
||||
- 第一阶段可继续返回前端确认动作；第二阶段再接 LangGraph `interrupt()`。
|
||||
|
||||
- `action_execute_node`
|
||||
- 只能调用现有业务服务。
|
||||
- 必须幂等，或在执行前检查动作是否已完成。
|
||||
- 提交类动作必须检查 `confirmation_required` 和用户确认来源。
|
||||
|
||||
- `persist_state_node`
|
||||
- 合并 `StewardFlowStateService.merge_plan()` / `merge_state()`。
|
||||
- 后续接入 LangGraph checkpointer 后，这里负责业务状态与 checkpoint 的一致性。
|
||||
|
||||
### 响应节点
|
||||
|
||||
- `response_adapter_node`
|
||||
- 输出现有 Pydantic response。
|
||||
- 必须保留 `model_call_traces`、`planning_source`、`steward_state`。
|
||||
|
||||
## 分阶段计划
|
||||
|
||||
### Phase 0：规划入口接入 LangGraph
|
||||
|
||||
状态：已完成。
|
||||
|
||||
完成标准：
|
||||
|
||||
- [x] 默认 runtime 为 `langgraph`。
|
||||
- [x] `STEWARD_AGENT_RUNTIME=legacy` 可回退。
|
||||
- [x] `/steward/plans` 真实接口仍返回兼容的 `StewardPlanResponse`。
|
||||
- [x] 模型失败后仍按 10s * 3 次再规则降级。
|
||||
|
||||
### Phase 1：修通模型成功路径
|
||||
|
||||
目标：让真实保存草稿话术至少能走一次 `llm_function_call` 成功路径。
|
||||
|
||||
文件：
|
||||
|
||||
- 修改：`server/src/app/services/runtime_chat.py`
|
||||
- 修改：`server/src/app/services/settings.py`
|
||||
- 修改：`server/tests/test_runtime_chat_service.py`
|
||||
- 测试：`server/tests/test_steward_intent_agent.py`
|
||||
|
||||
步骤：
|
||||
|
||||
- [x] 写失败测试：模拟 main provider 超时但 backup provider 可用时，`complete_with_tool_call()` 返回 backup 的 tool call。
|
||||
- [x] 确认 backup function calling 会在 main 失败后返回 tool call，不等待 main 重试结束。
|
||||
- [ ] 写失败测试：MiniMax 返回非 OpenAI tool call 兼容格式时，服务端能记录清晰 trace 并降级。
|
||||
- [x] 容器内运行：
|
||||
|
||||
```bash
|
||||
docker exec -w /app -e SERVER_VENV_DIR=/tmp/x-financial-server-venv x-financial-local-linux \
|
||||
timeout 60s /tmp/x-financial-server-venv/bin/pytest -q \
|
||||
server/tests/test_runtime_chat_service.py \
|
||||
server/tests/test_steward_intent_agent.py
|
||||
```
|
||||
|
||||
验收：
|
||||
|
||||
- [ ] 真实 `/api/v1/steward/plans` 对保存草稿原句返回 `planning_source=llm_function_call`。
|
||||
- [x] `model_call_traces` 能区分 main 失败、backup 成功或全失败。
|
||||
|
||||
### Phase 2：slot/runtime decision 迁入 graph
|
||||
|
||||
目标：把字段缺口和运行时动作判断从独立 agent 类迁进同一个 graph runtime。
|
||||
|
||||
状态：已完成。
|
||||
|
||||
文件：
|
||||
|
||||
- 已创建：`server/src/app/services/steward_graph_runtime.py`
|
||||
- 已修改：`server/src/app/api/v1/endpoints/steward.py`
|
||||
- 已测试：`server/tests/test_steward_graph_runtime.py`
|
||||
- 保留测试：`server/tests/test_steward_slot_decision_agent.py`
|
||||
- 保留测试：`server/tests/test_steward_runtime_decision_agent.py`
|
||||
|
||||
步骤：
|
||||
|
||||
- [x] 写失败测试：`StewardGraphRuntime.decide_slot()` 调用 slot node 后返回与现有 `StewardSlotDecisionAgent.decide()` 等价的 response。
|
||||
- [x] 写失败测试：`StewardGraphRuntime.decide_runtime()` 在用户补充字段时合并 `steward_state`。
|
||||
- [x] 把 `StewardSlotDecisionAgent` 包成 `slot_tool_decision` 节点。
|
||||
- [x] 把 `StewardRuntimeDecisionAgent` 包成 `runtime_tool_decision` 节点。
|
||||
- [x] 把已选流程确认和当前运行时记忆归一化拆成 `runtime_memory_context` / `runtime_action_decision` 节点。
|
||||
- [x] endpoint 在 `STEWARD_AGENT_RUNTIME=langgraph` 时使用 graph runtime。
|
||||
- [x] endpoint 在 graph runtime 异常时回退旧 Agent，避免框架层失效影响会话。
|
||||
|
||||
验收：
|
||||
|
||||
- [x] `slot-decisions`、`runtime-decisions` 和 `plans` 三个入口都由 LangGraph runtime 路由。
|
||||
- [x] legacy 回退仍可用。
|
||||
- [x] 图内工具节点失败时仍有可执行规则兜底。
|
||||
|
||||
### Phase 3：action node 标准化
|
||||
|
||||
目标：把保存草稿、提交审批、关联申请单这些副作用动作变成显式 action node。
|
||||
|
||||
状态：基础 action contract、第一版 action executor、前端点击执行闭环、LangGraph action node、checkpoint、pending interrupt 和幂等重放已完成；后续只剩 durable checkpointer 抽象与更完整 trace UI。
|
||||
|
||||
文件：
|
||||
|
||||
- 已创建：`server/src/app/services/steward_action_executor.py`
|
||||
- 已创建：`server/src/app/services/steward_action_contracts.py`
|
||||
- 已创建：`server/src/app/services/steward_graph_action_runtime.py`
|
||||
- 已修改：`server/src/app/api/v1/endpoints/steward.py`
|
||||
- 已修改：`server/src/app/services/steward_graph_planner.py`
|
||||
- 已修改：`server/src/app/schemas/steward.py`
|
||||
- 已修改：`web/src/services/steward.js`
|
||||
- 已修改：`web/src/views/scripts/stewardPlanModel.js`
|
||||
- 已修改：`web/src/composables/workbenchAiMode/useWorkbenchAiActionRouter.js`
|
||||
- 已修改：`web/src/composables/workbenchAiMode/usePersonalWorkbenchAiMode.js`
|
||||
- 已测试：`server/tests/test_steward_action_executor.py`
|
||||
- 已测试：`server/tests/test_steward_graph_planner.py`
|
||||
- 已测试：`server/tests/test_steward_planner.py`
|
||||
- 已测试：`web/tests/workbench-ai-intent-planner-model.test.mjs`
|
||||
- 已测试：`web/tests/steward-actions-service.test.mjs`
|
||||
- 已测试：`web/tests/steward-plan-message-copy.test.mjs`
|
||||
- 已测试：`web/tests/workbench-ai-action-router.test.mjs`
|
||||
|
||||
白名单 action：
|
||||
|
||||
- `build_application_preview`
|
||||
- `save_application_draft`
|
||||
- `submit_application`
|
||||
- `link_existing_application`
|
||||
- `create_reimbursement_draft`
|
||||
- `associate_attachments`
|
||||
|
||||
步骤：
|
||||
|
||||
- [x] 写失败测试：申请直接提交计划必须输出 `fill_application_fields -> build_application_preview -> validate_required_fields -> run_duplicate_precheck -> submit_application`。
|
||||
- [x] 写失败测试：保存草稿计划必须输出 `save_application_draft`，并在字段缺失时阻断后续副作用。
|
||||
- [x] 写失败测试：报销计划必须输出 `fill_reimbursement_fields -> build_reimbursement_preview -> validate_required_fields -> create_reimbursement_draft`。
|
||||
- [x] 在 `StewardTask` 和 `StewardPlanResponse` 中增加 `action_steps`。
|
||||
- [x] 实现 `StewardActionPlanBuilder`，由服务端确定性生成白名单 action step。
|
||||
- [x] 在 LangGraph planner 中新增 `attach_action_steps` 节点。
|
||||
- [x] 前端 planner model 优先消费服务端 `task.action_steps`，旧响应才回退本地推导。
|
||||
- [x] 写失败测试：未知 action step 被拒绝，不调用任何业务服务。
|
||||
- [x] 写失败测试：`submit_application` 缺少确认来源时返回 `needs_confirmation`。
|
||||
- [x] 写失败测试：`submit_application` 必须看到 precheck 通过后才允许真实提交。
|
||||
- [x] 实现 action registry，只允许白名单 action。
|
||||
- [x] 接入现有申请保存草稿、申请提交和报销草稿服务。
|
||||
- [x] 前端新增 `executeStewardAction()` 并让 suggested action 携带服务端 action step。
|
||||
- [x] AI 工作台点击 suggested action 时调用 `StewardActionExecutor`；直接提交先串行执行 precheck，再把结果交给 submit。
|
||||
- [x] 接入 `link_existing_application` 和附件关联的真实执行。
|
||||
- [x] 把 action executor 包成 LangGraph `action_execute_node`，并接入 checkpoint / interrupt 恢复。
|
||||
|
||||
验收：
|
||||
|
||||
- [x] 模型不能通过自由文本触发数据库写入，服务端只输出白名单 `StewardActionStep`。
|
||||
- [x] 申请提交动作没有确认时返回 `needs_confirmation`，不会写库。
|
||||
- [x] 申请提交动作没有 precheck 通过证据时被阻断。
|
||||
- [x] 保存申请草稿和创建报销草稿通过现有业务服务真实入库，测试覆盖。
|
||||
- [x] 前端点击可执行 steward action 会真实调用 executor，并把结果回写到会话消息。
|
||||
- [x] 基础副作用动作有 `client_trace_id` 幂等键、conversation checkpoint 和 pending interrupt 记录。
|
||||
|
||||
### Phase 4：checkpoint 与 human-in-the-loop
|
||||
|
||||
目标：让 LangGraph 负责暂停、恢复和跨轮状态，而不是只靠前端消息状态。
|
||||
|
||||
文件：
|
||||
|
||||
- 已创建：`server/src/app/services/steward_graph_action_runtime.py`
|
||||
- 已复用：`server/src/app/models/agent_conversation.py`
|
||||
- 已测试：`server/tests/test_steward_action_executor.py`
|
||||
|
||||
步骤：
|
||||
|
||||
- [x] 设计 `conversation_id -> thread_id` 映射，当前直接以 `conversation_id` 作为 graph action thread。
|
||||
- [x] 实现基于数据库的 checkpoint，先复用 `AgentConversation.state_json`。
|
||||
- [x] 在提交审批缺确认时生成 pending interrupt payload。
|
||||
- [x] 用户确认后用同一 `client_trace_id` / `conversation_id` 继续执行；终态请求会幂等重放。
|
||||
|
||||
验收：
|
||||
|
||||
- [x] 刷新页面后，后端仍保留当前等待确认的 action checkpoint。
|
||||
- [x] 同一个 action 不会因为重复点击或重试重复写库。
|
||||
- [ ] 前端完整恢复 UI 仍需继续把 checkpoint 状态展示为可恢复按钮。
|
||||
|
||||
### Phase 5：可观测性与 legacy 收敛
|
||||
|
||||
目标：让 agent 规划过程可解释、可测试、可回放，并逐步删除重复手写编排。
|
||||
|
||||
文件：
|
||||
|
||||
- 修改：`server/src/app/services/agent_traces.py`
|
||||
- 修改：`server/src/app/models/agent_run.py`
|
||||
- 修改：`document/development/Agent链路追踪中心/CONCEPT.md`
|
||||
- 测试：`server/tests/test_agent_traces.py`
|
||||
|
||||
步骤：
|
||||
|
||||
- [ ] 每个 graph node 写入 trace event：输入摘要、输出摘要、耗时、错误。
|
||||
- [ ] 前端显示“模型规划中 / 字段判断中 / 等待确认 / 执行动作”阶段。
|
||||
- [ ] 对 legacy planner 增加废弃标记和删除条件。
|
||||
- [ ] 删除重复的手写分支前，先保留至少一轮灰度开关。
|
||||
|
||||
验收：
|
||||
|
||||
- 任何一次用户请求都能从 trace 看出走过哪些 node。
|
||||
- 删除 legacy 前，LangGraph 路径覆盖当前核心申请/报销链路测试。
|
||||
|
||||
## 回退策略
|
||||
|
||||
- 环境变量：
|
||||
|
||||
```bash
|
||||
STEWARD_AGENT_RUNTIME=legacy
|
||||
```
|
||||
|
||||
- 回退后：
|
||||
- `/steward/plans` 使用旧 `StewardPlannerService`。
|
||||
- 新 action node 和 checkpoint 不应影响 legacy。
|
||||
- 回退原因必须写入当天工作日志。
|
||||
|
||||
## 验证矩阵
|
||||
|
||||
每个阶段至少跑：
|
||||
|
||||
```bash
|
||||
docker exec -w /app -e SERVER_VENV_DIR=/tmp/x-financial-server-venv x-financial-local-linux \
|
||||
timeout 60s /tmp/x-financial-server-venv/bin/pytest -q \
|
||||
server/tests/test_steward_graph_planner.py \
|
||||
server/tests/test_steward_planner.py \
|
||||
server/tests/test_steward_intent_agent.py \
|
||||
server/tests/test_runtime_chat_service.py
|
||||
```
|
||||
|
||||
涉及前端执行器时补跑：
|
||||
|
||||
```bash
|
||||
node --test web/tests/workbench-ai-intent-planner-model.test.mjs \
|
||||
web/tests/workbench-ai-application-gate-model.test.mjs \
|
||||
web/tests/steward-actions-service.test.mjs \
|
||||
web/tests/steward-plan-message-copy.test.mjs
|
||||
npm --prefix web run build
|
||||
```
|
||||
|
||||
每次完成后执行：
|
||||
|
||||
```bash
|
||||
git diff --check
|
||||
docker exec -w /app -e SERVER_VENV_DIR=/tmp/x-financial-server-venv x-financial-local-linux \
|
||||
/tmp/x-financial-server-venv/bin/python -m pip check
|
||||
```
|
||||
|
||||
## 不做的事
|
||||
|
||||
- 不引入 LangChain 高层 Agent 来替代现有业务服务。
|
||||
- 不让模型直接调用数据库写入、提交审批或绑定附件。
|
||||
- 不为了接框架重写申请、报销、OCR、票据夹、审批规则。
|
||||
- 不在没有测试覆盖时删除 legacy planner。
|
||||
|
||||
## 风险与处理
|
||||
|
||||
- 模型连通性不稳定：先修 provider 和 backup，再扩大 graph 节点。
|
||||
- checkpoint 与业务 state 双写不一致：先复用 `AgentConversation.state_json`，不要新增第二个业务状态源。
|
||||
- action node 副作用重复执行：每个 action 必须有幂等键和执行前状态检查。
|
||||
- LangGraph 传递依赖影响 WebSocket：当前 `pip check` 通过；后续若流式接口异常，先核对 `websockets` 版本。
|
||||
- 节点内继续堆大块逻辑：每个 node 只做一类事，超过 300 行先拆文件。
|
||||
32
document/development/AI意图规划器/TODO.md
Normal file
32
document/development/AI意图规划器/TODO.md
Normal file
@@ -0,0 +1,32 @@
|
||||
# AI 意图规划器 TODO
|
||||
|
||||
## 第一阶段
|
||||
|
||||
- [x] 落地 AI 意图规划器概念文档，明确大模型负责拆计划、业务代码负责执行。
|
||||
- [x] 新增前端 planner model，统一模型计划和本地 fallback 的输出结构。
|
||||
- [x] 个人工作台 AI 模式先请求 steward 模型计划，再使用本地 fallback。
|
||||
- [x] 差旅申请直提链路改为消费 `intent plan.steps`，不再直接消费正则识别结果。
|
||||
- [x] 补齐 planner model 与主流程接线回归测试。
|
||||
- [x] 跑前端构建和定向测试。
|
||||
- [x] 后端 `/steward/plans` 增加 `requested_action` 输出，减少前端从原句推断“提交/保存”的比例。
|
||||
- [x] 引入 LangGraph，并默认用 `StewardGraphPlannerService` 接管 `/steward/plans` 规划编排。
|
||||
- [x] 落地 LangGraph runtime 迁移计划文档：`LANGGRAPH_RUNTIME_MIGRATION.md`。
|
||||
- [x] 新增 `StewardGraphRuntime`，接管 `slot-decisions` 和 `runtime-decisions` 的 LangGraph 路由。
|
||||
- [x] 为 LangGraph runtime 增加图内规则兜底和端点级 legacy Agent 兜底。
|
||||
- [x] 为 `/steward/plans` 增加服务端白名单 `action_steps`，覆盖申请、报销、保存草稿和直接提交的基础动作规划。
|
||||
- [x] 前端 planner model 优先消费服务端 `task.action_steps`，旧响应才回退本地步骤推导。
|
||||
- [x] 新增 `/steward/actions/execute` 和 `StewardActionExecutor`，把未知 action 拒绝、提交确认门禁、precheck 阻断、申请草稿保存、申请提交和报销草稿创建接到现有业务服务。
|
||||
- [x] 前端新增 `executeStewardAction()` 服务方法，并让 steward suggested action 携带服务端可执行 action step。
|
||||
- [x] AI 工作台点击可执行 steward action 时调用 `/steward/actions/execute`；申请直接提交会先跑 `run_duplicate_precheck`，通过后再提交。
|
||||
- [x] `complete_with_tool_call()` 增加 main 失败后 backup tool-call 成功路径测试，保证模型成功路径能从 backup 返回 `llm_function_call`。
|
||||
- [x] 新增 `StewardGraphActionRuntime`，把 action executor 包成 LangGraph `action_execute_node`，并用 `conversation_id + client_trace_id` 在 `AgentConversation.state_json` 中持久化 checkpoint。
|
||||
- [x] 对提交确认生成 pending interrupt；重复 client trace 直接重放 checkpoint，避免重复保存草稿或重复提交。
|
||||
- [x] `link_existing_application` 接入现有报销草稿创建链路并写入申请关联 flag。
|
||||
- [x] `associate_attachments` 接入现有附件关联 runner，按 receipt_ids 归集到可匹配报销草稿。
|
||||
|
||||
## 后续阶段
|
||||
|
||||
- [ ] 用真实 MiniMax / backup 配置再回放 `/steward/plans`，确认真实环境返回 `planning_source=llm_function_call`，不是规则兜底。
|
||||
- [ ] 将当前 `AgentConversation.state_json` checkpoint 抽象为可替换的 durable checkpointer，并补恢复/清理策略。
|
||||
- [ ] 为每个 LangGraph node 写入可追溯 trace，展示模型调用、规则降级、等待确认和动作执行结果。
|
||||
- [ ] 在 LangGraph 路径覆盖申请/报销核心链路后，再逐步删除旧 `StewardPlannerService` 的重复编排。
|
||||
@@ -214,6 +214,188 @@
|
||||
- 操作：重启当前实际运行容器 `x-financial-local-linux` 并确认 `/api/v1/health` 正常；真实 5173 `/api/v1/ocr/recognize` 重新上传 `2月23_上海-武汉.pdf` 后返回 `document_type=train_ticket`、`preview_kind=image`、`receipt_preview_url=/receipt-folder/.../preview`，对应 `/preview` 响应 `content-type: image/png`。
|
||||
- 影响：AI 会话上传 PDF 火车票后，附件条和预览弹窗都会走统一预览资产判定；后续其它入口只要使用 `documentPreviewAssets.js`，就不会再各自维护一套 PDF/图片判断。
|
||||
|
||||
- 12:52：我重新修改了一键关联票据对话框的 UI 样式，并根据“卡片过大、不够精致”的反馈进行了尺寸收敛与精细化微调。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功执行；`HEAD..origin/main` 与 `origin/main..HEAD` 均无提交。
|
||||
- 修改：在 `receipt-folder-view.css` 中，为弹窗外框加上轻量圆角 (6px) 与精致投影；将弹窗 header padding 收至 `20px 24px 12px 24px`，body padding 收至 `0 24px 20px 24px`，确保紧凑挺拔。
|
||||
- 修改：将列表行间距设为 `8px`，每个条目高度收敛至 `52px`，内边距调整为 `10px 14px`，文件名与说明文本大小降为 `13px` 与 `11.5px`，以求更加精致细腻。
|
||||
- 修改：将底部操作区的按钮高度设为标准 `36px`，水平内边距设为 `16px`，字重保持专业的 `500`，使比例更协调，消除挤压感的同时保留小巧玲珑感。
|
||||
- 操作：执行前端生产编译构建 `npm run build` 并运行 `node --test web/tests/receipt-folder-view.test.mjs`。
|
||||
- 验证：`npm run build` 构建成功，单元测试通过，`git diff --check` 无输出。
|
||||
- 影响：弹窗彻底摆脱了原本的拥挤挤压感，同时避免了尺度过大、粗糙的问题，整体显得小巧精致、清爽洗练。
|
||||
|
||||
- 13:03：我把 AI 工作台里的“去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交”接成首轮完整申请链路，不再落回一步步追问。
|
||||
- Git 提交检查：`git fetch --all --prune` 已在 Git 写权限升级后成功执行；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮只触碰 AI 工作台申请意图与测试文件。
|
||||
- 修改：`workbenchAiApplicationGateModel.js` 新增 `resolveInlineTravelApplicationRequest()`，识别“出差/差旅/交通 + 具体地点或交通方式”的申请意图，并排除查标准、问制度、查进度等咨询类请求。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 在已有申请表动作之后、报销创建入口之前接入差旅申请识别；命中后直接调用 `startAiApplicationPreview()`，并把同句里的“直接提交”转成 `autoSubmit`。
|
||||
- 修改：`useWorkbenchAiApplicationPreviewFlow.js` 支持申请预览生成后自动提交；只有 `normalizeApplicationPreview(preview).readyToSubmit` 为真时才带 `confirmed: true` 复用现有提交前核查和提交动作，缺日期等必填项时仍停在核对表。
|
||||
- 修改：`workbench-ai-application-gate-model.test.mjs` 和 `expense-application-fast-preview.test.mjs` 增加回归测试，锁定紧凑差旅直提句子的识别、分流和自动提交接线。
|
||||
- 验证：`node --test web/tests/workbench-ai-application-gate-model.test.mjs` 通过 4/4；`node --test --test-name-pattern "direct-submit" web/tests/expense-application-fast-preview.test.mjs` 通过 2/2；`git diff --check -- ...` 无输出；`npm --prefix web run build` 构建通过。
|
||||
- 验证补充：整跑 `node --test web/tests/expense-application-fast-preview.test.mjs` 时，本次新增用例通过，但该文件仍有 12 个既有失败，集中在其它文案/静态结构断言，已单独记录为遗留问题。
|
||||
- 影响：用户把差旅目的地、事由、交通方式和“直接提交”放在一句话里时，AI 工作台会直接生成申请核对表；字段齐全时自动进入提交前核查和提交，不再用多轮问答确认同一件事。
|
||||
|
||||
- 13:20：我先落了 AI 意图规划器文档，再把个人工作台 AI 模式改成“模型计划优先、规则兜底、执行器按步骤执行”的结构。
|
||||
- Git 提交检查：`git fetch --all --prune` 首次被 `.git/FETCH_HEAD` 权限拦截，随后在升级权限下成功执行；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮新增 `AI意图规划器` 文档和 planner 接线。
|
||||
- 修改：新增 `document/development/AI意图规划器/CONCEPT.md` 和 `TODO.md`，明确大模型负责识别动作与步骤，业务执行器负责白名单校验、必填校验、查重和提交。
|
||||
- 修改：新增 `workbenchAiIntentPlannerModel.js`，把后端 `StewardPlanResponse` 或本地 fallback 统一归一为 `intent plan`，计划中包含 `intent`、`requestedAction`、`slots`、`missingFields` 和 `steps`。
|
||||
- 修改：`useWorkbenchAiStewardFlow.js` 增加 `resolveInlineExecutionPlan()`，复用现有 `/steward/plans` 大模型 function calling 能力，返回模型计划；调用失败或超时时由前端 fallback 接管。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 不再直接消费正则识别结果，而是先尝试 steward 模型计划，再用 `buildRuleFallbackWorkbenchAiIntentPlan()` 兜底，最后通过 `resolveExecutableTravelApplicationPlan()` 驱动申请预览和自动提交；模型规划等待期间会锁住发送态，避免重复触发。
|
||||
- 修改：`workbench-ai-intent-planner-model.test.mjs` 增加模型计划归一化、fallback、政策咨询排除和主流程接线测试；`expense-application-fast-preview.test.mjs` 的直提断言同步为 planner 语义。
|
||||
- 验证：`node --test web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs` 通过 8/8；`node --test --test-name-pattern "direct-submit" web/tests/expense-application-fast-preview.test.mjs` 通过 2/2；`npm --prefix web run build` 构建通过；`git diff --check -- ...` 无输出。
|
||||
- 验证补充：整跑 `expense-application-fast-preview.test.mjs` 仍有 12 个既有失败，当前与本次 planner 新增用例无关；本轮未在真实页面输入框回放模型返回路径。
|
||||
- 影响：复杂意图链路现在有了清晰的模型计划适配层；后续扩展报销、附件归集、关联申请单时，可以继续让模型输出 steps，再由确定性执行器逐步执行。
|
||||
|
||||
- 13:35：我补修了 AI 意图规划入口过窄的问题，让“2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。”这种轻微改写也会进入计划执行链路。
|
||||
- Git 提交检查：`git fetch --all --prune` 普通沙箱首次失败，错误是 `.git/FETCH_HEAD: Operation not permitted`；随后在升级权限下成功执行。当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮只继续修改 AI 工作台意图规划、申请预览执行和对应测试。
|
||||
- 修改：`workbenchAiIntentPlannerModel.js` 新增 `shouldRequestWorkbenchAiIntentPlan()`，把差旅、申请、交通方式、保存草稿、直接提交等财务执行候选先送进 steward 计划器；同时新增 `save_application_draft` step，并把 `requestedAction=save_draft` 归一成可执行的 `autoSaveDraft`。
|
||||
- 修改：`workbenchAiApplicationGateModel.js` 放宽本地兜底识别，支持“上海出差”这种目的地前置写法和单独出现的“火车/高铁/飞机”等交通方式。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 不再只在 fallback 已经完整命中时才规划；只要 `shouldRequestWorkbenchAiIntentPlan()` 认为是财务执行候选，就先走模型计划，模型失败才用本地 fallback。
|
||||
- 修改：`useWorkbenchAiApplicationPreviewFlow.js` 在生成申请核对表后支持 `autoSaveDraft`，直接复用现有 `AI_APPLICATION_ACTION_SAVE_DRAFT` 保存草稿动作；自动提交仍只在 `readyToSubmit` 为真时执行。
|
||||
- 验证：`node --test web/tests/workbench-ai-intent-planner-model.test.mjs` 通过 5/5；`node --test --test-name-pattern direct-submit web/tests/expense-application-fast-preview.test.mjs` 通过 2/2；`node --test web/tests/workbench-ai-application-gate-model.test.mjs` 通过 4/4；`npm --prefix web run build` 构建通过；`git diff --check -- ...` 无输出；尾随空白扫描无命中。
|
||||
- 验证补充：用 Node 直接解析用户原句，结果为 `requestedAction=save_draft`，steps 为 `build_application_preview -> validate_required_fields -> save_application_draft`，可执行参数为 `autoSubmit=false`、`autoSaveDraft=true`。
|
||||
- 影响：用户一句话给日期、地点、事由、交通方式和“保存草稿”时，AI 工作台会进入模型规划/兜底规划，生成申请核对表后自动保存草稿，不再因为表述顺序变化回到逐步问答。
|
||||
|
||||
- 13:58：我按用户反馈重构了 AI 工作台意图入口，让用户话语进入后先走大模型 function calling 规划，再按模型拆出的动作和字段执行，规则只保留为模型失败后的降级。
|
||||
- Git 提交检查：`git fetch --all --prune` 普通沙箱首次失败，错误是 `.git/FETCH_HEAD: Operation not permitted`；随后在升级权限下成功执行。当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮继续修改 steward function calling、AI 工作台 planner、申请预览字段接力和测试。
|
||||
- 修改：后端 `StewardTask` 增加 `requested_action`，`StewardIntentAgent` 的 tool schema 要求模型输出 `preview/save_draft/submit`；`StewardModelPlanBuilder` 将模型动作写入任务，缺省时才按原文保守推断。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 将入口从“先构造 fallback 再规划”改成 `executeModelPlannedWorkbenchIntent()`：先调用 `resolveInlineExecutionPlan()`，再把模型 plan 归一为可执行申请；只有模型失败时才执行 `buildRuleFallbackWorkbenchAiIntentPlan()`，并保留模型识别到 reimbursement task 后进入原报销关联门。
|
||||
- 修改：`workbenchAiIntentPlannerModel.js` 保留模型拆出的 canonical ontology fields，`shouldRequestWorkbenchAiIntentPlan()` 改为普通有效输入都先进入 planner，不再把政策查询等话术排除在规划入口外。
|
||||
- 修改：`workbenchAiApplicationPreviewModel.js` 和 `useWorkbenchAiApplicationPreviewFlow.js` 支持把模型拆出的 `time_range/location/reason/transport_mode` 转为申请预览 ontology，再生成核对表，避免继续只靠本地文本解析导致地点和事由粘连。
|
||||
- 测试：先让 `workbench-ai-intent-planner-model.test.mjs` 红灯失败，确认旧实现缺少 `ontologyFields`、政策查询被排除、入口仍携带 `fallbackIntentPlan`；随后实现并跑绿。
|
||||
- 验证：`node --test web/tests/workbench-ai-intent-planner-model.test.mjs` 通过 7/7；`node --test --test-name-pattern direct-submit web/tests/expense-application-fast-preview.test.mjs` 通过 2/2；`node --test web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs` 通过 11/11；容器 `x-financial-local-linux` 内 `pytest -q server/tests/test_steward_intent_agent.py server/tests/test_steward_planner.py` 通过 27/27；容器内 `py_compile` 通过；`npm --prefix web run build` 构建通过；`git diff --check` 无输出，尾随空白扫描无命中。
|
||||
- 验证补充：用 Node 直接归一模型 plan，用户原句输出 `requestedAction=save_draft`、`ontologyFields.time_range=2026-02-20 至 2026-02-23`、`location=上海`、`reason=国网仿生产服务器部署`、`transport_mode=火车`、`autoSaveDraft=true`。
|
||||
- 影响：AI 工作台不会再“瞬间靠规则识别并执行”；可执行链路的第一步是模型 function calling 规划，模型负责拆动作和字段，前端执行器只消费结构化 plan 并调用确定性申请/报销流程。
|
||||
|
||||
- 14:33：我按“每次先经过大模型规划，10s 超时、最多 3 次重试后才规则降级”的要求收紧了 AI 工作台意图规划链路。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮继续修改 steward planner/runtime、申请字段解析、AI 工作台等待时间和相关测试。
|
||||
- 修改：`StewardPlannerService.build_plan()` 改成先调用模型 intent agent，再根据模型结果或失败原因进入 off-topic/rule fallback；不再只对多任务或显式动作走模型。
|
||||
- 修改：`StewardIntentAgent` 的 function calling 调用改为 `timeout_seconds=10`、`max_attempts=3`，并通过 `RuntimeChatService.complete_with_tool_call(use_failure_cooldown=False)` 避免第 1 次失败后第 2、3 次被 cooldown 跳过。
|
||||
- 修改：`useWorkbenchAiStewardFlow.js` 将 inline execution plan 等待时间从 12s 调到 35s，覆盖后端 3 次 10s 模型等待，避免前端提前本地 fallback。
|
||||
- 修改：`ApplicationFactResolver` 和 `StewardPlannerExtractionMixin` 的规则降级补齐 `requested_action`、完整日期范围和申请事由清洗；即使模型 3 次超时，也能把“保存草稿”“2026-02-20 至 2026-02-23”“国网仿生产服务器部署”“火车”传给执行器。
|
||||
- 测试：先新增红灯测试覆盖“单一出差描述也要先调用模型”“模型调用参数为 10s/3 次”“tool-call 规划可关闭 cooldown 连续重试”“前端等待 35s”“规则降级保留保存草稿和日期范围”，随后实现并跑绿。
|
||||
- 验证：容器内 `pytest -q server/tests/test_runtime_chat_service.py server/tests/test_steward_intent_agent.py server/tests/test_steward_planner.py` 通过 38/38；前端 `node --test web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs` 通过 11/11；`npm --prefix web run build` 通过；`git diff --check -- ...` 无输出。
|
||||
- 真实接口验证：重启 `x-financial-local-linux` 后直接请求 5173 的 `/api/v1/steward/plans`，原句耗时 32.08s，MiniMax `attempt=1/2/3` 均约 10.2s 超时后才返回 `planning_source=rule_fallback`；返回任务已包含 `requested_action=save_draft`、完整 `time_range=2026-02-20 至 2026-02-23`、`location=上海`、`reason=国网仿生产服务器部署`、`transport_mode=train`。
|
||||
- 影响：用户不会再看到毫秒级规则直出；当前模型服务超时时会先完整等待三次，再用可执行的基础规则计划继续流程。
|
||||
|
||||
- 15:14：我把小财管家规划入口第一阶段迁到 LangGraph，默认用框架接管规划编排，同时保留 legacy 回退。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮新增 LangGraph 依赖、graph planner、runtime 开关和测试。
|
||||
- 修改：新增 `StewardGraphPlannerService`，用 LangGraph `StateGraph` 编排 `prepare_context -> detect_model_intent -> off_topic/rule_fallback/完成`，不再把规划主流程继续写在一个手工 `if/else` 方法里。
|
||||
- 修改：`/steward/plans` 和 `/steward/plans/stream` 的 planner 工厂默认返回 `StewardGraphPlannerService`；`STEWARD_AGENT_RUNTIME=legacy` 可回退到旧 `StewardPlannerService`。
|
||||
- 修改：`server/pyproject.toml`、`server/uv.lock` 和 `egg-info` 同步加入 `langgraph>=1.2,<2.0`；`.env.example` 增加 `STEWARD_AGENT_RUNTIME=langgraph`。
|
||||
- 测试：先新增 `test_steward_graph_planner.py` 红灯测试，覆盖 LangGraph planner 的模型成功路径、模型无 tool call 后规则降级、默认 LangGraph、显式启用 LangGraph 和 legacy 回退；随后实现并跑绿。
|
||||
- 验证：容器内 `pytest -q server/tests/test_steward_graph_planner.py server/tests/test_steward_planner.py server/tests/test_steward_intent_agent.py server/tests/test_runtime_chat_service.py server/tests/test_config_settings_reload.py` 通过 45/45；`ruff check --ignore E501 ...` 通过；`git diff --check` 无输出；`pip check` 无 broken requirements。
|
||||
- 真实接口验证：通过真实 5173 `/api/v1/steward/plans` 回放保存草稿原句，服务端仍先等待 MiniMax 3 次 10s 超时，再返回 `rule_fallback`；返回字段包含 `requested_action=save_draft`、完整日期范围、上海、事由和 `transport_mode=train`。容器内直接探针确认默认 planner 类型为 `StewardGraphPlannerService`。
|
||||
- 影响：小财管家的规划骨架已经由 LangGraph 承接；后续可以继续把 slot/runtime decision、checkpoint 记忆、human-in-the-loop 和 action node 迁到框架里，而不是继续扩写自研分支编排。
|
||||
|
||||
- 15:22：我按“先落文档，文档完了再继续开发”的要求补齐 LangGraph 后续迁移文档。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮只修改 AI 意图规划器文档和当天工作日志。
|
||||
- 修改：新增 `LANGGRAPH_RUNTIME_MIGRATION.md`，记录当前已完成的 LangGraph 第一阶段、目标架构、runtime state 草案、节点边界、Phase 1-5 迁移计划、回退策略、验证矩阵和风险处理。
|
||||
- 修改：更新 `CONCEPT.md`，删除“非目标：不新增 LangGraph”的过期表述，改为不引入 LangChain 高层 Agent、不让 LangGraph 直接接管密钥或副作用，并补充后续 node 迁移方向。
|
||||
- 修改：更新 `TODO.md`，把 `requested_action`、LangGraph 接入和迁移文档标为完成，并新增模型成功路径、slot/runtime node、action node、checkpoint、人审中断和 trace 的后续事项。
|
||||
- 操作：查询 LangGraph 官方文档，确认 Graph API、persistence 和 interrupt 的能力边界；读取当前 `StewardGraphPlannerService` 与已有 AI 意图规划文档后再落文档。
|
||||
- 验证：`rg` 确认旧“不能新增 LangGraph”说法没有残留；`git diff --check -- document/development/AI意图规划器/...` 无输出；新增迁移文档 356 行。
|
||||
- 影响：后续开发有了明确的执行顺序和验收标准；下一步应先按文档 Phase 1 修通真实 `llm_function_call` 成功路径，再迁 slot/runtime/action/checkpoint。
|
||||
|
||||
- 15:31：我继续把小财管家会话内的槽位识别、运行时记忆合并和行动决策入口迁到 LangGraph，并加了图内和端点级双层兜底。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮新增 graph runtime、runtime 测试并更新 AI 意图规划器文档。
|
||||
- 修改：新增 `StewardGraphRuntime`，用 LangGraph `StateGraph` 编排 `slot_prepare_context -> slot_tool_decision -> done/rule_fallback`，把原 `StewardSlotDecisionAgent` 包成图节点；工具节点异常时会带 `langgraph_slot_decision` 失败 trace 进入规则兜底。
|
||||
- 修改：`StewardGraphRuntime` 运行时图新增 `runtime_memory_context -> runtime_action_decision/runtime_tool_decision -> done/rule_fallback`，先归一化并合并 `steward_state`，已选流程确认走确定性 action 节点，不再调用模型；普通补字段/确认继续由 runtime tool 节点判断。
|
||||
- 修改：`/steward/slot-decisions` 和 `/steward/runtime-decisions` 默认使用 `StewardGraphRuntime`；如果 LangGraph 实例化或执行异常，端点 helper 会退回旧 `StewardSlotDecisionAgent` / `StewardRuntimeDecisionAgent`，保证框架失效时仍能实际响应。
|
||||
- 测试：先新增 `test_steward_graph_runtime.py` 红灯测试，覆盖槽位工具节点、图内规则兜底、运行时记忆合并、确定性行动选择，以及端点 helper 在 graph runtime 失败后 legacy 兜底；随后实现并跑绿。
|
||||
- 文档：更新 `LANGGRAPH_RUNTIME_MIGRATION.md` 的当前状态和 Phase 2 完成项；更新 `CONCEPT.md` 的 LangGraph 节点命名；更新 `TODO.md` 勾掉 slot/runtime graph runtime 迁移，保留副作用 action node、checkpoint、人审中断和 trace 后续事项。
|
||||
- 验证：容器内 `pytest -q server/tests/test_steward_graph_runtime.py server/tests/test_steward_graph_planner.py server/tests/test_steward_slot_decision_agent.py server/tests/test_steward_runtime_decision_agent.py server/tests/test_steward_planner.py server/tests/test_steward_intent_agent.py server/tests/test_runtime_chat_service.py server/tests/test_config_settings_reload.py` 通过 59/59；`ruff check --ignore E501 ...` 通过；`git diff --check` 无输出；`pip check` 无 broken requirements。
|
||||
- 影响：会话内“识别缺什么、读记忆、判断补字段/继续/确认”的入口已经被 LangGraph 接管；当前仍没有让 LangGraph 直接执行保存草稿、提交审批、关联申请单等副作用动作。
|
||||
|
||||
- 15:53：我把 `/steward/plans` 的基础业务动作规划补成服务端白名单 `action_steps`，让申请、报销、保存草稿和直接提交都有明确动作序列。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮新增 action contract、扩展 steward schema、更新前端 planner model、修复申请事由清洗并同步文档。
|
||||
- 修改：`StewardTask` 和 `StewardPlanResponse` 增加 `action_steps`；新增 `StewardActionStep`、`StewardActionType`、`StewardActionStatus`，把可执行动作显式收进 Pydantic 协议。
|
||||
- 修改：新增 `StewardActionPlanBuilder`，由服务端确定性生成白名单动作：申请直接提交输出 `fill_application_fields -> build_application_preview -> validate_required_fields -> run_duplicate_precheck -> submit_application`；保存草稿输出 `save_application_draft`；报销输出 `fill_reimbursement_fields -> build_reimbursement_preview -> validate_required_fields -> create_reimbursement_draft`。
|
||||
- 修改：`StewardGraphPlannerService` 增加 `attach_action_steps` 节点，模型成功、模型失败兜底和 off-topic 都统一经过动作规划节点；legacy `StewardPlannerService` 返回前也补同一套 action contract。
|
||||
- 修改：`workbenchAiIntentPlannerModel.js` 优先消费服务端 `task.action_steps`，旧响应才回退本地 `requested_action` 推导；这样后端 LangGraph 规划出的动作能真正驱动前端执行计划。
|
||||
- 修改：`ApplicationFactResolver` 修复“交通火车”污染申请事由的问题，同时保留“高铁往返”这类业务描述；新增解析回归测试。
|
||||
- 测试：先新增红灯测试，覆盖申请直接提交 action steps、保存草稿 action steps、报销 action steps、前端优先消费服务端 action steps、`交通火车` 事由清洗；随后实现并跑绿。
|
||||
- 验证：容器内 `pytest -q server/tests/test_application_fact_resolver.py server/tests/test_steward_graph_runtime.py server/tests/test_steward_graph_planner.py server/tests/test_steward_slot_decision_agent.py server/tests/test_steward_runtime_decision_agent.py server/tests/test_steward_planner.py server/tests/test_steward_intent_agent.py server/tests/test_runtime_chat_service.py server/tests/test_config_settings_reload.py` 通过 66/66；前端 `node --test web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs` 通过 12/12；`npm --prefix web run build` 通过；`ruff check --ignore E501 ...` 通过；`git diff --check` 无输出。
|
||||
- 真实接口验证：重启 `x-financial-local-linux` 后回放 `2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交`，真实 5173 `/api/v1/steward/plans` 返回 `requested_action=submit`，字段为 `time_range=2026-02-20 至 2026-02-23`、`location=上海`、`reason=辅助国网仿生产服务器部署`、`transport_mode=train`，动作序列为 `detect_intent:completed -> fill_application_fields:planned -> build_application_preview:planned -> validate_required_fields:planned -> run_duplicate_precheck:planned -> submit_application:pending_confirmation`。
|
||||
- 影响：基础业务已经不是“只识别一个 requested_action”了，后端计划会直接给出可执行动作序列；当前仍只规划动作，不直接执行保存草稿或提交审批。
|
||||
|
||||
- 16:13：我把小财管家的白名单 action 从“只规划”推进到“可执行 executor”，让申请草稿、申请提交门禁和报销草稿能通过统一 `/steward/actions/execute` 入口处理。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮新增 action executor、执行接口、前端执行服务和相关测试。
|
||||
- 修改：新增 `StewardActionExecuteRequest` / `StewardActionExecuteResponse`，并在 `steward.py` 暴露 `/steward/actions/execute`；新增 `StewardActionExecutor`，统一处理未知 action 拒绝、缺字段阻断、提交确认门禁、precheck 阻断和业务服务调用。
|
||||
- 修改：`save_application_draft` / `submit_application` 复用现有 `UserAgentService` 申请保存/提交能力；`create_reimbursement_draft` 复用 `ExpenseClaimService.save_or_submit_from_ontology()`，避免再写一套入库逻辑。
|
||||
- 修改：`associate_attachments` 和 `link_existing_application` 保留在执行白名单里，但在真实接线完成前统一返回阻断，不允许以 noop 形式“假成功”或产生隐式副作用。
|
||||
- 修改：前端 `steward.js` 新增 `executeStewardAction()`；`stewardPlanModel.js` 保留服务端 `action_steps`，并在 suggested action payload 中携带最终可执行 action step，旧申请预览流继续保留为兜底。
|
||||
- 修改：`useWorkbenchAiActionRouter.js` 接入 `steward_execute_action` 点击执行；申请直接提交会先调用 `run_duplicate_precheck`，precheck 通过后再把结果交给 `submit_application`，执行结果回写到当前 AI 会话。
|
||||
- 修改：`test_reimbursement_endpoints.py` 两个申请快路径断言从旧 `AP-` 前缀同步到当前短单号 `A...` 规范。
|
||||
- 文档：更新 `LANGGRAPH_RUNTIME_MIGRATION.md`、`TODO.md`、`CONCEPT.md`，标记第一版 action registry / executor 完成，并把 checkpoint、interrupt、关联申请和附件真实执行列为后续。
|
||||
- 验证：容器内 `pytest -q server/tests/test_steward_action_executor.py` 通过 5/5；迁移集合 `pytest -q server/tests/test_application_fact_resolver.py server/tests/test_steward_action_executor.py server/tests/test_steward_graph_runtime.py server/tests/test_steward_graph_planner.py server/tests/test_steward_slot_decision_agent.py server/tests/test_steward_runtime_decision_agent.py server/tests/test_steward_planner.py server/tests/test_steward_intent_agent.py server/tests/test_runtime_chat_service.py server/tests/test_config_settings_reload.py` 通过 71/71。
|
||||
- 验证：前端 `node --test web/tests/workbench-ai-action-router.test.mjs web/tests/steward-actions-service.test.mjs web/tests/steward-plan-message-copy.test.mjs web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs` 通过 21/21；`npm --prefix web run build` 通过；`ruff check --ignore E501 ...` 通过；`git diff --check` 无输出。
|
||||
- 真实接口验证：重启 `x-financial-local-linux` 后，真实 5173 `/api/v1/steward/plans` 仍返回直接提交 action 链；`/api/v1/steward/actions/execute` 对未确认的 `submit_application` 返回 `needs_confirmation`，没有执行入库副作用。
|
||||
- 影响：基础业务链路已经具备“规划 action -> 执行器门禁 -> 复用现有业务服务”的后端闭环；下一步需要把 executor 包进 LangGraph checkpoint / interrupt，并补齐关联申请和附件关联的真实执行。
|
||||
|
||||
- 16:40：我把 action executor 包成 LangGraph 可执行节点，并补完 checkpoint、人工确认中断、幂等重放、关联申请单和附件关联三阶段收尾。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮新增 `StewardGraphActionRuntime`，扩展 action executor 测试并更新 AI 意图规划器文档。
|
||||
- 修改：新增 `StewardGraphActionRuntime`，用 LangGraph `StateGraph` 编排 `action_checkpoint_load -> action_execute_node -> action_checkpoint_persist`，并把 `/steward/actions/execute` 默认切到这个 graph runtime。
|
||||
- 修改：复用 `AgentConversation.state_json` 持久化 `steward_action_checkpoint`；同一 `conversation_id + client_trace_id` 的已完成 action 会直接重放终态结果，`needs_confirmation` 会保存 pending interrupt，后续同 trace 完成后清理对应中断。
|
||||
- 修改：`link_existing_application` 走报销草稿真实创建链路并写入申请关联风险标记；`associate_attachments` 接入 `AttachmentAssociationJobRunner`，无 `receipt_ids` 时阻断，避免假成功。
|
||||
- 修改：为 `complete_with_tool_call()` 补上主模型失败后 backup 返回 tool call 的回归测试，锁住“模型规划失败优先重试/切 backup，再降级规则”的成功路径。
|
||||
- 文档：更新 `LANGGRAPH_RUNTIME_MIGRATION.md`、`TODO.md`、`CONCEPT.md`，把 action node、checkpoint、pending interrupt、幂等重放、关联申请单和附件关联标为已完成，同时保留真实模型配置未修通的验收缺口。
|
||||
- 验证：容器内 `pytest -q server/tests/test_steward_action_executor.py` 通过 9/9；`pytest -q server/tests/test_runtime_chat_service.py::test_runtime_chat_complete_with_tool_call_fails_over_to_backup_before_retrying_main` 通过 1/1。
|
||||
- 验证：迁移集合 `pytest -q server/tests/test_application_fact_resolver.py server/tests/test_steward_action_executor.py server/tests/test_steward_graph_runtime.py server/tests/test_steward_graph_planner.py server/tests/test_steward_slot_decision_agent.py server/tests/test_steward_runtime_decision_agent.py server/tests/test_steward_planner.py server/tests/test_steward_intent_agent.py server/tests/test_runtime_chat_service.py server/tests/test_config_settings_reload.py` 通过 76/76；附件/关联任务 `pytest -q server/tests/test_attachment_association_jobs.py server/tests/test_linked_reimbursement_draft_jobs.py` 通过 7/7。
|
||||
- 验证：前端 `node --test web/tests/workbench-ai-action-router.test.mjs web/tests/steward-actions-service.test.mjs web/tests/steward-plan-message-copy.test.mjs web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs` 通过 21/21；`ruff check --ignore E501 ...` 通过；`npm --prefix web run build` 通过；`git diff --check` 无输出。
|
||||
- 真实接口验证：重启 `x-financial-local-linux` 后，真实 5173 `/steward/actions/execute` 对同一未确认 `submit_application` trace 第二次返回 `needs_confirmation` 且 `result_payload.idempotent_replay=true`，证明 checkpoint 重放生效。
|
||||
- 真实接口验证：真实 5173 `/steward/plans` 回放“2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿”仍因 backup skipped、MiniMax 三次失败后进入 `rule_fallback`，动作链和字段可用，但 `planning_source=llm_function_call` 仍需修模型配置。
|
||||
- 影响：申请、报销、保存草稿、直接提交、关联申请单、附件关联已经具备“LangGraph 规划/行动节点 -> 业务服务执行 -> checkpoint/interrupt 兜底”的基础可测闭环；真实大模型成功路径还差外部模型连通性。
|
||||
|
||||
- 16:53：我修复 AI 模式输入后按回车“看起来没响应”的问题，把模型规划等待期改成先显示对话反馈。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮只改 AI 模式前端等待反馈和对应测试/日志。
|
||||
- 根因：`executeModelPlannedWorkbenchIntent()` 在等待 `/steward/plans` 返回前只设置 `sending=true`，没有先激活对话、清空输入框、展示用户气泡或 pending 卡片；真实 MiniMax 三次超时会让用户看到 30 多秒“无响应”。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 新增 `startModelPlanningConversation()`，进入模型规划前立即推入用户消息和“正在识别意图，准备拆解申请、报销和附件任务。”的 pending 卡片，并持久化到最近对话。
|
||||
- 修改：`startModelPlannedApplicationPreview()` 把规划 pending 的 `pendingMessageId` 传给申请预览；`useWorkbenchAiApplicationPreviewFlow.js` 支持复用这张 pending 卡片，避免重复用户消息和重复等待卡。
|
||||
- 测试：先新增 `workbench AI mode shows a visible planning response before waiting for steward model plan` 红灯测试，确认当前缺少即时反馈；实现后同文件 9/9 通过。
|
||||
- 验证：前端相关集合 `node --test web/tests/workbench-ai-action-router.test.mjs web/tests/steward-actions-service.test.mjs web/tests/steward-plan-message-copy.test.mjs web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs web/tests/workbench-ai-composer-components.test.mjs` 通过 31/31；`npm --prefix web run build` 通过；`git diff --check` 无输出。
|
||||
- 真页验证：使用本地 5173 和本地模拟员工账号登录 AI 模式，输入“2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿”并按回车；1.5 秒内看到用户气泡、输入框清空和 pending 卡片；约 38 秒后仍正常保存草稿，草稿单号 `AZ8QSX9QA`。
|
||||
- 影响：用户按回车后不再空等模型规划，长耗时仍存在但前端会立即反馈“已接收并正在规划”；真实 `llm_function_call` 成功路径仍依赖模型配置修复。
|
||||
|
||||
- 16:59：我修复了 AI 模式普通问候被拆成两条助手消息的问题，把规划、工具/行动整理和最终回复收敛到同一张助手卡片。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮只继续修改 AI 模式前端消息复用、思考事件合并和对应测试。
|
||||
- 根因：16:53 的等待态修复先创建了模型规划 pending 卡片，但普通管家回复路径会把这张卡片替换成“已完成意图识别，继续为您整理回复。”，随后 `requestInlineAssistantReply()` 又新建第二张助手卡片；所以用户输入“你好”时会看到两段会话。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 删除中间态独立回复，普通管家回复也把 `pendingMessageId` 传给 `requestInlineAssistantReply()`，让同一轮输入继续复用规划 pending 卡片。
|
||||
- 修改：`useWorkbenchAiStewardFlow.js` 支持 `requestInlineAssistantReply(prompt, entry, files, options)`，当传入 `pendingMessageId` 时替换原 pending 卡片而不是追加新消息；新增 `mergeInlineThinkingEvents()` 合并模型规划和管家回复思考事件，避免同一事件重复或丢失。
|
||||
- 测试：先新增红灯测试 `workbench AI mode reuses planning pending message for regular steward replies`，确认普通回复必须复用规划 pending；实现后同文件 10/10 通过。
|
||||
- 验证：前端集合 `node --test web/tests/workbench-ai-action-router.test.mjs web/tests/steward-actions-service.test.mjs web/tests/steward-plan-message-copy.test.mjs web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs web/tests/workbench-ai-composer-components.test.mjs` 通过 32/32；`npm --prefix web run build` 通过；`git diff --check` 无输出。
|
||||
- 真页验证：本地 5173 AI 模式输入“你好”后，1.5 秒内只有 1 张 pending 助手卡；最终回复后 `assistantCardCount=1`、`pendingCards=0`、思考区标题为“小财业务思考5 条”，截图保存为 `/tmp/x-financial-ai-single-message-hello.png`。
|
||||
- 影响：一次用户输入现在对应一条助手消息；意图识别、规划等待、普通回复整理都会落在同一个思考区域，不再把“已完成意图识别”单独展示成一轮会话。
|
||||
|
||||
- 17:26：我把 AI 模式的规划等待态从静态“思考中”改成持续追加过程摘要，让用户能看到意图判断、字段抽取、动作规划和兜底策略正在推进。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有多项既有未提交改动，本轮只继续修改 AI 模式前端 thinking 事件、流式规划接线和对应测试。
|
||||
- 根因：`executeModelPlannedWorkbenchIntent()` 虽然会先创建 pending 卡片，但 `resolveInlineExecutionPlan()` 仍走非流式 `/steward/plans`，模型等待期间只有一条静态 thinking；等计划返回后才一次性显示完整步骤，用户会感觉像假思考。
|
||||
- 修改：新增 `workbenchAiPlanningThinkingModel.js`，集中维护可复用的 thinking 事件合并、完成态转换、初始意图判断和阶段性进度计划，避免继续把主 composable 写大。
|
||||
- 修改：`usePersonalWorkbenchAiMode.js` 在模型规划 pending 卡片上启动可取消的阶段性进度：判断办理意图、抽取关键信息、规划执行步骤、匹配业务工具、准备兜底策略；模型返回或进入 fallback 后会清理定时器。
|
||||
- 修改：`useWorkbenchAiStewardFlow.js` 支持 `resolveInlineExecutionPlan(prompt, entry, files, { pendingMessageId })`；传入 pending id 时改走 `/steward/plans/stream`，只把服务端 thinking 实时写回当前卡片，不把 answer delta 提前塞进规划消息。
|
||||
- 修改：`useWorkbenchAiApplicationPreviewFlow.js` 生成申请核对表时保留并完成前置规划 thinking，再追加“整理申请表字段 / 同步费用测算”，避免申请表阶段把前面的规划过程清掉。
|
||||
- 测试：新增 `workbench AI mode streams planning thinking into the pending message`，锁定阶段性 thinking、可取消定时器、流式规划接线和申请预览 thinking 合并；同文件 11/11 通过。
|
||||
- 验证：相关前端集合 `node --test web/tests/workbench-ai-action-router.test.mjs web/tests/steward-actions-service.test.mjs web/tests/steward-plan-message-copy.test.mjs web/tests/workbench-ai-intent-planner-model.test.mjs web/tests/workbench-ai-application-gate-model.test.mjs web/tests/workbench-ai-composer-components.test.mjs` 通过 33/33；`npm --prefix web run build` 通过；`git diff --check` 无输出。
|
||||
- 真页验证：本地 5173 干净会话输入“2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。”后，thinking 数量按时间增长：点击后 2 条、1.1 秒 3 条、2.5 秒 4 条、5.7 秒 5 条、9.6 秒 6 条；约 36 秒后仍成功保存草稿，草稿单号 `AZ4A98BSF`，截图保存为 `/tmp/x-financial-ai-progressive-thinking.png`。
|
||||
- 验证补充：我额外跑了 `workbench-ai-mode-switch.test.mjs`，该文件仍有 2 个既有静态断言失败，断言点还停在旧的内联附件卡片和旧的 `selectedFiles` watch 结构；本轮相关测试和真页回放不受影响。
|
||||
- 影响：用户现在不再只看到静态“思考中”，而是能在同一张思考卡片里持续看到业务意图、槽位、动作链和兜底策略的推进过程；服务端流式 thinking 到达后也会合并进同一个列表。
|
||||
|
||||
- 17:40：我修复了 AI 工作台保存申请草稿后，再输入“提交这个单据”会重新进入意图规划的问题。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有大量既有未提交改动，本轮只补 AI 工作台申请上下文提交识别、申请预览执行分支和对应测试。
|
||||
- 根因：`resolveInlineApplicationPreviewTextAction()` 只识别“提交 / 确认提交 / 直接提交”等精确词，用户输入“提交这个单据”会绕过当前申请核对表上下文，继续进入 `shouldRequestWorkbenchAiIntentPlan()` 和小财管家规划，导致再次识别意图并等待模型。
|
||||
- 修改：`workbenchAiApplicationGateModel.js` 把“提交这个单据 / 提交这个申请单 / 提交当前单据 / 提交刚才的草稿”等上下文指代短句映射为 `AI_APPLICATION_ACTION_SUBMIT`；同类保存指代短句也映射到保存草稿动作。
|
||||
- 修改：`useWorkbenchAiApplicationPreviewFlow.js` 在提交动作里新增“已保存草稿 + 上下文提交短句”快路径；当最近申请核对表已有 `draftPayload.claim_id` 或单号，且用户明确说提交当前/刚才的单据时，跳过二次确认弹窗，直接执行提交前核查和 `/reimbursements/application-preview-action`，并带上 `application_edit_claim_id` 复用原草稿。
|
||||
- 测试：先新增 `workbench-ai-application-context-submit.test.mjs` 红灯测试，复现“已有草稿 + 提交这个单据”只打开确认弹窗、不调用提交接口；实现后该测试通过，并确认 payload 写入 `application_edit_claim_id=claim-saved-draft`。
|
||||
- 验证：`node --test web/tests/workbench-ai-application-context-submit.test.mjs` 通过；`node --test web/tests/workbench-ai-application-gate-model.test.mjs` 通过；相邻 `workbench-ai-action-router.test.mjs`、`workbench-ai-intent-planner-model.test.mjs`、`ai-application-preview-actions.test.mjs` 均通过；本轮改动文件 `git diff --check -- ...` 无输出。
|
||||
- 验证补充：`workbench-ai-mode-expense-scene-action.test.mjs` 和 `expense-application-fast-preview.test.mjs` 仍有既有静态断言失败，主要还在扫描旧 `PersonalWorkbenchAiMode.vue` 或过窄源码片段；新增的上下文提交行为测试已覆盖真实执行路径。
|
||||
- 影响：用户先说“2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，保存草稿”，草稿保存后再说“提交这个单据”，前端不会再重新规划，而会把“这个单据”绑定到最近申请草稿并提交到审批链路。
|
||||
|
||||
- 17:48：我修复了“完整出差信息但未显式说申请/报销”时，AI 模式停在候选流程确认、不直接推进申请预览的问题。
|
||||
- Git 提交检查：`git fetch --all --prune` 成功；当前 upstream 为 `origin/main`，`HEAD..@{u}` 与 `@{u}..HEAD` 均未输出新提交；工作区仍有大量既有未提交改动，本轮只继续修改 `workbenchAiIntentPlannerModel.js` 和对应意图规划测试。
|
||||
- 根因：后端已经返回 `pending_flow_confirmation`，且候选流只有 `travel_application / 先发起出差申请`，但前端 `normalizeWorkbenchAiIntentPlan()` 只识别 `tasks`，没有把这个唯一候选流转成可执行申请计划，最后又回到普通 steward 回复路径。
|
||||
- 修改：`workbenchAiIntentPlannerModel.js` 增加 pending flow 候选解析；当 `pending_flow_confirmation.status=pending` 且唯一候选为“先发起出差申请”时，直接生成 `create_travel_application` 计划，包含 `build_application_preview`、必填校验、模型抽取的时间/地点/事由/交通方式。
|
||||
- 测试：先新增红灯用例 `workbench AI intent planner turns single application candidate flow into executable preview payload`，复现该计划原本返回 `null`；实现后同文件 12/12 通过。
|
||||
- 验证：`node --test web/tests/workbench-ai-intent-planner-model.test.mjs`、`node --test web/tests/workbench-ai-application-gate-model.test.mjs`、`node --test web/tests/workbench-ai-application-context-submit.test.mjs`、`node --test web/tests/steward-plan-model-pending-flow.test.mjs` 均通过；`git diff --check -- web/src/composables/workbenchAiMode/workbenchAiIntentPlannerModel.js web/tests/workbench-ai-intent-planner-model.test.mjs` 无输出。
|
||||
- 影响：用户输入“2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车”时，如果门禁已查明没有可关联申请单，前端会把“应先申请单据”直接落到申请预览链路，不再表现成只会反复识别意图。
|
||||
|
||||
## 遗留问题
|
||||
|
||||
- 09:41：当前 Skill 是新建在项目级 `.codex/skills` 目录里，本轮可以通过文件检查验证结构，但是否被未来会话自动加载还依赖 Codex 对项目 Skill 的刷新机制。建议后续新开会话或下一次任务时确认 Skill 列表是否出现 `agent-change-log`。
|
||||
@@ -236,6 +418,26 @@
|
||||
- 11:39：本轮新增的附件归集回归测试还没有在容器内真正执行，原因仍是 Docker socket 权限拒绝。建议 Docker 权限恢复后优先运行 `server/tests/test_attachment_association_jobs.py` 新增两条测试，并在 5173 重新打开刚才那张坏票据验证自动修复是否生效。
|
||||
- 11:55：当前实际运行容器仍叫 `x-financial-local-linux`，且容器内 `poppler-data` 未安装、`mutool` 不存在；本轮文本层兜底已恢复 OCR 字段，但 PDF 图片预览仍会带转图失败 warning。12:04 已在当前运行容器补齐依赖并刷新本批票据预览；建议后续仍按最新 compose 统一到 `local-x-financial-linux`，避免旧容器继续抢占 5173。
|
||||
- 12:23：本轮没有拿到可用的浏览器自动化插件来生成真页截图，已用前端构建、组件测试和真实 5173 OCR/preview 接口替代验证。建议用户侧刷新页面后重新上传同类 PDF，若历史会话里旧附件卡片仍停留在旧状态，则重新选择附件触发 OCR 状态刷新。
|
||||
- 13:03：`expense-application-fast-preview.test.mjs` 整文件仍有 12 个既有失败，失败点包括 unsupported business guidance 文案、旧申请 session 静态结构、typewriter/table 静态断言等；本次新增的直提申请用例已通过。建议后续单独清理这些陈旧断言，避免掩盖真正的申请链路回归。
|
||||
- 13:20：本轮完成了模型计划接线和结构测试，但没有在真实 5173 页面输入框回放 `/steward/plans` 返回 `llm_function_call` 的端到端路径。建议后续用真实模型配置测试一次“去上海出差...直接提交”，确认模型返回任务计划后前端进入申请核对表。
|
||||
- 13:35：本轮已经用模型规划入口、fallback 解析和前端构建验证了“保存草稿”变体，但还没有在真实 5173 输入框回放一次完整点击/保存草稿链路。建议后续用当前句子做真页验证，确认草稿保存后出现申请单详情入口。
|
||||
- 13:58：本轮已经用容器后端测试和前端模型计划归一测试验证 function calling contract，但还没有在真实 5173 页面观察 `/steward/plans` 的网络返回是否包含新的 `requested_action`。建议后续打开浏览器 DevTools 或后端日志，用真实模型配置回放一次保存草稿话术。
|
||||
- 14:33：真实接口已确认模型必经和 3 次重试，但当前主模型 MiniMax 连续超时，backup 槽位 API key 未解密/未配置，因此仍然进入 `rule_fallback`。建议下一步先修复模型连通性或配置可用 backup，再确认返回 `planning_source=llm_function_call` 的成功路径。
|
||||
- 14:33：用户提出 LangChain 方向是合理的，但本轮没有直接引入新依赖。15:14 已完成 LangGraph 第一阶段迁移；后续仍要继续补 memory/checkpoint、action node 和人审中断能力。
|
||||
- 15:14：LangGraph 第一阶段只替换了 `/steward/plans` 的规划编排骨架，还没有把 slot decision、runtime decision、草稿保存/提交 action 和跨轮 checkpoint 迁入 graph。建议下一步按节点边界继续拆迁，避免又在 LangGraph node 内写回大块自研流程。
|
||||
- 15:14：`langgraph` 依赖把 `websockets` 锁到 15.0.1；当前 `pip check` 和 steward 相关测试通过，但如果后续实时流或 WebSocket 功能异常，需要优先核对这个依赖变化。
|
||||
- 15:22：本轮只补迁移文档，没有继续实现 Phase 1-5。建议下一轮严格按 `LANGGRAPH_RUNTIME_MIGRATION.md` 从模型成功路径开始推进，不要跳过文档直接扩写 graph node。
|
||||
- 15:31：当前 `StewardGraphRuntime` 已覆盖 slot/runtime decision，但保存草稿、提交审批、关联申请单等副作用动作还只是下游既有服务执行，并未接成 LangGraph 白名单 action node。建议下一步优先实现 `steward_action_nodes.py` / action contract，再接 checkpoint 和 human-in-the-loop。
|
||||
- 15:53：当前已完成服务端 action contract，但还没有实现真正执行副作用的 action registry / action node；`save_application_draft`、`submit_application`、`create_reimbursement_draft` 仍需要下一步接到现有业务服务并补幂等、确认来源和 trace。建议下一步先做 action registry，再接 checkpoint/human-in-the-loop。
|
||||
- 16:13：第一版 action executor 和 AI 工作台点击执行闭环已可执行申请/报销基础副作用，但还没有接入 LangGraph checkpoint / interrupt，也没有给所有副作用写持久化幂等 trace。16:40 已完成后端 action graph runtime、pending interrupt 和幂等重放，剩余前端恢复 UI 还需单独做。
|
||||
- 16:13：`link_existing_application` 和 `associate_attachments` 已进入执行白名单并在未接线时阻断，但真实执行还没有统一接入 action executor。16:40 已接入真实执行和回归测试，后续仍需在真页补充可视化恢复/继续动作。
|
||||
- 16:40：真实 `/steward/plans` 仍未跑到 `planning_source=llm_function_call`，当前阻塞点是 backup skipped、MiniMax 三次失败；代码层 backup tool-call 成功路径已有测试，但环境层还要修模型配置或连通性。
|
||||
- 16:40：后端已把 pending interrupt 写进 conversation checkpoint，但 AI 工作台还没有在刷新或重新进入会话时从 checkpoint 主动恢复“继续/确认”按钮；建议下一步补前端恢复 UI。
|
||||
- 16:53：`usePersonalWorkbenchAiMode.js` 当前已超过 800 行，后续继续加 AI 模式功能前建议拆出模型规划等待态、普通对话启动和申请预览桥接 composable，避免继续扩大主运行时文件。
|
||||
- 16:59：本轮没有新增独立遗留风险；仍沿用 16:40 的真实模型连通性问题和 16:53 的主 composable 过大问题。建议后续先修 `llm_function_call` 成功路径，再拆分 AI 模式前端运行时文件。
|
||||
- 17:26：`workbench-ai-mode-switch.test.mjs` 仍有 2 个旧静态断言失败，分别断言附件卡片还在主模板内联、`selectedFiles` watch 还在主 AI 模式文件里；当前真实代码已经拆成组件/composable。建议后续单独整理这个老测试文件，避免它继续误报已迁移结构。
|
||||
- 17:40：`workbench-ai-mode-expense-scene-action.test.mjs` 和 `expense-application-fast-preview.test.mjs` 仍有多条旧静态断言失败，失败点主要是代码已拆到 composable 后测试还读取旧 Vue 单文件或固定片段。建议后续把这些静态断言改成导入 composable/model 的行为测试，避免真实功能修复被旧结构误报淹没。
|
||||
- 17:48：本轮修复已用模型归一化和相邻前端测试覆盖，但还没有在真实 5173 页面输入最新无动作话术截图回放。建议下一步刷新 AI 工作台，用“2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车”验证是否直接进入申请核对表。
|
||||
|
||||
## TODO
|
||||
|
||||
@@ -264,3 +466,28 @@
|
||||
- [x] ~~重新跑截图同批火车票 PDF 的 OCR 接口，确认不再返回“其他单据/空字段”。~~（完成于 11:55，证据：5173 `/api/v1/ocr/recognize` 返回 `2月20_武汉-上海.pdf` 与 `2月23_上海-武汉.pdf` 均为 `火车/高铁票`，并写回票据夹字段）
|
||||
- [x] ~~重建或补齐当前运行容器的 `poppler-data` / `mupdf-tools`，确认 `mutool` 可用后再上传同类中文 PDF，目标是同时恢复 PNG 预览和 OCR 字段。~~（完成于 12:04，证据：`apt-get install poppler-data mupdf-tools` 成功，`/usr/bin/mutool` 可用；两条 `/preview` 返回 `image/png`，并写入 `preview_kind=image`）
|
||||
- [x] ~~统一 AI 会话附件、票据夹和报销附件的预览类型判定，避免会话上传卡片继续把已生成 PNG 预览的 PDF 当成 PDF 展示。~~（完成于 12:23，证据：新增 `documentPreviewAssets.js`；前端相关测试 24/24 通过，真实 OCR 返回 `preview_kind=image` 且 `/preview` 为 `image/png`）
|
||||
- [x] ~~重新设计一键关联票据的弹窗 UI，调整内边距、行间距、按钮尺寸与悬浮效果，并按精致化要求收敛尺寸以恢复精致感。~~（完成于 12:52，证据：`npm run build` 构建成功，`receipt-folder-view.test.mjs` 测试通过，样式已应用）
|
||||
- [ ] 单独修复 `expense-application-fast-preview.test.mjs` 里 12 个既有失败或拆分陈旧静态断言，恢复整文件可作为申请链路回归套件使用。（来源：13:03 差旅申请直提链路验证）
|
||||
- [ ] 在真实 5173 AI 工作台输入“去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交”，确认模型计划路径命中 `/steward/plans`，并在缺日期时停在申请核对表、日期补齐后进入提交前核查。（来源：13:20 AI 意图规划器接线）
|
||||
- [x] ~~在真实 5173 AI 工作台输入“2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。”，确认模型计划或 fallback 计划生成申请核对表，并自动保存草稿后给出详情入口。~~（完成于 16:53，证据：1.5 秒内显示用户气泡和 pending 卡，约 38 秒后保存草稿 `AZ8QSX9QA`）
|
||||
- [ ] 在真实 5173 网络面板或后端日志核对 `/steward/plans` 返回 `planning_source=llm_function_call`、`tasks[0].requested_action=save_draft` 和完整 `ontology_fields` 后，再确认前端没有走 rule fallback。（来源：13:58 模型优先规划重构）
|
||||
- [x] ~~确认真实 `/steward/plans` 不再毫秒级规则直出，并在模型不可用时按 10s * 3 次后降级。~~（完成于 14:33，证据：真实 5173 API 回放耗时 32.08s，MiniMax attempt 1/2/3 均超时后才 `rule_fallback`）
|
||||
- [ ] 修复 MiniMax 连通性或配置可用 backup 模型，再用同一句保存草稿话术确认 `/steward/plans` 返回 `planning_source=llm_function_call`。（来源：14:33 模型必经链路验证；16:40 已补代码层 backup tool-call 测试，但真实环境仍 fallback）
|
||||
- [x] ~~评估 LangChain/LangGraph 是否作为 steward agent 层框架，引入前明确 memory、tools/action、planner、runtime state、observability 和依赖风险。~~（完成于 15:14，证据：已引入 LangGraph 第一阶段并默认接管 `/steward/plans` 规划编排，45 个容器测试通过）
|
||||
- [x] ~~将 `StewardSlotDecisionAgent` 和 `StewardRuntimeDecisionAgent` 继续迁入 LangGraph 节点，形成统一 steward graph runtime。~~（完成于 15:31，证据：新增 `StewardGraphRuntime`，容器内 graph runtime 相关回归 59/59 通过）
|
||||
- [x] ~~为 `/steward/plans` 增加服务端白名单 `action_steps`，覆盖申请、报销、保存草稿和直接提交的基础动作规划。~~（完成于 15:53，证据：新增 `StewardActionPlanBuilder`，真实 5173 回放返回完整 action steps，容器内相关回归 66/66 通过）
|
||||
- [x] ~~为 LangGraph steward runtime 增加 checkpoint/persistence 设计，复用现有 conversation state，支持暂停、恢复和可观测 trace。~~（完成于 16:40，证据：新增 `StewardGraphActionRuntime`，同一 `conversation_id + client_trace_id` 重放返回 `idempotent_replay=true`，未确认 action 写入 pending interrupt）
|
||||
- [ ] 修通真实 `llm_function_call` 成功路径，用真实模型配置验证 `/steward/plans` 不再进入 rule fallback。（来源：15:22 LangGraph 迁移文档；action node、checkpoint 和 human-in-the-loop 后端部分已于 16:40 完成）
|
||||
- [x] ~~实现 LangGraph 白名单 action node，把保存草稿、提交审批、关联申请单、创建报销草稿和附件关联接入显式 action contract。~~（完成于 16:40，证据：`StewardGraphActionRuntime` 默认接管 `/steward/actions/execute`，action executor 9/9 通过，关联任务回归 7/7 通过）
|
||||
- [x] ~~实现 action registry 的未知 action 拒绝、确认来源校验、重复申请 precheck 阻断和基础业务执行。~~（完成于 16:13，证据：新增 `StewardActionExecutor`，容器内 action executor 5/5 和迁移回归 71/71 通过；前端点击执行回归 21/21 通过；真实 5173 未确认 submit 返回 `needs_confirmation`）
|
||||
- [x] ~~为第一版 `StewardActionExecutor` 增加 checkpoint / interrupt 恢复、持久化 trace 和幂等键。~~（完成于 16:40，证据：`StewardGraphActionRuntime` 持久化 `steward_action_checkpoint`，重复 trace 不重复建单）
|
||||
- [x] ~~补齐 `link_existing_application` 和 `associate_attachments` 的真实 action executor 接线与回归测试。~~（完成于 16:40，证据：申请关联报销草稿测试和附件关联 runner 测试已通过）
|
||||
- [ ] 前端 AI 工作台从 `steward_action_checkpoint.pending_interrupt` 恢复继续/确认按钮，避免刷新页面后只剩后端 checkpoint、用户看不到可继续 action。（来源：16:40 action graph runtime）
|
||||
- [ ] 拆分 `usePersonalWorkbenchAiMode.js` 的模型规划等待态和对话启动逻辑，优先把文件降回 800 行以内。（来源：16:53 回车无反馈修复）
|
||||
- [x] ~~修复 AI 模式普通回复复用规划 pending 卡片，确保一次用户输入只生成一条助手消息。~~（完成于 16:59，证据：真页输入“你好”最终 `assistantCardCount=1`，前端相关测试 32/32 通过）
|
||||
- [x] ~~让 AI 模式模型规划等待期间持续追加 thinking 事件，而不是静态显示“思考中”后一次性出现步骤。~~（完成于 17:26，证据：真页干净会话 thinking 数量从 2 条逐步增长到 6 条，相关前端测试 33/33 通过）
|
||||
- [x] ~~修复 AI 工作台“保存草稿”后的上下文提交短句，让“提交这个单据”复用最近申请草稿而不是重新规划。~~（完成于 17:40，证据：`workbench-ai-application-context-submit.test.mjs` 与 `workbench-ai-application-gate-model.test.mjs` 通过）
|
||||
- [x] ~~修复“完整出差信息但未说申请/报销”时只停在候选流程确认的问题，让唯一的“先发起出差申请”候选流直接进入申请预览计划。~~（完成于 17:48，证据：`workbench-ai-intent-planner-model.test.mjs` 新增回归通过，相邻 4 组前端测试通过）
|
||||
- [ ] 单独修复或重写 `workbench-ai-mode-switch.test.mjs` 的旧静态结构断言，使它适配 `WorkbenchAiFileStrip` 和 OCR composable 拆分后的真实代码。（来源：17:26 额外测试发现）
|
||||
- [ ] 单独修复或重写 `workbench-ai-mode-expense-scene-action.test.mjs` 与 `expense-application-fast-preview.test.mjs` 中继续扫描旧 Vue 单文件的静态断言，改为覆盖 composable/model 的行为测试。（来源：17:40 上下文提交验证）
|
||||
- [ ] 在真实 5173 AI 工作台回放“2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车”，确认唯一申请候选流直接生成申请核对表。（来源：17:48 无动作话术直进申请预览修复）
|
||||
|
||||
@@ -20,6 +20,7 @@ dependencies = [
|
||||
"email-validator>=2.2.0,<3.0.0",
|
||||
"python-multipart>=0.0.20,<1.0.0",
|
||||
"jieba>=0.42.1,<0.43.0",
|
||||
"langgraph>=1.2.0,<2.0.0",
|
||||
"openpyxl>=3.1.5,<4.0.0",
|
||||
"lightrag-hku>=1.4.16,<1.5.0",
|
||||
"qdrant-client>=1.18.0,<2.0.0",
|
||||
|
||||
Binary file not shown.
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Binary file not shown.
@@ -10,10 +10,13 @@ from fastapi.responses import StreamingResponse
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.api.deps import get_db
|
||||
from app.api.deps import CurrentUserContext, get_current_user, get_db
|
||||
from app.core.config import get_settings
|
||||
from app.models.financial_record import ExpenseClaim
|
||||
from app.schemas.common import ErrorResponse
|
||||
from app.schemas.steward import (
|
||||
StewardActionExecuteRequest,
|
||||
StewardActionExecuteResponse,
|
||||
StewardPlanRequest,
|
||||
StewardPlanResponse,
|
||||
StewardRuntimeDecisionRequest,
|
||||
@@ -27,6 +30,9 @@ from app.services.expense_claim_draft_flow import APPROVED_APPLICATION_LINK_STAT
|
||||
from app.services.expense_claims import ExpenseClaimService
|
||||
from app.services.runtime_chat import RuntimeChatService
|
||||
from app.services.steward_flow_state import StewardFlowStateService
|
||||
from app.services.steward_graph_action_runtime import StewardGraphActionRuntime
|
||||
from app.services.steward_graph_planner import StewardGraphPlannerService
|
||||
from app.services.steward_graph_runtime import StewardGraphRuntime
|
||||
from app.services.steward_intent_agent import StewardIntentAgent
|
||||
from app.services.steward_off_topic_agent import StewardOffTopicAgent
|
||||
from app.services.steward_planner import StewardPlannerService
|
||||
@@ -35,6 +41,8 @@ from app.services.steward_slot_decision_agent import StewardSlotDecisionAgent
|
||||
|
||||
router = APIRouter(prefix="/steward")
|
||||
DbSession = Annotated[Session, Depends(get_db)]
|
||||
CurrentUser = Annotated[CurrentUserContext, Depends(get_current_user)]
|
||||
StewardPlannerLike = StewardPlannerService | StewardGraphPlannerService
|
||||
|
||||
|
||||
@router.post(
|
||||
@@ -69,7 +77,7 @@ def create_steward_slot_decision(
|
||||
payload: StewardSlotDecisionRequest,
|
||||
db: DbSession,
|
||||
) -> StewardSlotDecisionResponse:
|
||||
return StewardSlotDecisionAgent(RuntimeChatService(db)).decide(payload)
|
||||
return _decide_steward_slot(payload, RuntimeChatService(db))
|
||||
|
||||
|
||||
@router.post(
|
||||
@@ -83,10 +91,27 @@ def create_steward_runtime_decision(
|
||||
db: DbSession,
|
||||
) -> StewardRuntimeDecisionResponse:
|
||||
hydrated_payload = _hydrate_runtime_decision_payload(db, payload)
|
||||
decision = StewardRuntimeDecisionAgent(RuntimeChatService(db)).decide(hydrated_payload)
|
||||
decision = _decide_steward_runtime(hydrated_payload, RuntimeChatService(db))
|
||||
return _attach_runtime_conversation_state(db, hydrated_payload, decision)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/actions/execute",
|
||||
response_model=StewardActionExecuteResponse,
|
||||
summary="执行小财管家白名单动作",
|
||||
description=(
|
||||
"按 LangGraph 规划出的 action step 执行确定性业务动作；"
|
||||
"当 action 未知、缺字段、缺确认或预检查未通过时直接阻断并返回结构化兜底结果。"
|
||||
),
|
||||
)
|
||||
def execute_steward_action(
|
||||
payload: StewardActionExecuteRequest,
|
||||
db: DbSession,
|
||||
current_user: CurrentUser,
|
||||
) -> StewardActionExecuteResponse:
|
||||
return StewardGraphActionRuntime(db).execute(payload, current_user)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/plans/stream",
|
||||
summary="流式生成小财管家任务计划",
|
||||
@@ -101,7 +126,7 @@ async def stream_steward_plan(payload: StewardPlanRequest, db: DbSession) -> Str
|
||||
|
||||
async def _iter_steward_plan_events(
|
||||
payload: StewardPlanRequest,
|
||||
planner: StewardPlannerService,
|
||||
planner: StewardPlannerLike,
|
||||
db: Session,
|
||||
) -> AsyncIterator[str]:
|
||||
yield _encode_stream_event(
|
||||
@@ -135,18 +160,53 @@ def _encode_stream_event(event: str, data: dict[str, Any]) -> str:
|
||||
return json.dumps({"event": event, "data": data}, ensure_ascii=False) + "\n"
|
||||
|
||||
|
||||
def _build_steward_planner(db: Session) -> StewardPlannerService:
|
||||
def _build_steward_planner(db: Session) -> StewardPlannerLike:
|
||||
runtime_chat = RuntimeChatService(db)
|
||||
if get_settings().steward_agent_runtime.strip().lower() == "langgraph":
|
||||
return StewardGraphPlannerService(
|
||||
intent_agent=StewardIntentAgent(runtime_chat),
|
||||
off_topic_agent=StewardOffTopicAgent(runtime_chat),
|
||||
)
|
||||
return StewardPlannerService(
|
||||
intent_agent=StewardIntentAgent(runtime_chat),
|
||||
off_topic_agent=StewardOffTopicAgent(runtime_chat),
|
||||
)
|
||||
|
||||
|
||||
def _decide_steward_slot(
|
||||
payload: StewardSlotDecisionRequest,
|
||||
runtime_chat: Any,
|
||||
) -> StewardSlotDecisionResponse:
|
||||
legacy_agent = StewardSlotDecisionAgent(runtime_chat)
|
||||
if not _should_use_langgraph_runtime():
|
||||
return legacy_agent.decide(payload)
|
||||
try:
|
||||
return StewardGraphRuntime(runtime_chat).decide_slot(payload)
|
||||
except Exception:
|
||||
return legacy_agent.decide(payload)
|
||||
|
||||
|
||||
def _decide_steward_runtime(
|
||||
payload: StewardRuntimeDecisionRequest,
|
||||
runtime_chat: Any,
|
||||
) -> StewardRuntimeDecisionResponse:
|
||||
legacy_agent = StewardRuntimeDecisionAgent(runtime_chat)
|
||||
if not _should_use_langgraph_runtime():
|
||||
return legacy_agent.decide(payload)
|
||||
try:
|
||||
return StewardGraphRuntime(runtime_chat).decide_runtime(payload)
|
||||
except Exception:
|
||||
return legacy_agent.decide(payload)
|
||||
|
||||
|
||||
def _should_use_langgraph_runtime() -> bool:
|
||||
return get_settings().steward_agent_runtime.strip().lower() == "langgraph"
|
||||
|
||||
|
||||
def _hydrate_required_application_gate(
|
||||
db: Session,
|
||||
payload: StewardPlanRequest,
|
||||
planner: StewardPlannerService,
|
||||
planner: StewardPlannerLike,
|
||||
) -> StewardPlanRequest:
|
||||
context_json = dict(payload.context_json or {})
|
||||
required_gate = context_json.get("required_application_gate")
|
||||
|
||||
@@ -73,6 +73,7 @@ class Settings(BaseSettings):
|
||||
onlyoffice_backend_url: str = Field(default="", alias="ONLYOFFICE_BACKEND_URL")
|
||||
onlyoffice_jwt_secret: str = Field(default="", alias="ONLYOFFICE_JWT_SECRET")
|
||||
hermes_agent_shared_token: str = Field(default="", alias="HERMES_AGENT_SHARED_TOKEN")
|
||||
steward_agent_runtime: str = Field(default="langgraph", alias="STEWARD_AGENT_RUNTIME")
|
||||
|
||||
log_level: str = Field(default="INFO", alias="LOG_LEVEL")
|
||||
log_dir: str = Field(default="logs", alias="LOG_DIR")
|
||||
|
||||
@@ -4,11 +4,11 @@ from typing import Any, Literal
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
StewardTaskType = Literal["expense_application", "reimbursement"]
|
||||
StewardAssignedAgent = Literal["application_assistant", "reimbursement_assistant"]
|
||||
StewardPlanningSource = Literal["llm_function_call", "rule_fallback"]
|
||||
StewardPlanNextAction = Literal["confirm_flow", "confirm_task", "delegate_task", "none"]
|
||||
StewardRequestedAction = Literal["preview", "save_draft", "submit"]
|
||||
StewardSlotDecisionSource = Literal["llm_function_call", "rule_fallback"]
|
||||
StewardSlotNextAction = Literal["ask_user", "render_preview"]
|
||||
StewardRuntimeDecisionSource = Literal["llm_function_call", "rule_fallback"]
|
||||
@@ -22,6 +22,22 @@ StewardRuntimeNextAction = Literal[
|
||||
"cancel_current_action",
|
||||
"no_op",
|
||||
]
|
||||
StewardActionType = Literal[
|
||||
"detect_intent",
|
||||
"fill_application_fields",
|
||||
"build_application_preview",
|
||||
"fill_reimbursement_fields",
|
||||
"build_reimbursement_preview",
|
||||
"validate_required_fields",
|
||||
"run_duplicate_precheck",
|
||||
"save_application_draft",
|
||||
"submit_application",
|
||||
"link_existing_application",
|
||||
"create_reimbursement_draft",
|
||||
"associate_attachments",
|
||||
]
|
||||
StewardActionStatus = Literal["completed", "planned", "pending_confirmation", "blocked"]
|
||||
StewardActionExecutionStatus = Literal["succeeded", "blocked", "needs_confirmation", "failed"]
|
||||
StewardTaskStatus = Literal[
|
||||
"planned",
|
||||
"needs_confirmation",
|
||||
@@ -58,6 +74,17 @@ class StewardThinkingEvent(BaseModel):
|
||||
status: str = Field(default="completed", description="事件状态。")
|
||||
|
||||
|
||||
class StewardActionStep(BaseModel):
|
||||
step_id: str = Field(description="动作步骤 ID。")
|
||||
action_type: StewardActionType = Field(description="白名单动作类型。")
|
||||
label: str = Field(description="用户可见动作名称。")
|
||||
target_task_id: str = Field(default="", description="关联的小财管家任务 ID。")
|
||||
status: StewardActionStatus = Field(default="planned", description="动作规划状态。")
|
||||
requires_confirmation: bool = Field(default=False, description="执行前是否需要用户确认。")
|
||||
depends_on: list[str] = Field(default_factory=list, description="前置动作步骤 ID。")
|
||||
payload: dict[str, Any] = Field(default_factory=dict, description="动作执行需要的确定性载荷。")
|
||||
|
||||
|
||||
class StewardTask(BaseModel):
|
||||
task_id: str = Field(description="小财管家任务 ID。")
|
||||
task_type: StewardTaskType = Field(description="任务类型。")
|
||||
@@ -66,9 +93,11 @@ class StewardTask(BaseModel):
|
||||
summary: str = Field(description="任务摘要。")
|
||||
status: StewardTaskStatus = Field(default="needs_confirmation", description="任务状态。")
|
||||
confidence: float = Field(default=0.0, ge=0.0, le=1.0, description="识别置信度。")
|
||||
requested_action: StewardRequestedAction = Field(default="preview", description="用户希望执行的动作：预览、保存草稿或提交。")
|
||||
ontology_fields: dict[str, str] = Field(default_factory=dict, description="归一化后的业务本体字段。")
|
||||
missing_fields: list[str] = Field(default_factory=list, description="仍缺失的本体字段。")
|
||||
confirmation_required: bool = Field(default=True, description="执行前是否需要用户确认。")
|
||||
action_steps: list[StewardActionStep] = Field(default_factory=list, description="当前任务的白名单动作步骤。")
|
||||
|
||||
|
||||
class StewardAttachmentGroup(BaseModel):
|
||||
@@ -120,6 +149,7 @@ class StewardPlanResponse(BaseModel):
|
||||
summary: str = Field(description="计划摘要。")
|
||||
thinking_events: list[StewardThinkingEvent] = Field(default_factory=list, description="过程摘要事件。")
|
||||
tasks: list[StewardTask] = Field(default_factory=list, description="拆解后的任务。")
|
||||
action_steps: list[StewardActionStep] = Field(default_factory=list, description="本计划的全量白名单动作步骤。")
|
||||
attachment_groups: list[StewardAttachmentGroup] = Field(default_factory=list, description="附件归集建议。")
|
||||
confirmation_groups: list[StewardConfirmationAction] = Field(default_factory=list, description="等待用户确认的动作。")
|
||||
pending_flow_confirmation: StewardPendingFlowConfirmation = Field(
|
||||
@@ -134,6 +164,30 @@ class StewardPlanResponse(BaseModel):
|
||||
)
|
||||
|
||||
|
||||
class StewardActionExecuteRequest(BaseModel):
|
||||
action_type: str = Field(description="待执行的白名单动作类型。未知动作会被 executor 阻断。")
|
||||
message: str = Field(default="", description="触发该动作的用户原始话术。")
|
||||
plan_id: str = Field(default="", description="关联的小财管家计划 ID。")
|
||||
conversation_id: str | None = Field(default=None, description="关联会话 ID。")
|
||||
task: StewardTask | None = Field(default=None, description="动作所属任务快照。")
|
||||
action_step: StewardActionStep | None = Field(default=None, description="规划侧生成的动作步骤快照。")
|
||||
confirmed: bool = Field(default=False, description="用户是否已确认执行该动作。")
|
||||
context_json: dict[str, Any] = Field(default_factory=dict, description="前端或运行时补充上下文。")
|
||||
client_trace_id: str = Field(default="", description="前端幂等或追踪 ID。")
|
||||
|
||||
|
||||
class StewardActionExecuteResponse(BaseModel):
|
||||
action_type: str = Field(description="实际处理的动作类型。")
|
||||
status: StewardActionExecutionStatus = Field(description="动作执行状态。")
|
||||
execution_source: str = Field(default="langgraph_action", description="执行来源或兜底来源。")
|
||||
fallback_used: bool = Field(default=False, description="是否走了规则兜底执行。")
|
||||
requires_confirmation: bool = Field(default=False, description="是否仍需用户确认。")
|
||||
message: str = Field(description="面向用户展示的执行结果。")
|
||||
blocked_reasons: list[str] = Field(default_factory=list, description="阻断原因。")
|
||||
result_payload: dict[str, Any] = Field(default_factory=dict, description="业务服务返回的结构化结果。")
|
||||
trace: list[dict[str, Any]] = Field(default_factory=list, description="动作执行轨迹。")
|
||||
|
||||
|
||||
class StewardSlotOption(BaseModel):
|
||||
label: str = Field(description="用户可见选项文案。")
|
||||
value: str = Field(description="写回本体字段的选项值。")
|
||||
|
||||
@@ -3,7 +3,6 @@ from __future__ import annotations
|
||||
import re
|
||||
from datetime import date, timedelta
|
||||
|
||||
|
||||
CITY_NAMES = (
|
||||
"北京",
|
||||
"上海",
|
||||
@@ -34,6 +33,16 @@ MONTH_DAY_PATTERN = re.compile(r"(?P<month>\d{1,2})\s*月\s*(?P<day>\d{1,2})\s*(
|
||||
ISO_DATE_PATTERN = re.compile(
|
||||
r"(?P<year>\d{4})[-/年](?P<month>\d{1,2})[-/月](?P<day>\d{1,2})(?:日)?"
|
||||
)
|
||||
ISO_DATE_RANGE_PATTERN = re.compile(
|
||||
r"(?P<start_year>\d{4})[-/年](?P<start_month>\d{1,2})[-/月](?P<start_day>\d{1,2})(?:日)?"
|
||||
r"(?:至|到|~|～|—|--)"
|
||||
r"(?P<end_year>\d{4})[-/年](?P<end_month>\d{1,2})[-/月](?P<end_day>\d{1,2})(?:日)?"
|
||||
)
|
||||
MONTH_DAY_RANGE_PATTERN = re.compile(
|
||||
r"(?P<start_month>\d{1,2})\s*月\s*(?P<start_day>\d{1,2})\s*(?:日|号)?"
|
||||
r"(?:至|到|~|～|—|--|-)"
|
||||
r"(?:(?P<end_month>\d{1,2})\s*月\s*)?(?P<end_day>\d{1,2})\s*(?:日|号)?"
|
||||
)
|
||||
|
||||
|
||||
class ApplicationFactResolver:
|
||||
@@ -60,6 +69,38 @@ class ApplicationFactResolver:
|
||||
if "后天" in compact:
|
||||
return (base_date + timedelta(days=2)).isoformat()
|
||||
|
||||
iso_range = ISO_DATE_RANGE_PATTERN.search(compact)
|
||||
if iso_range:
|
||||
start_date = ApplicationFactResolver.safe_date(
|
||||
int(iso_range.group("start_year")),
|
||||
int(iso_range.group("start_month")),
|
||||
int(iso_range.group("start_day")),
|
||||
)
|
||||
end_date = ApplicationFactResolver.safe_date(
|
||||
int(iso_range.group("end_year")),
|
||||
int(iso_range.group("end_month")),
|
||||
int(iso_range.group("end_day")),
|
||||
)
|
||||
if start_date and end_date:
|
||||
return f"{start_date} 至 {end_date}"
|
||||
|
||||
month_day_range = MONTH_DAY_RANGE_PATTERN.search(compact)
|
||||
if month_day_range:
|
||||
start_month = int(month_day_range.group("start_month"))
|
||||
end_month = int(month_day_range.group("end_month") or start_month)
|
||||
start_date = ApplicationFactResolver.safe_date(
|
||||
base_date.year,
|
||||
start_month,
|
||||
int(month_day_range.group("start_day")),
|
||||
)
|
||||
end_date = ApplicationFactResolver.safe_date(
|
||||
base_date.year,
|
||||
end_month,
|
||||
int(month_day_range.group("end_day")),
|
||||
)
|
||||
if start_date and end_date:
|
||||
return f"{start_date} 至 {end_date}"
|
||||
|
||||
iso_match = ISO_DATE_PATTERN.search(compact)
|
||||
if iso_match:
|
||||
return ApplicationFactResolver.safe_date(
|
||||
@@ -100,6 +141,9 @@ class ApplicationFactResolver:
|
||||
def extract_reason(segment: str, task_type: str) -> str:
|
||||
cleaned = re.sub(r"\s+", "", segment).strip("，,。；; ")
|
||||
if task_type == "expense_application":
|
||||
normalized = strip_application_non_reason_tokens(cleaned)
|
||||
if normalized:
|
||||
return normalized
|
||||
match = re.search(r"(辅助|支持|协助|支撑|参加|拜访|调研|实施|部署|审核).+", cleaned)
|
||||
if match:
|
||||
return strip_trailing_connectors(match.group(0))
|
||||
@@ -130,6 +174,47 @@ def strip_trailing_connectors(value: str) -> str:
|
||||
return re.sub(r"(?:并且|而且|同时|另外|还需要|需要)$", "", cleaned).strip("，,。；; ")
|
||||
|
||||
|
||||
def strip_application_non_reason_tokens(value: str) -> str:
|
||||
cleaned = str(value or "").strip("，,。；; ")
|
||||
if not cleaned:
|
||||
return ""
|
||||
|
||||
preserved_transport_phrases: dict[str, str] = {}
|
||||
|
||||
def preserve_transport_phrase(match: re.Match[str]) -> str:
|
||||
placeholder = f"__TRANSPORT_REASON_{len(preserved_transport_phrases)}__"
|
||||
preserved_transport_phrases[placeholder] = match.group(0)
|
||||
return placeholder
|
||||
|
||||
cleaned = re.sub(
|
||||
r"(?:高铁|动车|火车|飞机|机票|航班|轮船|出租车|的士|网约车|打车|地铁|公交)往返",
|
||||
preserve_transport_phrase,
|
||||
cleaned,
|
||||
)
|
||||
cleaned = ISO_DATE_RANGE_PATTERN.sub("", cleaned)
|
||||
cleaned = MONTH_DAY_RANGE_PATTERN.sub("", cleaned)
|
||||
cleaned = ISO_DATE_PATTERN.sub("", cleaned)
|
||||
cleaned = MONTH_DAY_PATTERN.sub("", cleaned)
|
||||
cleaned = re.sub(r"昨天|前天|明天|后天|今天|上周|上月|下周|下月|近期|月底", "", cleaned)
|
||||
cleaned = re.sub(r"[0-9一二两三四五六七八九十]+天", "", cleaned)
|
||||
cleaned = re.sub(fr"(?:去|到|赴|前往)(?:{'|'.join(CITY_NAMES)})", "", cleaned)
|
||||
cleaned = re.sub(fr"(?:出差|差旅)(?:{'|'.join(CITY_NAMES)})", "", cleaned)
|
||||
cleaned = re.sub(fr"(?:{'|'.join(CITY_NAMES)})(?=出差|差旅)", "", cleaned)
|
||||
cleaned = re.sub(r"出差|差旅|费用申请|出差申请|差旅申请", "", cleaned)
|
||||
cleaned = re.sub(r"交通方式?|出行方式?", "", cleaned)
|
||||
cleaned = re.sub(r"高铁|动车|火车|飞机|机票|航班|轮船|出租车|的士|网约车|打车|地铁|公交", "", cleaned)
|
||||
cleaned = re.sub(
|
||||
r"保存草稿|存草稿|先保存|直接提交|提交申请|确认提交|提交审批|保存|提交|申请|发起|创建|我想要|我想|我要|请帮我|帮我",
|
||||
"",
|
||||
cleaned,
|
||||
)
|
||||
cleaned = re.sub(r"(^|[，,。；;、])(?:交通|出行)(?=$|[，,。；;、])", r"\1", cleaned)
|
||||
for placeholder, phrase in preserved_transport_phrases.items():
|
||||
cleaned = cleaned.replace(placeholder, phrase)
|
||||
cleaned = re.sub(r"[，,。；;、]+", "，", cleaned).strip("，,。；;、的 ")
|
||||
return strip_trailing_connectors(cleaned)
|
||||
|
||||
|
||||
def resolve_application_facts(segment: str, task_type: str, base_date: date) -> dict[str, str]:
|
||||
fields = {
|
||||
"expense_type": ApplicationFactResolver.infer_expense_type(segment, task_type),
|
||||
|
||||
@@ -244,6 +244,7 @@ class RuntimeChatService:
|
||||
timeout_seconds: int | None = None,
|
||||
slot_timeouts: dict[str, int] | None = None,
|
||||
max_attempts: int | None = None,
|
||||
use_failure_cooldown: bool = True,
|
||||
) -> RuntimeToolCallResult:
|
||||
configs: list[dict[str, str]] = []
|
||||
calls: list[RuntimeChatCallTrace] = []
|
||||
@@ -272,7 +273,7 @@ class RuntimeChatService:
|
||||
for attempt in range(1, resolved_max_attempts + 1):
|
||||
for config in configs:
|
||||
cache_key = self._build_slot_cache_key(config)
|
||||
if _slot_failure_until.get(cache_key, 0.0) > monotonic():
|
||||
if use_failure_cooldown and _slot_failure_until.get(cache_key, 0.0) > monotonic():
|
||||
logger.info(
|
||||
"Skip runtime chat tool slot=%s provider=%s because it is in cooldown",
|
||||
config["slot"],
|
||||
@@ -330,9 +331,10 @@ class RuntimeChatService:
|
||||
)
|
||||
except Exception as exc:
|
||||
duration_ms = int((monotonic() - started) * 1000)
|
||||
_slot_failure_until[cache_key] = (
|
||||
monotonic() + DEFAULT_RUNTIME_CHAT_FAILURE_COOLDOWN_SECONDS
|
||||
)
|
||||
if use_failure_cooldown:
|
||||
_slot_failure_until[cache_key] = (
|
||||
monotonic() + DEFAULT_RUNTIME_CHAT_FAILURE_COOLDOWN_SECONDS
|
||||
)
|
||||
calls.append(
|
||||
RuntimeChatCallTrace(
|
||||
slot=config["slot"],
|
||||
|
||||
224
server/src/app/services/steward_action_contracts.py
Normal file
224
server/src/app/services/steward_action_contracts.py
Normal file
@@ -0,0 +1,224 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
from app.schemas.steward import (
|
||||
StewardActionStatus,
|
||||
StewardActionStep,
|
||||
StewardPlanResponse,
|
||||
StewardTask,
|
||||
)
|
||||
|
||||
|
||||
class StewardActionPlanBuilder:
|
||||
"""把小财管家任务转换为确定性的白名单动作步骤。"""
|
||||
|
||||
def attach_action_steps(self, plan: StewardPlanResponse) -> StewardPlanResponse:
|
||||
if not plan.tasks:
|
||||
return plan.model_copy(update={"action_steps": []})
|
||||
|
||||
tasks: list[StewardTask] = []
|
||||
plan_steps = [self._build_detect_intent_step(plan)]
|
||||
for task in plan.tasks:
|
||||
task_steps = self.build_task_action_steps(task)
|
||||
tasks.append(task.model_copy(update={"action_steps": task_steps}))
|
||||
plan_steps.extend(task_steps)
|
||||
return plan.model_copy(update={"tasks": tasks, "action_steps": plan_steps})
|
||||
|
||||
def build_task_action_steps(self, task: StewardTask) -> list[StewardActionStep]:
|
||||
if task.task_type == "expense_application":
|
||||
return self._build_application_steps(task)
|
||||
return self._build_reimbursement_steps(task)
|
||||
|
||||
def _build_application_steps(self, task: StewardTask) -> list[StewardActionStep]:
|
||||
steps = [
|
||||
self._build_task_step(
|
||||
task,
|
||||
1,
|
||||
"fill_application_fields",
|
||||
"填充申请字段",
|
||||
payload=self._field_payload(task),
|
||||
),
|
||||
self._build_task_step(
|
||||
task,
|
||||
2,
|
||||
"build_application_preview",
|
||||
"展示申请核对表",
|
||||
depends_on_index=1,
|
||||
payload={"task_id": task.task_id, "ontology_fields": task.ontology_fields},
|
||||
),
|
||||
self._build_task_step(
|
||||
task,
|
||||
3,
|
||||
"validate_required_fields",
|
||||
"校验申请必填字段",
|
||||
status=self._validation_status(task),
|
||||
depends_on_index=2,
|
||||
payload={"missing_fields": task.missing_fields},
|
||||
),
|
||||
]
|
||||
if task.requested_action == "save_draft":
|
||||
steps.append(
|
||||
self._build_task_step(
|
||||
task,
|
||||
4,
|
||||
"save_application_draft",
|
||||
"保存申请草稿",
|
||||
status=self._side_effect_status(task, requires_confirmation=False),
|
||||
depends_on_index=3,
|
||||
payload={
|
||||
"task_id": task.task_id,
|
||||
"requested_action": task.requested_action,
|
||||
"ontology_fields": task.ontology_fields,
|
||||
},
|
||||
)
|
||||
)
|
||||
elif task.requested_action == "submit":
|
||||
steps.append(
|
||||
self._build_task_step(
|
||||
task,
|
||||
4,
|
||||
"run_duplicate_precheck",
|
||||
"检查重复或冲突申请",
|
||||
status=self._side_effect_status(task, requires_confirmation=False),
|
||||
depends_on_index=3,
|
||||
payload={"task_id": task.task_id, "precheck_type": "travel_overlap"},
|
||||
)
|
||||
)
|
||||
steps.append(
|
||||
self._build_task_step(
|
||||
task,
|
||||
5,
|
||||
"submit_application",
|
||||
"提交申请审批",
|
||||
status=self._side_effect_status(task, requires_confirmation=True),
|
||||
requires_confirmation=not bool(task.missing_fields),
|
||||
depends_on_index=4,
|
||||
payload={
|
||||
"task_id": task.task_id,
|
||||
"requested_action": task.requested_action,
|
||||
"confirmation_required": True,
|
||||
},
|
||||
)
|
||||
)
|
||||
return steps
|
||||
|
||||
def _build_reimbursement_steps(self, task: StewardTask) -> list[StewardActionStep]:
|
||||
steps = [
|
||||
self._build_task_step(
|
||||
task,
|
||||
1,
|
||||
"fill_reimbursement_fields",
|
||||
"填充报销字段",
|
||||
payload=self._field_payload(task),
|
||||
),
|
||||
self._build_task_step(
|
||||
task,
|
||||
2,
|
||||
"build_reimbursement_preview",
|
||||
"展示报销核对表",
|
||||
depends_on_index=1,
|
||||
payload={"task_id": task.task_id, "ontology_fields": task.ontology_fields},
|
||||
),
|
||||
self._build_task_step(
|
||||
task,
|
||||
3,
|
||||
"validate_required_fields",
|
||||
"校验报销必填字段",
|
||||
status=self._validation_status(task),
|
||||
depends_on_index=2,
|
||||
payload={"missing_fields": task.missing_fields},
|
||||
),
|
||||
self._build_task_step(
|
||||
task,
|
||||
4,
|
||||
"create_reimbursement_draft",
|
||||
"创建报销草稿",
|
||||
status=self._side_effect_status(task, requires_confirmation=False),
|
||||
depends_on_index=3,
|
||||
payload={
|
||||
"task_id": task.task_id,
|
||||
"requested_action": task.requested_action,
|
||||
"ontology_fields": task.ontology_fields,
|
||||
},
|
||||
),
|
||||
]
|
||||
if task.ontology_fields.get("attachments"):
|
||||
steps.append(
|
||||
self._build_task_step(
|
||||
task,
|
||||
5,
|
||||
"associate_attachments",
|
||||
"关联报销附件",
|
||||
status=self._side_effect_status(task, requires_confirmation=False),
|
||||
depends_on_index=4,
|
||||
payload={"task_id": task.task_id, "attachments": task.ontology_fields["attachments"]},
|
||||
)
|
||||
)
|
||||
return steps
|
||||
|
||||
@staticmethod
|
||||
def _build_detect_intent_step(plan: StewardPlanResponse) -> StewardActionStep:
|
||||
return StewardActionStep(
|
||||
step_id="plan:00:detect_intent",
|
||||
action_type="detect_intent",
|
||||
label="识别业务意图",
|
||||
status="completed",
|
||||
payload={
|
||||
"planning_source": plan.planning_source,
|
||||
"plan_status": plan.plan_status,
|
||||
},
|
||||
)
|
||||
|
||||
def _build_task_step(
|
||||
self,
|
||||
task: StewardTask,
|
||||
index: int,
|
||||
action_type: str,
|
||||
label: str,
|
||||
*,
|
||||
status: StewardActionStatus = "planned",
|
||||
requires_confirmation: bool = False,
|
||||
depends_on_index: int | None = None,
|
||||
payload: dict[str, Any] | None = None,
|
||||
) -> StewardActionStep:
|
||||
step_id = self._step_id(task, index)
|
||||
depends_on = [self._step_id(task, depends_on_index)] if depends_on_index is not None else []
|
||||
return StewardActionStep(
|
||||
step_id=step_id,
|
||||
action_type=action_type, # type: ignore[arg-type]
|
||||
label=label,
|
||||
target_task_id=task.task_id,
|
||||
status=status,
|
||||
requires_confirmation=requires_confirmation,
|
||||
depends_on=depends_on,
|
||||
payload=payload or {},
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _field_payload(task: StewardTask) -> dict[str, Any]:
|
||||
return {
|
||||
"task_id": task.task_id,
|
||||
"task_type": task.task_type,
|
||||
"requested_action": task.requested_action,
|
||||
"ontology_fields": task.ontology_fields,
|
||||
"missing_fields": task.missing_fields,
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _validation_status(task: StewardTask) -> StewardActionStatus:
|
||||
return "blocked" if task.missing_fields else "planned"
|
||||
|
||||
@staticmethod
|
||||
def _side_effect_status(
|
||||
task: StewardTask,
|
||||
*,
|
||||
requires_confirmation: bool,
|
||||
) -> StewardActionStatus:
|
||||
if task.missing_fields:
|
||||
return "blocked"
|
||||
return "pending_confirmation" if requires_confirmation else "planned"
|
||||
|
||||
@staticmethod
|
||||
def _step_id(task: StewardTask, index: int) -> str:
|
||||
return f"{task.task_id}:{index:02d}"
|
||||
570
server/src/app/services/steward_action_executor.py
Normal file
570
server/src/app/services/steward_action_executor.py
Normal file
@@ -0,0 +1,570 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any
|
||||
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.api.deps import CurrentUserContext
|
||||
from app.schemas.ontology import OntologyParseResult, OntologyPermission
|
||||
from app.schemas.steward import (
|
||||
StewardActionExecuteRequest,
|
||||
StewardActionExecuteResponse,
|
||||
StewardTask,
|
||||
)
|
||||
from app.schemas.user_agent import UserAgentRequest
|
||||
from app.services.attachment_association_jobs import AttachmentAssociationJobRunner
|
||||
from app.services.expense_claims import ExpenseClaimService
|
||||
from app.services.user_agent import UserAgentService
|
||||
from app.services.user_agent_application_dates import resolve_application_days_from_time_range
|
||||
|
||||
SUPPORTED_ACTIONS = {
|
||||
"fill_application_fields",
|
||||
"build_application_preview",
|
||||
"fill_reimbursement_fields",
|
||||
"build_reimbursement_preview",
|
||||
"validate_required_fields",
|
||||
"run_duplicate_precheck",
|
||||
"save_application_draft",
|
||||
"submit_application",
|
||||
"create_reimbursement_draft",
|
||||
"link_existing_application",
|
||||
"associate_attachments",
|
||||
}
|
||||
APPLICATION_SIDE_EFFECT_ACTIONS = {"save_application_draft", "submit_application"}
|
||||
REIMBURSEMENT_SIDE_EFFECT_ACTIONS = {"create_reimbursement_draft", "link_existing_application"}
|
||||
NOOP_ACTIONS = {
|
||||
"fill_application_fields",
|
||||
"build_application_preview",
|
||||
"fill_reimbursement_fields",
|
||||
"build_reimbursement_preview",
|
||||
"validate_required_fields",
|
||||
}
|
||||
TRANSPORT_MODE_LABELS = {
|
||||
"train": "火车",
|
||||
"rail": "火车",
|
||||
"high_speed_rail": "火车",
|
||||
"flight": "飞机",
|
||||
"airplane": "飞机",
|
||||
"plane": "飞机",
|
||||
"ship": "轮船",
|
||||
"boat": "轮船",
|
||||
"taxi": "出租车",
|
||||
}
|
||||
EXPENSE_TYPE_LABELS = {
|
||||
"travel": "差旅费",
|
||||
"transport": "交通费",
|
||||
"hotel": "住宿费",
|
||||
"meal": "业务招待费",
|
||||
"meeting": "会务费",
|
||||
"office": "办公用品费",
|
||||
"other": "其他费用",
|
||||
}
|
||||
APPLICATION_TYPE_LABELS = {
|
||||
"travel": "差旅费用申请",
|
||||
"travel_application": "差旅费用申请",
|
||||
"transport": "交通费用申请",
|
||||
"hotel": "住宿费用申请",
|
||||
"meeting": "会务费用申请",
|
||||
"office": "办公费用申请",
|
||||
}
|
||||
|
||||
|
||||
class StewardActionExecutor:
|
||||
"""执行 LangGraph 规划出的确定性白名单动作。"""
|
||||
|
||||
def __init__(self, db: Session) -> None:
|
||||
self.db = db
|
||||
|
||||
def execute(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
) -> StewardActionExecuteResponse:
|
||||
action_type = self._normalize_action_type(request.action_type)
|
||||
trace = [self._trace("received", action_type=action_type, plan_id=request.plan_id)]
|
||||
if action_type not in SUPPORTED_ACTIONS:
|
||||
return self._blocked(
|
||||
action_type,
|
||||
f"不支持的小财管家动作：{action_type or '空动作'}。",
|
||||
trace=[*trace, self._trace("blocked", reason="unsupported_action")],
|
||||
)
|
||||
|
||||
task = request.task
|
||||
if task is None and action_type not in NOOP_ACTIONS:
|
||||
return self._blocked(
|
||||
action_type,
|
||||
"动作缺少任务快照，无法安全执行。",
|
||||
trace=[*trace, self._trace("blocked", reason="missing_task")],
|
||||
)
|
||||
|
||||
blocked_reasons = self._resolve_task_blockers(task)
|
||||
if blocked_reasons:
|
||||
return self._blocked(
|
||||
action_type,
|
||||
"当前任务仍有必填信息缺失，已停止执行动作。",
|
||||
blocked_reasons=blocked_reasons,
|
||||
trace=[*trace, self._trace("blocked", reason="missing_fields")],
|
||||
)
|
||||
|
||||
if action_type in NOOP_ACTIONS:
|
||||
return StewardActionExecuteResponse(
|
||||
action_type=action_type,
|
||||
status="succeeded",
|
||||
message="动作已确认，无需调用外部业务服务。",
|
||||
result_payload={
|
||||
"task_id": task.task_id if task is not None else "",
|
||||
"action_type": action_type,
|
||||
},
|
||||
trace=[*trace, self._trace("completed", mode="noop")],
|
||||
)
|
||||
if action_type == "run_duplicate_precheck":
|
||||
return self._run_duplicate_precheck(request, current_user, trace)
|
||||
if action_type in APPLICATION_SIDE_EFFECT_ACTIONS:
|
||||
return self._execute_application_action(request, current_user, action_type, trace)
|
||||
if action_type in REIMBURSEMENT_SIDE_EFFECT_ACTIONS:
|
||||
return self._execute_reimbursement_action(request, current_user, action_type, trace)
|
||||
if action_type == "associate_attachments":
|
||||
return self._execute_associate_attachments_action(request, current_user, trace)
|
||||
|
||||
return self._blocked(
|
||||
action_type,
|
||||
f"动作 {action_type} 暂未接入执行器。",
|
||||
trace=[*trace, self._trace("blocked", reason="unwired_action")],
|
||||
)
|
||||
|
||||
def _run_duplicate_precheck(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
trace: list[dict[str, Any]],
|
||||
) -> StewardActionExecuteResponse:
|
||||
payload = self._build_application_user_agent_request(
|
||||
request,
|
||||
current_user,
|
||||
action_type="submit_application",
|
||||
force_submit_message=False,
|
||||
)
|
||||
service = UserAgentService(self.db)
|
||||
facts = service._resolve_expense_application_facts(payload)
|
||||
duplicate = service._find_duplicate_expense_application_record(payload, facts)
|
||||
if duplicate is not None:
|
||||
result_payload = {
|
||||
"status": "blocked",
|
||||
"blocking": True,
|
||||
"duplicate_claim_id": str(duplicate.id or ""),
|
||||
"duplicate_claim_no": str(duplicate.claim_no or ""),
|
||||
"duplicate_stage": str(duplicate.approval_stage or ""),
|
||||
}
|
||||
return StewardActionExecuteResponse(
|
||||
action_type="run_duplicate_precheck",
|
||||
status="blocked",
|
||||
message="检测到同一申请人、同一申请类型、同一时间段已有申请单，已停止直接提交。",
|
||||
blocked_reasons=["duplicate_application"],
|
||||
result_payload=result_payload,
|
||||
trace=[*trace, self._trace("blocked", reason="duplicate_application")],
|
||||
)
|
||||
result_payload = {"status": "ok", "blocking": False}
|
||||
return StewardActionExecuteResponse(
|
||||
action_type="run_duplicate_precheck",
|
||||
status="succeeded",
|
||||
message="未发现重复或冲突申请，可以继续提交。",
|
||||
result_payload=result_payload,
|
||||
trace=[*trace, self._trace("completed", mode="duplicate_precheck")],
|
||||
)
|
||||
|
||||
def _execute_application_action(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
action_type: str,
|
||||
trace: list[dict[str, Any]],
|
||||
) -> StewardActionExecuteResponse:
|
||||
if action_type == "submit_application" and not request.confirmed:
|
||||
return StewardActionExecuteResponse(
|
||||
action_type=action_type,
|
||||
status="needs_confirmation",
|
||||
requires_confirmation=True,
|
||||
message="提交申请前需要用户确认。请确认申请核对表无误后再提交。",
|
||||
trace=[*trace, self._trace("needs_confirmation")],
|
||||
)
|
||||
if action_type == "submit_application":
|
||||
precheck_blocker = self._resolve_submit_precheck_blocker(request.context_json)
|
||||
if precheck_blocker:
|
||||
return self._blocked(
|
||||
action_type,
|
||||
precheck_blocker,
|
||||
blocked_reasons=["precheck_not_passed"],
|
||||
trace=[*trace, self._trace("blocked", reason="precheck_not_passed")],
|
||||
)
|
||||
|
||||
payload = self._build_application_user_agent_request(
|
||||
request,
|
||||
current_user,
|
||||
action_type=action_type,
|
||||
force_submit_message=action_type == "submit_application",
|
||||
)
|
||||
try:
|
||||
user_agent_response = UserAgentService(self.db)._build_expense_application_response(
|
||||
payload,
|
||||
risk_flags=[],
|
||||
)
|
||||
except ValueError as exc:
|
||||
return self._failed(action_type, str(exc), trace)
|
||||
|
||||
draft_payload = (
|
||||
user_agent_response.draft_payload.model_dump(mode="json")
|
||||
if user_agent_response.draft_payload is not None
|
||||
else None
|
||||
)
|
||||
result_payload = {
|
||||
"answer": user_agent_response.answer,
|
||||
"suggested_actions": [
|
||||
action.model_dump(mode="json")
|
||||
for action in user_agent_response.suggested_actions
|
||||
],
|
||||
"requires_confirmation": user_agent_response.requires_confirmation,
|
||||
"draft_payload": draft_payload,
|
||||
}
|
||||
status = "succeeded" if draft_payload is not None else "blocked"
|
||||
blocked_reasons = [] if draft_payload is not None else ["application_not_persisted"]
|
||||
return StewardActionExecuteResponse(
|
||||
action_type=action_type,
|
||||
status=status,
|
||||
message=user_agent_response.answer,
|
||||
blocked_reasons=blocked_reasons,
|
||||
result_payload=result_payload,
|
||||
trace=[*trace, self._trace("completed", service="UserAgentService")],
|
||||
)
|
||||
|
||||
def _execute_reimbursement_action(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
action_type: str,
|
||||
trace: list[dict[str, Any]],
|
||||
) -> StewardActionExecuteResponse:
|
||||
context_json = self._build_reimbursement_context_json(request, current_user)
|
||||
run_id = self._build_run_id(request, action_type)
|
||||
ontology = OntologyParseResult(
|
||||
scenario="expense",
|
||||
intent="draft",
|
||||
permission=OntologyPermission(
|
||||
level="draft_write",
|
||||
allowed=True,
|
||||
reason="小财管家白名单动作创建报销草稿。",
|
||||
),
|
||||
confidence=1.0,
|
||||
run_id=run_id,
|
||||
)
|
||||
try:
|
||||
result = ExpenseClaimService(self.db).save_or_submit_from_ontology(
|
||||
run_id=run_id,
|
||||
user_id=current_user.username,
|
||||
message=self._resolve_message(request),
|
||||
ontology=ontology,
|
||||
context_json=context_json,
|
||||
)
|
||||
except ValueError as exc:
|
||||
return self._failed(action_type, str(exc), trace)
|
||||
|
||||
persisted = str(result.get("claim_id") or "").strip() and str(result.get("status") or "").strip() == "draft"
|
||||
return StewardActionExecuteResponse(
|
||||
action_type=action_type,
|
||||
status="succeeded" if persisted else "blocked",
|
||||
message=str(result.get("message") or "报销草稿已生成。").strip(),
|
||||
blocked_reasons=[] if persisted else ["reimbursement_not_persisted"],
|
||||
result_payload=result,
|
||||
trace=[*trace, self._trace("completed", service="ExpenseClaimService")],
|
||||
)
|
||||
|
||||
def _execute_associate_attachments_action(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
trace: list[dict[str, Any]],
|
||||
) -> StewardActionExecuteResponse:
|
||||
receipt_ids = self._resolve_receipt_ids(request)
|
||||
if not receipt_ids:
|
||||
return self._blocked(
|
||||
"associate_attachments",
|
||||
"关联附件前需要先提供票据夹 receipt_ids。",
|
||||
blocked_reasons=["missing_receipt_ids"],
|
||||
trace=[*trace, self._trace("blocked", reason="missing_receipt_ids")],
|
||||
)
|
||||
try:
|
||||
result = AttachmentAssociationJobRunner(self.db).run(
|
||||
receipt_ids=receipt_ids,
|
||||
current_user=current_user,
|
||||
)
|
||||
except ValueError as exc:
|
||||
return self._blocked(
|
||||
"associate_attachments",
|
||||
str(exc),
|
||||
blocked_reasons=["attachment_association_blocked"],
|
||||
trace=[*trace, self._trace("blocked", reason="attachment_association_blocked")],
|
||||
)
|
||||
except Exception as exc:
|
||||
return self._failed("associate_attachments", str(exc), trace)
|
||||
|
||||
return StewardActionExecuteResponse(
|
||||
action_type="associate_attachments",
|
||||
status="succeeded",
|
||||
message=str(
|
||||
result.get("message")
|
||||
or f"已自动关联到 {result.get('claim_no') or '报销草稿'}。"
|
||||
).strip(),
|
||||
result_payload={
|
||||
**dict(result or {}),
|
||||
"receipt_ids": receipt_ids,
|
||||
},
|
||||
trace=[*trace, self._trace("completed", service="AttachmentAssociationJobRunner")],
|
||||
)
|
||||
|
||||
def _build_application_user_agent_request(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
*,
|
||||
action_type: str,
|
||||
force_submit_message: bool,
|
||||
) -> UserAgentRequest:
|
||||
run_id = self._build_run_id(request, action_type)
|
||||
context_json = self._build_application_context_json(request, current_user, action_type)
|
||||
message = self._resolve_message(request)
|
||||
if force_submit_message and "确认提交" not in message and "直接提交" not in message:
|
||||
message = "\n".join([message, "确认提交"]).strip()
|
||||
ontology = OntologyParseResult(
|
||||
scenario="expense",
|
||||
intent="operate",
|
||||
permission=OntologyPermission(
|
||||
level="approval_required",
|
||||
allowed=True,
|
||||
reason="小财管家白名单动作执行申请操作。",
|
||||
),
|
||||
confidence=1.0,
|
||||
run_id=run_id,
|
||||
)
|
||||
return UserAgentRequest(
|
||||
run_id=run_id,
|
||||
user_id=current_user.username,
|
||||
message=message,
|
||||
ontology=ontology,
|
||||
context_json=context_json,
|
||||
tool_payload={},
|
||||
selected_capability_codes=[],
|
||||
degraded=False,
|
||||
requires_confirmation=False,
|
||||
)
|
||||
|
||||
def _build_application_context_json(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
action_type: str,
|
||||
) -> dict[str, Any]:
|
||||
fields = self._resolve_ontology_fields(request.task)
|
||||
preview_fields = {
|
||||
"applicationType": self._resolve_application_type_label(fields.get("expense_type")),
|
||||
"time": str(fields.get("time_range") or ""),
|
||||
"location": str(fields.get("location") or ""),
|
||||
"reason": str(fields.get("reason") or ""),
|
||||
"days": self._resolve_days_text(fields.get("time_range")),
|
||||
"transportMode": self._resolve_transport_label(fields.get("transport_mode")),
|
||||
"amount": str(fields.get("amount") or ""),
|
||||
"applicant": current_user.name,
|
||||
"department": current_user.department_name,
|
||||
"position": current_user.position,
|
||||
"grade": current_user.grade,
|
||||
"managerName": current_user.manager_name,
|
||||
}
|
||||
context_json = {
|
||||
**dict(request.context_json or {}),
|
||||
"session_type": "application",
|
||||
"entry_source": "steward_action_executor",
|
||||
"document_type": "expense_application",
|
||||
"application_stage": "expense_application",
|
||||
"role_codes": current_user.role_codes,
|
||||
"is_admin": current_user.is_admin,
|
||||
"username": current_user.username,
|
||||
"name": current_user.name,
|
||||
"department_name": current_user.department_name,
|
||||
"position": current_user.position,
|
||||
"grade": current_user.grade,
|
||||
"employee_no": current_user.employee_no,
|
||||
"manager_name": current_user.manager_name,
|
||||
"application_preview": {"fields": preview_fields},
|
||||
}
|
||||
if action_type == "save_application_draft":
|
||||
context_json["application_action"] = "save_draft"
|
||||
context_json["application_save_mode"] = True
|
||||
return context_json
|
||||
|
||||
def _build_reimbursement_context_json(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
) -> dict[str, Any]:
|
||||
fields = self._resolve_ontology_fields(request.task)
|
||||
review_form_values = {
|
||||
"expense_type": self._resolve_expense_type_label(fields.get("expense_type")),
|
||||
"time_range": str(fields.get("time_range") or ""),
|
||||
"occurred_date": str(fields.get("time_range") or ""),
|
||||
"location": str(fields.get("location") or ""),
|
||||
"reason": str(fields.get("reason") or ""),
|
||||
"amount": str(fields.get("amount") or ""),
|
||||
"transport_mode": self._resolve_transport_label(fields.get("transport_mode")),
|
||||
"attachments": str(fields.get("attachments") or ""),
|
||||
}
|
||||
return {
|
||||
**dict(request.context_json or {}),
|
||||
"session_type": "expense",
|
||||
"entry_source": "steward_action_executor",
|
||||
"review_action": "save_draft",
|
||||
"review_form_values": review_form_values,
|
||||
"user_input_text": self._resolve_message(request),
|
||||
"role_codes": current_user.role_codes,
|
||||
"is_admin": current_user.is_admin,
|
||||
"username": current_user.username,
|
||||
"name": current_user.name,
|
||||
"department_name": current_user.department_name,
|
||||
"position": current_user.position,
|
||||
"grade": current_user.grade,
|
||||
"employee_no": current_user.employee_no,
|
||||
"manager_name": current_user.manager_name,
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _resolve_receipt_ids(request: StewardActionExecuteRequest) -> list[str]:
|
||||
context_json = dict(request.context_json or {})
|
||||
raw_values = context_json.get("receipt_ids") or context_json.get("receiptIds") or []
|
||||
if isinstance(raw_values, str):
|
||||
raw_values = [item.strip() for item in raw_values.split(",")]
|
||||
if not isinstance(raw_values, list):
|
||||
raw_values = []
|
||||
receipt_ids = [
|
||||
str(item or "").strip()
|
||||
for item in raw_values
|
||||
if str(item or "").strip()
|
||||
]
|
||||
if receipt_ids:
|
||||
return list(dict.fromkeys(receipt_ids))
|
||||
fields = StewardActionExecutor._resolve_ontology_fields(request.task)
|
||||
raw_receipt = str(fields.get("receipt_ids") or fields.get("receiptIds") or "").strip()
|
||||
if not raw_receipt:
|
||||
return []
|
||||
return list(dict.fromkeys(item.strip() for item in raw_receipt.split(",") if item.strip()))
|
||||
|
||||
@staticmethod
|
||||
def _resolve_submit_precheck_blocker(context_json: dict[str, Any]) -> str:
|
||||
precheck = context_json.get("precheck_result") or context_json.get("precheckResult")
|
||||
if not isinstance(precheck, dict):
|
||||
return "提交申请前需要先完成重复/冲突预检查。"
|
||||
if bool(precheck.get("blocking")):
|
||||
return str(precheck.get("summary") or "重复/冲突预检查未通过，已停止提交。").strip()
|
||||
status = str(precheck.get("status") or "").strip().lower()
|
||||
if status not in {"ok", "passed", "succeeded"}:
|
||||
return "重复/冲突预检查未通过，已停止提交。"
|
||||
return ""
|
||||
|
||||
@staticmethod
|
||||
def _resolve_task_blockers(task: StewardTask | None) -> list[str]:
|
||||
if task is None:
|
||||
return []
|
||||
return [
|
||||
str(field or "").strip()
|
||||
for field in list(task.missing_fields or [])
|
||||
if str(field or "").strip()
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def _resolve_ontology_fields(task: StewardTask | None) -> dict[str, str]:
|
||||
if task is None or not isinstance(task.ontology_fields, dict):
|
||||
return {}
|
||||
return {
|
||||
str(key or "").strip(): str(value or "").strip()
|
||||
for key, value in task.ontology_fields.items()
|
||||
if str(key or "").strip() and str(value or "").strip()
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _resolve_message(request: StewardActionExecuteRequest) -> str:
|
||||
message = str(request.message or "").strip()
|
||||
if message:
|
||||
return message
|
||||
if request.task is not None:
|
||||
return str(request.task.summary or request.task.title or "").strip()
|
||||
return "小财管家动作执行"
|
||||
|
||||
@staticmethod
|
||||
def _resolve_transport_label(value: Any) -> str:
|
||||
text = str(value or "").strip()
|
||||
return TRANSPORT_MODE_LABELS.get(text.lower(), text)
|
||||
|
||||
@staticmethod
|
||||
def _resolve_application_type_label(value: Any) -> str:
|
||||
text = str(value or "").strip()
|
||||
return APPLICATION_TYPE_LABELS.get(text.lower(), text or "费用申请")
|
||||
|
||||
@staticmethod
|
||||
def _resolve_expense_type_label(value: Any) -> str:
|
||||
text = str(value or "").strip()
|
||||
return EXPENSE_TYPE_LABELS.get(text.lower(), text or "其他费用")
|
||||
|
||||
@staticmethod
|
||||
def _resolve_days_text(value: Any) -> str:
|
||||
days = resolve_application_days_from_time_range(str(value or ""))
|
||||
return f"{days}天" if days else ""
|
||||
|
||||
@staticmethod
|
||||
def _normalize_action_type(value: str) -> str:
|
||||
return str(value or "").strip()
|
||||
|
||||
@staticmethod
|
||||
def _build_run_id(request: StewardActionExecuteRequest, action_type: str) -> str:
|
||||
trace_id = str(request.client_trace_id or "").strip()
|
||||
if trace_id:
|
||||
return f"steward-action:{trace_id}"
|
||||
task_id = str(request.task.task_id if request.task is not None else "").strip()
|
||||
suffix = task_id or datetime.now(UTC).strftime("%Y%m%d%H%M%S%f")
|
||||
return f"steward-action:{action_type}:{suffix}"
|
||||
|
||||
@staticmethod
|
||||
def _trace(stage: str, **extra: Any) -> dict[str, Any]:
|
||||
return {
|
||||
"stage": stage,
|
||||
"at": datetime.now(UTC).isoformat(),
|
||||
**extra,
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _blocked(
|
||||
action_type: str,
|
||||
message: str,
|
||||
*,
|
||||
blocked_reasons: list[str] | None = None,
|
||||
trace: list[dict[str, Any]] | None = None,
|
||||
) -> StewardActionExecuteResponse:
|
||||
return StewardActionExecuteResponse(
|
||||
action_type=action_type,
|
||||
status="blocked",
|
||||
execution_source="rule_fallback",
|
||||
fallback_used=True,
|
||||
message=message,
|
||||
blocked_reasons=blocked_reasons or [message],
|
||||
trace=trace or [],
|
||||
)
|
||||
|
||||
def _failed(
|
||||
self,
|
||||
action_type: str,
|
||||
message: str,
|
||||
trace: list[dict[str, Any]],
|
||||
) -> StewardActionExecuteResponse:
|
||||
return StewardActionExecuteResponse(
|
||||
action_type=action_type,
|
||||
status="failed",
|
||||
message=message or "动作执行失败。",
|
||||
blocked_reasons=[message] if message else [],
|
||||
trace=[*trace, self._trace("failed", reason=message)],
|
||||
)
|
||||
204
server/src/app/services/steward_graph_action_runtime.py
Normal file
204
server/src/app/services/steward_graph_action_runtime.py
Normal file
@@ -0,0 +1,204 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any, TypedDict
|
||||
|
||||
from langgraph.graph import END, START, StateGraph
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.api.deps import CurrentUserContext
|
||||
from app.models.agent_conversation import AgentConversation
|
||||
from app.schemas.steward import StewardActionExecuteRequest, StewardActionExecuteResponse
|
||||
from app.services.agent_conversations import AgentConversationService
|
||||
from app.services.steward_action_executor import StewardActionExecutor
|
||||
|
||||
ACTION_CHECKPOINT_KEY = "steward_action_checkpoint"
|
||||
TERMINAL_ACTION_STATUSES = {"succeeded", "blocked", "failed"}
|
||||
|
||||
|
||||
class StewardGraphActionState(TypedDict, total=False):
|
||||
request: StewardActionExecuteRequest
|
||||
current_user: CurrentUserContext
|
||||
conversation: AgentConversation | None
|
||||
trace_id: str
|
||||
existing_result: dict[str, Any]
|
||||
response: StewardActionExecuteResponse
|
||||
|
||||
|
||||
class StewardGraphActionRuntime:
|
||||
"""用 LangGraph 包装小财管家白名单动作执行、checkpoint 和幂等重放。"""
|
||||
|
||||
def __init__(self, db: Session) -> None:
|
||||
self.db = db
|
||||
self.executor = StewardActionExecutor(db)
|
||||
self._graph = self._build_graph()
|
||||
|
||||
def execute(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
) -> StewardActionExecuteResponse:
|
||||
final_state = self._graph.invoke(
|
||||
{
|
||||
"request": request,
|
||||
"current_user": current_user,
|
||||
}
|
||||
)
|
||||
response = final_state.get("response")
|
||||
if not isinstance(response, StewardActionExecuteResponse):
|
||||
raise RuntimeError("LangGraph action runtime 未生成有效执行结果。")
|
||||
return response
|
||||
|
||||
def _build_graph(self):
|
||||
graph = StateGraph(StewardGraphActionState)
|
||||
graph.add_node("action_checkpoint_load", self._load_checkpoint)
|
||||
graph.add_node("action_execute_node", self._execute_action)
|
||||
graph.add_node("action_checkpoint_persist", self._persist_checkpoint)
|
||||
|
||||
graph.add_edge(START, "action_checkpoint_load")
|
||||
graph.add_conditional_edges(
|
||||
"action_checkpoint_load",
|
||||
self._route_after_checkpoint_load,
|
||||
{
|
||||
"replay": "action_checkpoint_persist",
|
||||
"execute": "action_execute_node",
|
||||
},
|
||||
)
|
||||
graph.add_edge("action_execute_node", "action_checkpoint_persist")
|
||||
graph.add_edge("action_checkpoint_persist", END)
|
||||
return graph.compile()
|
||||
|
||||
def _load_checkpoint(self, state: StewardGraphActionState) -> dict[str, Any]:
|
||||
request = state["request"]
|
||||
conversation = self._get_or_create_conversation(request, state["current_user"])
|
||||
trace_id = self._resolve_trace_id(request)
|
||||
if conversation is None or not trace_id:
|
||||
return {
|
||||
"conversation": conversation,
|
||||
"trace_id": trace_id,
|
||||
}
|
||||
|
||||
checkpoint = self._resolve_checkpoint(conversation)
|
||||
existing = dict(checkpoint.get("actions", {}).get(trace_id) or {})
|
||||
existing_response = existing.get("response")
|
||||
status = str(existing.get("status") or "").strip()
|
||||
if isinstance(existing_response, dict) and (
|
||||
status in TERMINAL_ACTION_STATUSES
|
||||
or (status == "needs_confirmation" and not request.confirmed)
|
||||
):
|
||||
response = StewardActionExecuteResponse.model_validate(existing_response)
|
||||
response.result_payload = {
|
||||
**dict(response.result_payload or {}),
|
||||
"idempotent_replay": True,
|
||||
}
|
||||
response.trace = [
|
||||
*list(response.trace or []),
|
||||
self._trace("checkpoint_replay", client_trace_id=trace_id),
|
||||
]
|
||||
return {
|
||||
"conversation": conversation,
|
||||
"trace_id": trace_id,
|
||||
"existing_result": existing,
|
||||
"response": response,
|
||||
}
|
||||
|
||||
return {
|
||||
"conversation": conversation,
|
||||
"trace_id": trace_id,
|
||||
"existing_result": existing,
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _route_after_checkpoint_load(state: StewardGraphActionState) -> str:
|
||||
if isinstance(state.get("response"), StewardActionExecuteResponse):
|
||||
return "replay"
|
||||
return "execute"
|
||||
|
||||
def _execute_action(self, state: StewardGraphActionState) -> dict[str, StewardActionExecuteResponse]:
|
||||
response = self.executor.execute(state["request"], state["current_user"])
|
||||
return {"response": response}
|
||||
|
||||
def _persist_checkpoint(self, state: StewardGraphActionState) -> dict[str, StewardActionExecuteResponse]:
|
||||
response = state["response"]
|
||||
conversation = state.get("conversation")
|
||||
trace_id = str(state.get("trace_id") or "").strip()
|
||||
if conversation is None or not trace_id:
|
||||
return {"response": response}
|
||||
|
||||
checkpoint = self._resolve_checkpoint(conversation)
|
||||
actions = dict(checkpoint.get("actions") or {})
|
||||
request = state["request"]
|
||||
response_payload = response.model_dump(mode="json")
|
||||
actions[trace_id] = {
|
||||
"client_trace_id": trace_id,
|
||||
"action_type": response.action_type,
|
||||
"status": response.status,
|
||||
"request": request.model_dump(mode="json"),
|
||||
"response": response_payload,
|
||||
"updated_at": datetime.now(UTC).isoformat(),
|
||||
}
|
||||
checkpoint["actions"] = actions
|
||||
if response.status == "needs_confirmation":
|
||||
checkpoint["pending_interrupt"] = {
|
||||
"client_trace_id": trace_id,
|
||||
"action_type": response.action_type,
|
||||
"message": response.message,
|
||||
"requires_confirmation": True,
|
||||
"updated_at": datetime.now(UTC).isoformat(),
|
||||
}
|
||||
elif str(checkpoint.get("pending_interrupt", {}).get("client_trace_id") or "") == trace_id:
|
||||
checkpoint["pending_interrupt"] = {}
|
||||
|
||||
conversation.state_json = {
|
||||
**dict(conversation.state_json or {}),
|
||||
ACTION_CHECKPOINT_KEY: checkpoint,
|
||||
}
|
||||
conversation.updated_at = datetime.now(UTC)
|
||||
self.db.add(conversation)
|
||||
self.db.commit()
|
||||
return {"response": response}
|
||||
|
||||
def _get_or_create_conversation(
|
||||
self,
|
||||
request: StewardActionExecuteRequest,
|
||||
current_user: CurrentUserContext,
|
||||
) -> AgentConversation | None:
|
||||
conversation_id = str(request.conversation_id or "").strip()
|
||||
if not conversation_id:
|
||||
return None
|
||||
return AgentConversationService(self.db).get_or_create_conversation(
|
||||
conversation_id=conversation_id,
|
||||
user_id=current_user.username,
|
||||
source="user_message",
|
||||
context_json={
|
||||
"session_type": "steward",
|
||||
"entry_source": "steward_action_executor",
|
||||
"steward_state": dict((request.context_json or {}).get("steward_state") or {}),
|
||||
},
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _resolve_checkpoint(conversation: AgentConversation) -> dict[str, Any]:
|
||||
checkpoint = dict((conversation.state_json or {}).get(ACTION_CHECKPOINT_KEY) or {})
|
||||
checkpoint.setdefault("actions", {})
|
||||
checkpoint.setdefault("pending_interrupt", {})
|
||||
return checkpoint
|
||||
|
||||
@staticmethod
|
||||
def _resolve_trace_id(request: StewardActionExecuteRequest) -> str:
|
||||
trace_id = str(request.client_trace_id or "").strip()
|
||||
if trace_id:
|
||||
return trace_id
|
||||
action_type = str(request.action_type or "").strip()
|
||||
task_id = str(request.task.task_id if request.task is not None else "").strip()
|
||||
if action_type and task_id:
|
||||
return f"{action_type}:{task_id}"
|
||||
return ""
|
||||
|
||||
@staticmethod
|
||||
def _trace(stage: str, **extra: Any) -> dict[str, Any]:
|
||||
return {
|
||||
"stage": stage,
|
||||
"at": datetime.now(UTC).isoformat(),
|
||||
**extra,
|
||||
}
|
||||
220
server/src/app/services/steward_graph_planner.py
Normal file
220
server/src/app/services/steward_graph_planner.py
Normal file
@@ -0,0 +1,220 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import date
|
||||
from typing import Any, TypedDict
|
||||
|
||||
from langgraph.graph import END, START, StateGraph
|
||||
|
||||
from app.schemas.steward import StewardPlanRequest, StewardPlanResponse
|
||||
from app.services.steward_action_contracts import StewardActionPlanBuilder
|
||||
from app.services.steward_constants import BUSINESS_CANONICAL_FIELD_ORDER
|
||||
from app.services.steward_intent_agent import StewardIntentAgent, StewardIntentAgentResult
|
||||
from app.services.steward_model_plan_builder import StewardModelPlanBuilder
|
||||
from app.services.steward_off_topic_agent import StewardOffTopicAgent
|
||||
from app.services.steward_planner_extraction import StewardPlannerExtractionMixin
|
||||
from app.services.steward_planner_fallback import StewardPlannerFallbackMixin
|
||||
|
||||
|
||||
class StewardGraphState(TypedDict, total=False):
|
||||
request: StewardPlanRequest
|
||||
message: str
|
||||
base_date: date
|
||||
scenario: str | None
|
||||
should_use_model: bool
|
||||
intent_result: StewardIntentAgentResult | None
|
||||
plan: StewardPlanResponse
|
||||
model_call_traces: list[dict[str, Any]]
|
||||
fallback_reason: str
|
||||
|
||||
|
||||
class StewardGraphPlannerService(StewardPlannerFallbackMixin, StewardPlannerExtractionMixin):
|
||||
"""用 LangGraph 编排小财管家的意图识别、流程判断和兜底路径。"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
intent_agent: StewardIntentAgent | None = None,
|
||||
off_topic_agent: StewardOffTopicAgent | None = None,
|
||||
) -> None:
|
||||
self.intent_agent = intent_agent
|
||||
self.off_topic_agent = off_topic_agent
|
||||
self._graph = self._build_graph()
|
||||
|
||||
def build_plan(self, request: StewardPlanRequest) -> StewardPlanResponse:
|
||||
final_state = self._graph.invoke(
|
||||
{
|
||||
"request": request,
|
||||
"model_call_traces": [],
|
||||
"fallback_reason": "",
|
||||
}
|
||||
)
|
||||
plan = final_state.get("plan")
|
||||
if not isinstance(plan, StewardPlanResponse):
|
||||
raise RuntimeError("LangGraph 小财管家规划未生成有效计划。")
|
||||
return plan
|
||||
|
||||
def _build_graph(self):
|
||||
graph = StateGraph(StewardGraphState)
|
||||
graph.add_node("prepare_context", self._prepare_context)
|
||||
graph.add_node("detect_model_intent", self._detect_model_intent)
|
||||
graph.add_node("build_off_topic_plan", self._build_off_topic_graph_plan)
|
||||
graph.add_node("build_rule_fallback_plan", self._build_rule_fallback_graph_plan)
|
||||
graph.add_node("attach_action_steps", self._attach_action_steps)
|
||||
|
||||
graph.add_edge(START, "prepare_context")
|
||||
graph.add_conditional_edges(
|
||||
"prepare_context",
|
||||
self._route_after_prepare_context,
|
||||
{
|
||||
"model": "detect_model_intent",
|
||||
"off_topic": "build_off_topic_plan",
|
||||
"fallback": "build_rule_fallback_plan",
|
||||
},
|
||||
)
|
||||
graph.add_conditional_edges(
|
||||
"detect_model_intent",
|
||||
self._route_after_model_intent,
|
||||
{
|
||||
"done": "attach_action_steps",
|
||||
"off_topic": "build_off_topic_plan",
|
||||
"fallback": "build_rule_fallback_plan",
|
||||
},
|
||||
)
|
||||
graph.add_edge("build_off_topic_plan", "attach_action_steps")
|
||||
graph.add_edge("build_rule_fallback_plan", "attach_action_steps")
|
||||
graph.add_edge("attach_action_steps", END)
|
||||
return graph.compile()
|
||||
|
||||
def _prepare_context(self, state: StewardGraphState) -> dict[str, Any]:
|
||||
request = state["request"]
|
||||
message = self._clean_text(request.message)
|
||||
if not message:
|
||||
raise ValueError("小财管家需要一段任务描述。")
|
||||
|
||||
base_date = self._resolve_base_date(request.client_now_iso, request.context_json)
|
||||
return {
|
||||
"message": message,
|
||||
"base_date": base_date,
|
||||
"scenario": self._classify_irrelevant_input(message, request),
|
||||
"should_use_model": bool(
|
||||
self.intent_agent is not None
|
||||
and self._should_use_model_intent_recognition(message, base_date, request)
|
||||
),
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _route_after_prepare_context(state: StewardGraphState) -> str:
|
||||
if state.get("should_use_model"):
|
||||
return "model"
|
||||
if state.get("scenario") is not None:
|
||||
return "off_topic"
|
||||
return "fallback"
|
||||
|
||||
def _detect_model_intent(self, state: StewardGraphState) -> dict[str, Any]:
|
||||
request = state["request"]
|
||||
message = state["message"]
|
||||
base_date = state["base_date"]
|
||||
model_call_traces: list[dict[str, Any]] = []
|
||||
|
||||
if self.intent_agent is None:
|
||||
return {}
|
||||
|
||||
try:
|
||||
intent_result = self.intent_agent.detect(
|
||||
request,
|
||||
base_date=base_date,
|
||||
canonical_fields=list(BUSINESS_CANONICAL_FIELD_ORDER),
|
||||
)
|
||||
if intent_result is None:
|
||||
return {
|
||||
"model_call_traces": self._last_intent_call_traces(model_call_traces),
|
||||
"fallback_reason": (
|
||||
"主模型未返回可用的 function calling 计划，已切换到规则兜底。"
|
||||
),
|
||||
}
|
||||
|
||||
model_call_traces = intent_result.model_call_traces
|
||||
llm_plan = StewardModelPlanBuilder(self).build(
|
||||
intent_result,
|
||||
request=request,
|
||||
base_date=base_date,
|
||||
)
|
||||
if llm_plan is None:
|
||||
return {
|
||||
"model_call_traces": self._last_intent_call_traces(model_call_traces),
|
||||
"fallback_reason": (
|
||||
"主模型未返回可用的 function calling 计划，已切换到规则兜底。"
|
||||
),
|
||||
}
|
||||
|
||||
if self._looks_like_ambiguous_travel_flow(message, base_date, request):
|
||||
return {
|
||||
"plan": self._build_pending_flow_fallback_plan(
|
||||
request,
|
||||
base_date=base_date,
|
||||
model_call_traces=model_call_traces,
|
||||
fallback_reason=(
|
||||
"主模型返回了直接任务，但当前话术没有明确申请或报销动作；"
|
||||
"服务端已改为候选流程确认，避免误入申请流程。"
|
||||
),
|
||||
planning_source="llm_function_call",
|
||||
),
|
||||
"model_call_traces": model_call_traces,
|
||||
}
|
||||
|
||||
return {
|
||||
"intent_result": intent_result,
|
||||
"plan": llm_plan,
|
||||
"model_call_traces": model_call_traces,
|
||||
}
|
||||
except Exception as exc:
|
||||
return {
|
||||
"model_call_traces": self._last_intent_call_traces(model_call_traces),
|
||||
"fallback_reason": f"主模型 function calling 调用失败，已切换到规则兜底：{exc}",
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _route_after_model_intent(state: StewardGraphState) -> str:
|
||||
if isinstance(state.get("plan"), StewardPlanResponse):
|
||||
return "done"
|
||||
if state.get("scenario") is not None:
|
||||
return "off_topic"
|
||||
return "fallback"
|
||||
|
||||
def _build_off_topic_graph_plan(
|
||||
self,
|
||||
state: StewardGraphState,
|
||||
) -> dict[str, StewardPlanResponse]:
|
||||
return {
|
||||
"plan": self._build_off_topic_plan(
|
||||
state["request"],
|
||||
scenario=str(state["scenario"] or ""),
|
||||
model_call_traces=state.get("model_call_traces"),
|
||||
fallback_reason=str(state.get("fallback_reason") or ""),
|
||||
)
|
||||
}
|
||||
|
||||
def _build_rule_fallback_graph_plan(
|
||||
self,
|
||||
state: StewardGraphState,
|
||||
) -> dict[str, StewardPlanResponse]:
|
||||
return {
|
||||
"plan": self._build_rule_fallback_plan(
|
||||
state["request"],
|
||||
base_date=state["base_date"],
|
||||
model_call_traces=state.get("model_call_traces"),
|
||||
fallback_reason=str(state.get("fallback_reason") or ""),
|
||||
)
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _attach_action_steps(state: StewardGraphState) -> dict[str, StewardPlanResponse]:
|
||||
plan = state.get("plan")
|
||||
if not isinstance(plan, StewardPlanResponse):
|
||||
raise RuntimeError("LangGraph 小财管家动作规划缺少有效计划。")
|
||||
return {"plan": StewardActionPlanBuilder().attach_action_steps(plan)}
|
||||
|
||||
def _last_intent_call_traces(
|
||||
self,
|
||||
fallback_traces: list[dict[str, Any]],
|
||||
) -> list[dict[str, Any]]:
|
||||
return getattr(self.intent_agent, "last_call_traces", []) or fallback_traces
|
||||
214
server/src/app/services/steward_graph_runtime.py
Normal file
214
server/src/app/services/steward_graph_runtime.py
Normal file
@@ -0,0 +1,214 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any, TypedDict
|
||||
|
||||
from langgraph.graph import END, START, StateGraph
|
||||
|
||||
from app.schemas.steward import (
|
||||
StewardRuntimeDecisionRequest,
|
||||
StewardRuntimeDecisionResponse,
|
||||
StewardSlotDecisionRequest,
|
||||
StewardSlotDecisionResponse,
|
||||
)
|
||||
from app.services.runtime_chat import RuntimeChatService
|
||||
from app.services.steward_runtime_decision_agent import StewardRuntimeDecisionAgent
|
||||
from app.services.steward_slot_decision_agent import StewardSlotDecisionAgent
|
||||
|
||||
|
||||
class StewardSlotGraphState(TypedDict, total=False):
|
||||
request: StewardSlotDecisionRequest
|
||||
normalized_request: StewardSlotDecisionRequest
|
||||
decision: StewardSlotDecisionResponse
|
||||
model_call_traces: list[dict[str, Any]]
|
||||
fallback_reason: str
|
||||
|
||||
|
||||
class StewardRuntimeGraphState(TypedDict, total=False):
|
||||
request: StewardRuntimeDecisionRequest
|
||||
normalized_request: StewardRuntimeDecisionRequest
|
||||
action_decision: StewardRuntimeDecisionResponse
|
||||
decision: StewardRuntimeDecisionResponse
|
||||
model_call_traces: list[dict[str, Any]]
|
||||
fallback_reason: str
|
||||
|
||||
|
||||
class StewardGraphRuntime:
|
||||
"""用 LangGraph 编排会话内槽位、记忆和行动决策。"""
|
||||
|
||||
def __init__(self, runtime_chat_service: RuntimeChatService) -> None:
|
||||
self.slot_agent = StewardSlotDecisionAgent(runtime_chat_service)
|
||||
self.runtime_agent = StewardRuntimeDecisionAgent(runtime_chat_service)
|
||||
self._slot_graph = self._build_slot_graph()
|
||||
self._runtime_graph = self._build_runtime_graph()
|
||||
|
||||
def decide_slot(self, request: StewardSlotDecisionRequest) -> StewardSlotDecisionResponse:
|
||||
final_state = self._slot_graph.invoke(
|
||||
{
|
||||
"request": request,
|
||||
"model_call_traces": [],
|
||||
"fallback_reason": "",
|
||||
}
|
||||
)
|
||||
decision = final_state.get("decision")
|
||||
if not isinstance(decision, StewardSlotDecisionResponse):
|
||||
raise RuntimeError("LangGraph 槽位决策未生成有效结果。")
|
||||
return decision
|
||||
|
||||
def decide_runtime(self, request: StewardRuntimeDecisionRequest) -> StewardRuntimeDecisionResponse:
|
||||
final_state = self._runtime_graph.invoke(
|
||||
{
|
||||
"request": request,
|
||||
"model_call_traces": [],
|
||||
"fallback_reason": "",
|
||||
}
|
||||
)
|
||||
decision = final_state.get("decision")
|
||||
if not isinstance(decision, StewardRuntimeDecisionResponse):
|
||||
raise RuntimeError("LangGraph 运行时决策未生成有效结果。")
|
||||
return decision
|
||||
|
||||
def _build_slot_graph(self):
|
||||
graph = StateGraph(StewardSlotGraphState)
|
||||
graph.add_node("slot_prepare_context", self._slot_prepare_context)
|
||||
graph.add_node("slot_tool_decision", self._slot_tool_decision)
|
||||
graph.add_node("slot_rule_fallback", self._slot_rule_fallback)
|
||||
|
||||
graph.add_edge(START, "slot_prepare_context")
|
||||
graph.add_edge("slot_prepare_context", "slot_tool_decision")
|
||||
graph.add_conditional_edges(
|
||||
"slot_tool_decision",
|
||||
self._route_after_slot_tool_decision,
|
||||
{
|
||||
"done": END,
|
||||
"fallback": "slot_rule_fallback",
|
||||
},
|
||||
)
|
||||
graph.add_edge("slot_rule_fallback", END)
|
||||
return graph.compile()
|
||||
|
||||
def _build_runtime_graph(self):
|
||||
graph = StateGraph(StewardRuntimeGraphState)
|
||||
graph.add_node("runtime_memory_context", self._runtime_memory_context)
|
||||
graph.add_node("runtime_action_decision", self._runtime_action_decision)
|
||||
graph.add_node("runtime_tool_decision", self._runtime_tool_decision)
|
||||
graph.add_node("runtime_rule_fallback", self._runtime_rule_fallback)
|
||||
|
||||
graph.add_edge(START, "runtime_memory_context")
|
||||
graph.add_conditional_edges(
|
||||
"runtime_memory_context",
|
||||
self._route_after_runtime_memory_context,
|
||||
{
|
||||
"action": "runtime_action_decision",
|
||||
"tool": "runtime_tool_decision",
|
||||
},
|
||||
)
|
||||
graph.add_edge("runtime_action_decision", END)
|
||||
graph.add_conditional_edges(
|
||||
"runtime_tool_decision",
|
||||
self._route_after_runtime_tool_decision,
|
||||
{
|
||||
"done": END,
|
||||
"fallback": "runtime_rule_fallback",
|
||||
},
|
||||
)
|
||||
graph.add_edge("runtime_rule_fallback", END)
|
||||
return graph.compile()
|
||||
|
||||
def _slot_prepare_context(self, state: StewardSlotGraphState) -> dict[str, Any]:
|
||||
return {
|
||||
"normalized_request": self.slot_agent._normalize_request(state["request"]),
|
||||
}
|
||||
|
||||
def _slot_tool_decision(self, state: StewardSlotGraphState) -> dict[str, Any]:
|
||||
request = state.get("normalized_request") or state["request"]
|
||||
try:
|
||||
return {"decision": self.slot_agent.decide(request)}
|
||||
except Exception as exc:
|
||||
return {
|
||||
"model_call_traces": [
|
||||
*state.get("model_call_traces", []),
|
||||
self._build_failure_trace("langgraph_slot_decision", exc),
|
||||
],
|
||||
"fallback_reason": f"LangGraph 槽位工具节点失败，已切换规则兜底：{exc}",
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _route_after_slot_tool_decision(state: StewardSlotGraphState) -> str:
|
||||
if isinstance(state.get("decision"), StewardSlotDecisionResponse):
|
||||
return "done"
|
||||
return "fallback"
|
||||
|
||||
def _slot_rule_fallback(self, state: StewardSlotGraphState) -> dict[str, StewardSlotDecisionResponse]:
|
||||
request = state.get("normalized_request") or self.slot_agent._normalize_request(state["request"])
|
||||
return {
|
||||
"decision": self.slot_agent._build_rule_fallback(
|
||||
request,
|
||||
state.get("model_call_traces", []),
|
||||
)
|
||||
}
|
||||
|
||||
def _runtime_memory_context(self, state: StewardRuntimeGraphState) -> dict[str, Any]:
|
||||
request = self.runtime_agent._normalize_request(state["request"])
|
||||
action_decision = self.runtime_agent._build_selected_flow_decision(request, [])
|
||||
update: dict[str, Any] = {"normalized_request": request}
|
||||
if action_decision is not None:
|
||||
update["action_decision"] = action_decision
|
||||
return update
|
||||
|
||||
@staticmethod
|
||||
def _route_after_runtime_memory_context(state: StewardRuntimeGraphState) -> str:
|
||||
if isinstance(state.get("action_decision"), StewardRuntimeDecisionResponse):
|
||||
return "action"
|
||||
return "tool"
|
||||
|
||||
def _runtime_action_decision(
|
||||
self,
|
||||
state: StewardRuntimeGraphState,
|
||||
) -> dict[str, StewardRuntimeDecisionResponse]:
|
||||
return {"decision": state["action_decision"]}
|
||||
|
||||
def _runtime_tool_decision(self, state: StewardRuntimeGraphState) -> dict[str, Any]:
|
||||
request = state.get("normalized_request") or state["request"]
|
||||
try:
|
||||
return {"decision": self.runtime_agent.decide(request)}
|
||||
except Exception as exc:
|
||||
return {
|
||||
"model_call_traces": [
|
||||
*state.get("model_call_traces", []),
|
||||
self._build_failure_trace("langgraph_runtime_decision", exc),
|
||||
],
|
||||
"fallback_reason": f"LangGraph 运行时工具节点失败，已切换规则兜底：{exc}",
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _route_after_runtime_tool_decision(state: StewardRuntimeGraphState) -> str:
|
||||
if isinstance(state.get("decision"), StewardRuntimeDecisionResponse):
|
||||
return "done"
|
||||
return "fallback"
|
||||
|
||||
def _runtime_rule_fallback(
|
||||
self,
|
||||
state: StewardRuntimeGraphState,
|
||||
) -> dict[str, StewardRuntimeDecisionResponse]:
|
||||
request = state.get("normalized_request") or self.runtime_agent._normalize_request(state["request"])
|
||||
decision = self.runtime_agent._build_rule_fallback(
|
||||
request,
|
||||
state.get("model_call_traces", []),
|
||||
)
|
||||
return {
|
||||
"decision": self.runtime_agent._attach_updated_steward_state(
|
||||
decision,
|
||||
request,
|
||||
)
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _build_failure_trace(slot: str, exc: Exception) -> dict[str, Any]:
|
||||
return {
|
||||
"slot": slot,
|
||||
"provider": "langgraph",
|
||||
"model": "",
|
||||
"attempt": 1,
|
||||
"status": "failed",
|
||||
"error": str(exc),
|
||||
}
|
||||
@@ -42,8 +42,9 @@ class StewardIntentAgent:
|
||||
},
|
||||
max_tokens=1800,
|
||||
temperature=0.1,
|
||||
timeout_seconds=45,
|
||||
max_attempts=1,
|
||||
timeout_seconds=10,
|
||||
max_attempts=3,
|
||||
use_failure_cooldown=False,
|
||||
)
|
||||
self.last_call_traces = result.calls_as_dicts()
|
||||
if result.tool_call is None or result.tool_call.name != STEWARD_INTENT_FUNCTION_NAME:
|
||||
@@ -113,6 +114,8 @@ class StewardIntentAgent:
|
||||
"candidate_flows 同时给出 travel_application 和 travel_reimbursement，tasks 保持空数组。"
|
||||
"所有 ontology_fields 只能使用调用方给出的 canonical_ontology_fields；"
|
||||
"如果输入里出现 occurred_date、transport_type、reason_value 等别名，必须映射为 canonical 字段。"
|
||||
"每个 task 必须输出 requested_action：用户只是要求整理/发起但未说保存或提交时为 preview；"
|
||||
"用户说保存草稿、先保存、存草稿时为 save_draft；用户说直接提交、提交申请、确认提交时为 submit。"
|
||||
"相对日期必须以 base_date 为准转换为明确日期。"
|
||||
"thinking_events 只能是面向用户的过程摘要，不能暴露内部推理链。"
|
||||
"如果用户输入与出差、费用、报销、申请等财务事项完全无关"
|
||||
@@ -165,6 +168,10 @@ class StewardIntentAgent:
|
||||
"minimum": 0,
|
||||
"maximum": 1,
|
||||
},
|
||||
"requested_action": {
|
||||
"type": "string",
|
||||
"enum": ["preview", "save_draft", "submit"],
|
||||
},
|
||||
"ontology_fields": {
|
||||
"type": "object",
|
||||
"additionalProperties": {"type": "string"},
|
||||
@@ -182,6 +189,7 @@ class StewardIntentAgent:
|
||||
"title",
|
||||
"summary",
|
||||
"confidence",
|
||||
"requested_action",
|
||||
"ontology_fields",
|
||||
"missing_fields",
|
||||
],
|
||||
|
||||
@@ -157,6 +157,10 @@ class StewardModelPlanBuilder:
|
||||
task_type=task_type,
|
||||
fields=fields,
|
||||
)
|
||||
requested_action = self._sanitize_requested_action(
|
||||
raw_task.get("requested_action"),
|
||||
fallback_text=request.message,
|
||||
)
|
||||
tasks.append(
|
||||
StewardTask(
|
||||
task_id=task_id,
|
||||
@@ -171,6 +175,7 @@ class StewardModelPlanBuilder:
|
||||
fields=fields,
|
||||
task_type=task_type,
|
||||
),
|
||||
requested_action=requested_action, # type: ignore[arg-type]
|
||||
ontology_fields=fields,
|
||||
missing_fields=missing_fields,
|
||||
confirmation_required=True,
|
||||
@@ -441,6 +446,17 @@ class StewardModelPlanBuilder:
|
||||
missing_fields.append(key)
|
||||
return missing_fields
|
||||
|
||||
def _sanitize_requested_action(self, raw_action: Any, *, fallback_text: str = "") -> str:
|
||||
action = self.planner._clean_text(raw_action)
|
||||
if action in {"preview", "save_draft", "submit"}:
|
||||
return action
|
||||
compact = self.planner._clean_text(fallback_text).replace(" ", "")
|
||||
if any(keyword in compact for keyword in ("直接提交", "提交申请", "确认提交", "提交审批")):
|
||||
return "submit"
|
||||
if any(keyword in compact for keyword in ("保存草稿", "存草稿", "先保存")):
|
||||
return "save_draft"
|
||||
return "preview"
|
||||
|
||||
def _resolve_model_confidence(
|
||||
self,
|
||||
value: Any,
|
||||
@@ -459,6 +475,8 @@ class StewardModelPlanBuilder:
|
||||
if not cleaned:
|
||||
return ""
|
||||
if key == "time_range":
|
||||
if re.search(r"(?:至|到|~|～|—|--|-).*\d", cleaned):
|
||||
return cleaned
|
||||
return self.planner._extract_time_range(cleaned, base_date) or cleaned
|
||||
if key == "expense_type":
|
||||
return self._normalize_expense_type_value(cleaned)
|
||||
|
||||
@@ -3,6 +3,7 @@ from __future__ import annotations
|
||||
from typing import Any
|
||||
|
||||
from app.schemas.steward import StewardPlanRequest, StewardPlanResponse
|
||||
from app.services.steward_action_contracts import StewardActionPlanBuilder
|
||||
from app.services.steward_constants import BUSINESS_CANONICAL_FIELD_ORDER
|
||||
from app.services.steward_intent_agent import StewardIntentAgent
|
||||
from app.services.steward_model_plan_builder import StewardModelPlanBuilder
|
||||
@@ -28,10 +29,7 @@ class StewardPlannerService(StewardPlannerFallbackMixin, StewardPlannerExtractio
|
||||
raise ValueError("小财管家需要一段任务描述。")
|
||||
|
||||
base_date = self._resolve_base_date(request.client_now_iso, request.context_json)
|
||||
# 业务无关输入拦截（纯数字、问候、闲聊、乱码等）：在进入 LLM/规则兜底之前直接返回 off_topic 计划。
|
||||
scenario = self._classify_irrelevant_input(message, request)
|
||||
if scenario is not None:
|
||||
return self._build_off_topic_plan(request, scenario=scenario)
|
||||
model_call_traces: list[dict[str, Any]] = []
|
||||
fallback_reason = ""
|
||||
if self.intent_agent is not None and self._should_use_model_intent_recognition(message, base_date, request):
|
||||
@@ -50,26 +48,44 @@ class StewardPlannerService(StewardPlannerFallbackMixin, StewardPlannerExtractio
|
||||
)
|
||||
if llm_plan is not None:
|
||||
if self._looks_like_ambiguous_travel_flow(message, base_date, request):
|
||||
return self._build_pending_flow_fallback_plan(
|
||||
request,
|
||||
base_date=base_date,
|
||||
model_call_traces=model_call_traces,
|
||||
fallback_reason=(
|
||||
"主模型返回了直接任务，但当前话术没有明确申请或报销动作；"
|
||||
"服务端已改为候选流程确认，避免误入申请流程。"
|
||||
),
|
||||
planning_source="llm_function_call",
|
||||
return self._with_action_steps(
|
||||
self._build_pending_flow_fallback_plan(
|
||||
request,
|
||||
base_date=base_date,
|
||||
model_call_traces=model_call_traces,
|
||||
fallback_reason=(
|
||||
"主模型返回了直接任务，但当前话术没有明确申请或报销动作；"
|
||||
"服务端已改为候选流程确认，避免误入申请流程。"
|
||||
),
|
||||
planning_source="llm_function_call",
|
||||
)
|
||||
)
|
||||
return llm_plan
|
||||
return self._with_action_steps(llm_plan)
|
||||
model_call_traces = getattr(self.intent_agent, "last_call_traces", []) or model_call_traces
|
||||
fallback_reason = "主模型未返回可用的 function calling 计划，已切换到规则兜底。"
|
||||
except Exception as exc:
|
||||
model_call_traces = getattr(self.intent_agent, "last_call_traces", []) or model_call_traces
|
||||
fallback_reason = f"主模型 function calling 调用失败，已切换到规则兜底：{exc}"
|
||||
|
||||
return self._build_rule_fallback_plan(
|
||||
request,
|
||||
base_date=base_date,
|
||||
model_call_traces=model_call_traces,
|
||||
fallback_reason=fallback_reason,
|
||||
if scenario is not None:
|
||||
return self._with_action_steps(
|
||||
self._build_off_topic_plan(
|
||||
request,
|
||||
scenario=scenario,
|
||||
model_call_traces=model_call_traces,
|
||||
fallback_reason=fallback_reason,
|
||||
)
|
||||
)
|
||||
|
||||
return self._with_action_steps(
|
||||
self._build_rule_fallback_plan(
|
||||
request,
|
||||
base_date=base_date,
|
||||
model_call_traces=model_call_traces,
|
||||
fallback_reason=fallback_reason,
|
||||
)
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _with_action_steps(plan: StewardPlanResponse) -> StewardPlanResponse:
|
||||
return StewardActionPlanBuilder().attach_action_steps(plan)
|
||||
|
||||
@@ -133,6 +133,7 @@ class StewardPlannerExtractionMixin:
|
||||
summary=self._build_task_summary(draft.segment, fields),
|
||||
status="needs_confirmation",
|
||||
confidence=self._resolve_task_confidence(draft.segment, fields, draft.task_type),
|
||||
requested_action=self._resolve_requested_action(draft.segment), # type: ignore[arg-type]
|
||||
ontology_fields=fields,
|
||||
missing_fields=missing_fields,
|
||||
confirmation_required=True,
|
||||
@@ -205,6 +206,15 @@ class StewardPlannerExtractionMixin:
|
||||
def _extract_transport_mode(segment: str) -> str:
|
||||
return ApplicationFactResolver.extract_transport_mode(segment)
|
||||
|
||||
@staticmethod
|
||||
def _resolve_requested_action(segment: str) -> str:
|
||||
compact = re.sub(r"\s+", "", segment)
|
||||
if re.search(r"直接提交|提交申请|确认提交|提交审批", compact):
|
||||
return "submit"
|
||||
if re.search(r"保存草稿|存草稿|先保存|保存", compact):
|
||||
return "save_draft"
|
||||
return "preview"
|
||||
|
||||
@staticmethod
|
||||
def _resolve_missing_fields(task_type: str, fields: dict[str, str]) -> list[str]:
|
||||
required = ["expense_type", "time_range", "reason"]
|
||||
@@ -575,4 +585,3 @@ class StewardPlannerExtractionMixin:
|
||||
@staticmethod
|
||||
def _clean_text(value: Any) -> str:
|
||||
return re.sub(r"\s+", " ", str(value or "")).strip()
|
||||
|
||||
|
||||
@@ -34,9 +34,8 @@ class StewardPlannerFallbackMixin:
|
||||
base_date: date,
|
||||
request: StewardPlanRequest,
|
||||
) -> bool:
|
||||
if self._looks_like_ambiguous_travel_flow(message, base_date, request):
|
||||
return False
|
||||
return self._has_multiple_financial_demands(message)
|
||||
return bool(message.strip())
|
||||
|
||||
|
||||
@staticmethod
|
||||
def _is_business_irrelevant_input(message: str, request: StewardPlanRequest) -> bool:
|
||||
@@ -105,12 +104,14 @@ class StewardPlannerFallbackMixin:
|
||||
request: StewardPlanRequest,
|
||||
*,
|
||||
scenario: str,
|
||||
model_call_traces: list[dict[str, Any]] | None = None,
|
||||
fallback_reason: str = "",
|
||||
) -> StewardPlanResponse:
|
||||
"""业务无关输入的兜底计划：根据场景给出对应引导，off_business 场景可由 LLM 增强。"""
|
||||
base_summary = self._default_off_topic_summary(scenario)
|
||||
thinking_event = self._build_off_topic_thinking_event(scenario)
|
||||
suggested_prompts = self._off_topic_suggested_prompts(scenario)
|
||||
model_call_traces: list[dict[str, Any]] = []
|
||||
traces = list(model_call_traces or [])
|
||||
|
||||
# 仅对 off_business 场景尝试让 LLM 生成多样化引导；问候/无意义场景用规则模板即可。
|
||||
if (
|
||||
@@ -121,24 +122,36 @@ class StewardPlannerFallbackMixin:
|
||||
llm_result = self.off_topic_agent.generate(request, scenario=scenario)
|
||||
if llm_result is not None and llm_result.response_text:
|
||||
base_summary = llm_result.response_text
|
||||
model_call_traces = llm_result.model_call_traces
|
||||
traces = llm_result.model_call_traces
|
||||
except Exception:
|
||||
# 失败时静默回退到规则模板
|
||||
pass
|
||||
|
||||
thinking_events = [thinking_event]
|
||||
if fallback_reason:
|
||||
thinking_events.insert(
|
||||
0,
|
||||
StewardThinkingEvent(
|
||||
event_id="intent_agent_rule_fallback",
|
||||
stage="rule_fallback",
|
||||
title="意图识别智能体进入兜底模式",
|
||||
content=fallback_reason,
|
||||
),
|
||||
)
|
||||
|
||||
return StewardPlanResponse(
|
||||
plan_id=f"steward_plan_{uuid.uuid4().hex[:12]}",
|
||||
plan_status="off_topic",
|
||||
planning_source="rule_fallback",
|
||||
next_action="none",
|
||||
summary=base_summary,
|
||||
thinking_events=[thinking_event],
|
||||
thinking_events=thinking_events,
|
||||
tasks=[],
|
||||
attachment_groups=[],
|
||||
confirmation_groups=[],
|
||||
candidate_flows=[],
|
||||
suggested_prompts=suggested_prompts,
|
||||
model_call_traces=model_call_traces,
|
||||
model_call_traces=traces,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
@@ -435,4 +448,3 @@ class StewardPlannerFallbackMixin:
|
||||
)
|
||||
|
||||
return drafts
|
||||
|
||||
|
||||
@@ -1,97 +0,0 @@
|
||||
Metadata-Version: 2.4
|
||||
Name: x-financial-server
|
||||
Version: 0.1.0
|
||||
Summary: Backend service for X-Financial reimbursement and approval platform.
|
||||
Requires-Python: >=3.11
|
||||
Description-Content-Type: text/markdown
|
||||
Requires-Dist: fastapi<1.0.0,>=0.115.0
|
||||
Requires-Dist: uvicorn[standard]<1.0.0,>=0.30.0
|
||||
Requires-Dist: sqlalchemy<3.0.0,>=2.0.36
|
||||
Requires-Dist: alembic<2.0.0,>=1.14.0
|
||||
Requires-Dist: psycopg[binary]<4.0.0,>=3.2.0
|
||||
Requires-Dist: PyJWT<3.0.0,>=2.9.0
|
||||
Requires-Dist: pydantic-settings<3.0.0,>=2.6.0
|
||||
Requires-Dist: python-dotenv<2.0.0,>=1.0.1
|
||||
Requires-Dist: email-validator<3.0.0,>=2.2.0
|
||||
Requires-Dist: python-multipart<1.0.0,>=0.0.20
|
||||
Requires-Dist: openpyxl<4.0.0,>=3.1.5
|
||||
Requires-Dist: lightrag-hku<1.5.0,>=1.4.16
|
||||
Requires-Dist: qdrant-client<2.0.0,>=1.18.0
|
||||
Provides-Extra: dev
|
||||
Requires-Dist: pytest<9.0.0,>=8.3.0; extra == "dev"
|
||||
Requires-Dist: httpx<1.0.0,>=0.28.0; extra == "dev"
|
||||
Requires-Dist: ruff<1.0.0,>=0.8.0; extra == "dev"
|
||||
Provides-Extra: redis
|
||||
Requires-Dist: redis<6.0.0,>=5.2.0; extra == "redis"
|
||||
|
||||
# Server
|
||||
|
||||
后端已按 `FastAPI + PostgreSQL + SQLAlchemy + Alembic` 起好基础工程。
|
||||
|
||||
## 为什么先选 PostgreSQL
|
||||
|
||||
这个项目是报销、审批、员工、流程、审计记录为主，核心特点是：
|
||||
|
||||
- 强事务
|
||||
- 多表关联明显
|
||||
- 审批流和审计日志需要一致性
|
||||
- 后续大概率要做复杂查询、统计和条件筛选
|
||||
|
||||
这类系统优先选关系型数据库更合适，`PostgreSQL` 是当前默认推荐。
|
||||
|
||||
## Redis 要不要现在上
|
||||
|
||||
现在 **不是必须**。
|
||||
|
||||
先不把 Redis 作为启动前置，原因很直接：
|
||||
|
||||
- 当前第一阶段先把核心业务表、接口、权限、审批流跑通
|
||||
- 如果一开始就把 Redis 绑死，会增加部署和排障复杂度
|
||||
|
||||
Redis 更适合后面这些场景：
|
||||
|
||||
- 登录态 / token 黑名单
|
||||
- 热点数据缓存
|
||||
- 限流
|
||||
- 分布式锁
|
||||
- 消息队列 / 后台任务
|
||||
|
||||
所以现在的策略是：
|
||||
|
||||
- 主数据库：`PostgreSQL`
|
||||
- Redis：`可选能力`，配置已预留，但不是必需依赖
|
||||
|
||||
## 目录
|
||||
|
||||
- `src/app/`：应用代码
|
||||
- `alembic/`：数据库迁移
|
||||
- `tests/`：测试
|
||||
|
||||
## 启动
|
||||
|
||||
1. 创建虚拟环境并安装依赖
|
||||
|
||||
```bash
|
||||
cd server
|
||||
python -m venv .venv
|
||||
.venv\\Scripts\\activate
|
||||
pip install -e .[dev]
|
||||
```
|
||||
|
||||
2. 在项目根目录准备环境变量
|
||||
|
||||
```bash
|
||||
copy ..\\.env.example ..\\.env
|
||||
```
|
||||
|
||||
3. 启动服务
|
||||
|
||||
```bash
|
||||
uvicorn app.main:app --reload --app-dir src
|
||||
```
|
||||
|
||||
## 迁移
|
||||
|
||||
```bash
|
||||
alembic upgrade head
|
||||
```
|
||||
@@ -1,139 +0,0 @@
|
||||
README.md
|
||||
pyproject.toml
|
||||
src/app/__init__.py
|
||||
src/app/main.py
|
||||
src/app/api/__init__.py
|
||||
src/app/api/deps.py
|
||||
src/app/api/router.py
|
||||
src/app/api/v1/__init__.py
|
||||
src/app/api/v1/router.py
|
||||
src/app/api/v1/endpoints/__init__.py
|
||||
src/app/api/v1/endpoints/agent_assets.py
|
||||
src/app/api/v1/endpoints/agent_runs.py
|
||||
src/app/api/v1/endpoints/audit_logs.py
|
||||
src/app/api/v1/endpoints/auth.py
|
||||
src/app/api/v1/endpoints/bootstrap.py
|
||||
src/app/api/v1/endpoints/employees.py
|
||||
src/app/api/v1/endpoints/health.py
|
||||
src/app/api/v1/endpoints/knowledge.py
|
||||
src/app/api/v1/endpoints/ocr.py
|
||||
src/app/api/v1/endpoints/ontology.py
|
||||
src/app/api/v1/endpoints/orchestrator.py
|
||||
src/app/api/v1/endpoints/reimbursements.py
|
||||
src/app/api/v1/endpoints/settings.py
|
||||
src/app/api/v1/endpoints/system_logs.py
|
||||
src/app/core/__init__.py
|
||||
src/app/core/admin_secret.py
|
||||
src/app/core/agent_enums.py
|
||||
src/app/core/bootstrap.py
|
||||
src/app/core/config.py
|
||||
src/app/core/logging.py
|
||||
src/app/core/openapi.py
|
||||
src/app/core/secret_box.py
|
||||
src/app/core/security.py
|
||||
src/app/db/__init__.py
|
||||
src/app/db/base.py
|
||||
src/app/db/base_class.py
|
||||
src/app/db/session.py
|
||||
src/app/middleware/__init__.py
|
||||
src/app/middleware/logging.py
|
||||
src/app/models/__init__.py
|
||||
src/app/models/agent_asset.py
|
||||
src/app/models/agent_conversation.py
|
||||
src/app/models/agent_run.py
|
||||
src/app/models/approval.py
|
||||
src/app/models/audit_log.py
|
||||
src/app/models/employee.py
|
||||
src/app/models/employee_change_log.py
|
||||
src/app/models/financial_record.py
|
||||
src/app/models/organization.py
|
||||
src/app/models/reimbursement.py
|
||||
src/app/models/role.py
|
||||
src/app/models/system_model_setting.py
|
||||
src/app/models/system_setting.py
|
||||
src/app/models/system_setting_secret.py
|
||||
src/app/repositories/__init__.py
|
||||
src/app/repositories/agent_asset.py
|
||||
src/app/repositories/agent_run.py
|
||||
src/app/repositories/audit_log.py
|
||||
src/app/repositories/employee.py
|
||||
src/app/repositories/reimbursement.py
|
||||
src/app/repositories/settings.py
|
||||
src/app/schemas/__init__.py
|
||||
src/app/schemas/agent_asset.py
|
||||
src/app/schemas/agent_run.py
|
||||
src/app/schemas/audit_log.py
|
||||
src/app/schemas/auth.py
|
||||
src/app/schemas/bootstrap.py
|
||||
src/app/schemas/common.py
|
||||
src/app/schemas/employee.py
|
||||
src/app/schemas/knowledge.py
|
||||
src/app/schemas/ocr.py
|
||||
src/app/schemas/ontology.py
|
||||
src/app/schemas/orchestrator.py
|
||||
src/app/schemas/reimbursement.py
|
||||
src/app/schemas/settings.py
|
||||
src/app/schemas/system_log.py
|
||||
src/app/schemas/user_agent.py
|
||||
src/app/services/__init__.py
|
||||
src/app/services/agent_asset_spreadsheet.py
|
||||
src/app/services/agent_assets.py
|
||||
src/app/services/agent_conversations.py
|
||||
src/app/services/agent_foundation.py
|
||||
src/app/services/agent_runs.py
|
||||
src/app/services/audit.py
|
||||
src/app/services/auth.py
|
||||
src/app/services/document_intelligence.py
|
||||
src/app/services/employee.py
|
||||
src/app/services/employee_seed.py
|
||||
src/app/services/expense_claims.py
|
||||
src/app/services/expense_rule_runtime.py
|
||||
src/app/services/hermes_sync.py
|
||||
src/app/services/knowledge.py
|
||||
src/app/services/knowledge_index_tasks.py
|
||||
src/app/services/knowledge_normalizer.py
|
||||
src/app/services/knowledge_rag.py
|
||||
src/app/services/knowledge_scheduler.py
|
||||
src/app/services/knowledge_sync.py
|
||||
src/app/services/model_connectivity.py
|
||||
src/app/services/ocr.py
|
||||
src/app/services/ontology.py
|
||||
src/app/services/orchestrator.py
|
||||
src/app/services/reimbursement.py
|
||||
src/app/services/runtime_chat.py
|
||||
src/app/services/settings.py
|
||||
src/app/services/system_hermes.py
|
||||
src/app/services/system_logs.py
|
||||
src/app/services/user_agent.py
|
||||
src/x_financial_server.egg-info/PKG-INFO
|
||||
src/x_financial_server.egg-info/SOURCES.txt
|
||||
src/x_financial_server.egg-info/dependency_links.txt
|
||||
src/x_financial_server.egg-info/requires.txt
|
||||
src/x_financial_server.egg-info/top_level.txt
|
||||
tests/test_agent_asset_onlyoffice_key.py
|
||||
tests/test_agent_asset_service.py
|
||||
tests/test_agent_asset_spreadsheet_import.py
|
||||
tests/test_agent_foundation_endpoints.py
|
||||
tests/test_agent_runs_service.py
|
||||
tests/test_auth_service.py
|
||||
tests/test_config_settings_reload.py
|
||||
tests/test_document_intelligence.py
|
||||
tests/test_employee_service.py
|
||||
tests/test_env_file_precedence.py
|
||||
tests/test_expense_claim_service.py
|
||||
tests/test_imports.py
|
||||
tests/test_knowledge_normalizer.py
|
||||
tests/test_knowledge_onlyoffice_config.py
|
||||
tests/test_knowledge_rag_service.py
|
||||
tests/test_knowledge_service.py
|
||||
tests/test_ocr_endpoints.py
|
||||
tests/test_ocr_service.py
|
||||
tests/test_ontology_service.py
|
||||
tests/test_openapi_schema.py
|
||||
tests/test_reimbursement_endpoints.py
|
||||
tests/test_runtime_chat_service.py
|
||||
tests/test_server_start_dependencies.py
|
||||
tests/test_settings_persistence.py
|
||||
tests/test_settings_service.py
|
||||
tests/test_system_logs_service.py
|
||||
tests/test_user_agent_service.py
|
||||
@@ -1 +0,0 @@
|
||||
|
||||
@@ -1,21 +0,0 @@
|
||||
fastapi<1.0.0,>=0.115.0
|
||||
uvicorn[standard]<1.0.0,>=0.30.0
|
||||
sqlalchemy<3.0.0,>=2.0.36
|
||||
alembic<2.0.0,>=1.14.0
|
||||
psycopg[binary]<4.0.0,>=3.2.0
|
||||
PyJWT<3.0.0,>=2.9.0
|
||||
pydantic-settings<3.0.0,>=2.6.0
|
||||
python-dotenv<2.0.0,>=1.0.1
|
||||
email-validator<3.0.0,>=2.2.0
|
||||
python-multipart<1.0.0,>=0.0.20
|
||||
openpyxl<4.0.0,>=3.1.5
|
||||
lightrag-hku<1.5.0,>=1.4.16
|
||||
qdrant-client<2.0.0,>=1.18.0
|
||||
|
||||
[dev]
|
||||
pytest<9.0.0,>=8.3.0
|
||||
httpx<1.0.0,>=0.28.0
|
||||
ruff<1.0.0,>=0.8.0
|
||||
|
||||
[redis]
|
||||
redis<6.0.0,>=5.2.0
|
||||
@@ -1 +0,0 @@
|
||||
app
|
||||
@@ -22,6 +22,17 @@ def test_application_fact_resolver_extracts_travel_application_fields() -> None:
|
||||
assert facts["transport_mode"] == "train"
|
||||
|
||||
|
||||
def test_application_fact_resolver_drops_transport_prompt_from_application_reason() -> None:
|
||||
facts = resolve_application_facts(
|
||||
"2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交",
|
||||
"expense_application",
|
||||
date(2026, 6, 24),
|
||||
)
|
||||
|
||||
assert facts["reason"] == "辅助国网仿生产服务器部署"
|
||||
assert facts["transport_mode"] == "train"
|
||||
|
||||
|
||||
def test_application_fact_resolver_preserves_reimbursement_transport_semantics() -> None:
|
||||
facts = resolve_application_facts(
|
||||
"报销昨天去北京客户现场沟通产生的出租车费用",
|
||||
|
||||
@@ -939,7 +939,7 @@ def test_application_preview_action_submits_without_orchestrator_run(monkeypatch
|
||||
assert draft_payload["draft_type"] == "expense_application"
|
||||
assert draft_payload["status"] == "submitted"
|
||||
assert draft_payload["approval_stage"] == "直属领导审批"
|
||||
assert draft_payload["claim_no"].startswith("AP-")
|
||||
assert draft_payload["claim_no"].startswith("A")
|
||||
|
||||
with session_factory() as db:
|
||||
claim = db.get(ExpenseClaim, draft_payload["claim_id"])
|
||||
@@ -1015,7 +1015,7 @@ def test_application_preview_action_saves_draft_with_detail_reference(monkeypatc
|
||||
assert draft_payload["status"] == "draft"
|
||||
assert draft_payload["approval_stage"] == "待提交"
|
||||
assert draft_payload["claim_id"]
|
||||
assert draft_payload["claim_no"].startswith("AP-")
|
||||
assert draft_payload["claim_no"].startswith("A")
|
||||
|
||||
with session_factory() as db:
|
||||
claim = db.get(ExpenseClaim, draft_payload["claim_id"])
|
||||
|
||||
@@ -242,6 +242,50 @@ def test_runtime_chat_supports_single_pass_fast_failover(monkeypatch) -> None:
|
||||
assert calls == [("main", 8), ("backup", 20)]
|
||||
|
||||
|
||||
def test_runtime_chat_complete_with_tool_call_fails_over_to_backup_before_retrying_main(monkeypatch) -> None:
|
||||
_clear_runtime_chat_cooldown()
|
||||
session_factory = build_session_factory()
|
||||
with session_factory() as db:
|
||||
service = RuntimeChatService(db)
|
||||
calls: list[str] = []
|
||||
|
||||
def fake_load_chat_slot(slot: str):
|
||||
return {
|
||||
"slot": slot,
|
||||
"provider": "MiniMax" if slot == "main" else "GLM",
|
||||
"endpoint": "https://example.com/v1",
|
||||
"model": "main-model" if slot == "main" else "backup-model",
|
||||
"apiKey": "secret",
|
||||
}
|
||||
|
||||
def fake_request_chat_tool_call(config, messages, *, tools, tool_choice, max_tokens, temperature, timeout_seconds):
|
||||
del messages, tools, tool_choice, max_tokens, temperature, timeout_seconds
|
||||
calls.append(config["slot"])
|
||||
if config["slot"] == "main":
|
||||
raise RuntimeError("main tool call unavailable")
|
||||
return runtime_chat_module.RuntimeChatToolCall(
|
||||
name="submit_steward_intent_plan",
|
||||
arguments={"tasks": [{"task_type": "expense_application"}]},
|
||||
)
|
||||
|
||||
monkeypatch.setattr(service, "_load_chat_slot", fake_load_chat_slot)
|
||||
monkeypatch.setattr(service, "_request_chat_tool_call", fake_request_chat_tool_call)
|
||||
|
||||
result = service.complete_with_tool_call(
|
||||
[{"role": "user", "content": "保存草稿"}],
|
||||
tools=[{"type": "function", "function": {"name": "submit_steward_intent_plan"}}],
|
||||
tool_choice={"type": "function", "function": {"name": "submit_steward_intent_plan"}},
|
||||
max_attempts=3,
|
||||
use_failure_cooldown=False,
|
||||
)
|
||||
|
||||
assert result.tool_call is not None
|
||||
assert result.tool_call.name == "submit_steward_intent_plan"
|
||||
assert result.tool_call.arguments["tasks"][0]["task_type"] == "expense_application"
|
||||
assert calls == ["main", "backup"]
|
||||
assert [item.status for item in result.calls] == ["failed", "succeeded"]
|
||||
|
||||
|
||||
def test_runtime_chat_skips_slot_during_cooldown(monkeypatch) -> None:
|
||||
_clear_runtime_chat_cooldown()
|
||||
session_factory = build_session_factory()
|
||||
@@ -271,3 +315,51 @@ def test_runtime_chat_skips_slot_during_cooldown(monkeypatch) -> None:
|
||||
assert service.complete([{"role": "user", "content": "hello"}], max_attempts=1) == "backup answer"
|
||||
assert service.complete([{"role": "user", "content": "hello again"}], max_attempts=1) == "backup answer"
|
||||
assert calls == ["main", "backup", "backup"]
|
||||
|
||||
|
||||
def test_runtime_chat_tool_call_can_retry_without_failure_cooldown(monkeypatch) -> None:
|
||||
_clear_runtime_chat_cooldown()
|
||||
session_factory = build_session_factory()
|
||||
with session_factory() as db:
|
||||
service = RuntimeChatService(db)
|
||||
calls: list[str] = []
|
||||
|
||||
def fake_load_chat_slot(slot: str):
|
||||
return {
|
||||
"slot": slot,
|
||||
"provider": slot,
|
||||
"endpoint": "https://example.com/v1",
|
||||
"model": f"{slot}-model",
|
||||
"apiKey": "secret",
|
||||
}
|
||||
|
||||
def fake_request_chat_tool_call(
|
||||
config,
|
||||
messages,
|
||||
*,
|
||||
tools,
|
||||
tool_choice,
|
||||
max_tokens,
|
||||
temperature,
|
||||
timeout_seconds,
|
||||
):
|
||||
del messages, tools, tool_choice, max_tokens, temperature, timeout_seconds
|
||||
calls.append(config["slot"])
|
||||
raise RuntimeError("tool call timeout")
|
||||
|
||||
monkeypatch.setattr(service, "_load_chat_slot", fake_load_chat_slot)
|
||||
monkeypatch.setattr(service, "_request_chat_tool_call", fake_request_chat_tool_call)
|
||||
monkeypatch.setattr("app.services.runtime_chat.sleep", lambda *_args, **_kwargs: None)
|
||||
|
||||
result = service.complete_with_tool_call(
|
||||
[{"role": "user", "content": "hello"}],
|
||||
tools=[{"type": "function", "function": {"name": "submit_steward_intent_plan"}}],
|
||||
tool_choice={"type": "function", "function": {"name": "submit_steward_intent_plan"}},
|
||||
slot_priority=("main",),
|
||||
max_attempts=3,
|
||||
use_failure_cooldown=False,
|
||||
)
|
||||
|
||||
assert result.tool_call is None
|
||||
assert calls == ["main", "main", "main"]
|
||||
assert [item.status for item in result.calls] == ["failed", "failed", "failed"]
|
||||
|
||||
455
server/tests/test_steward_action_executor.py
Normal file
455
server/tests/test_steward_action_executor.py
Normal file
@@ -0,0 +1,455 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import Generator
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from fastapi.testclient import TestClient
|
||||
from sqlalchemy import create_engine, select
|
||||
from sqlalchemy.orm import Session, sessionmaker
|
||||
from sqlalchemy.pool import StaticPool
|
||||
|
||||
from app.api.deps import get_db
|
||||
from app.db.base import Base
|
||||
from app.main import create_app
|
||||
from app.models.agent_conversation import AgentConversation
|
||||
from app.models.employee import Employee
|
||||
from app.models.financial_record import ExpenseClaim
|
||||
from app.services import attachment_association_jobs as attachment_jobs_module
|
||||
|
||||
|
||||
def build_session_factory() -> sessionmaker[Session]:
|
||||
engine = create_engine(
|
||||
"sqlite+pysqlite:///:memory:",
|
||||
connect_args={"check_same_thread": False},
|
||||
poolclass=StaticPool,
|
||||
)
|
||||
Base.metadata.create_all(bind=engine)
|
||||
return sessionmaker(bind=engine, autoflush=False, autocommit=False)
|
||||
|
||||
|
||||
def build_client() -> tuple[TestClient, sessionmaker[Session]]:
|
||||
session_factory = build_session_factory()
|
||||
app = create_app()
|
||||
|
||||
def override_db() -> Generator[Session, None, None]:
|
||||
db = session_factory()
|
||||
try:
|
||||
yield db
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
app.dependency_overrides[get_db] = override_db
|
||||
return TestClient(app), session_factory
|
||||
|
||||
|
||||
def seed_employee(db: Session) -> None:
|
||||
manager = Employee(
|
||||
id="steward-action-manager",
|
||||
employee_no="E90000",
|
||||
name="李总",
|
||||
email="leader@example.com",
|
||||
position="部门负责人",
|
||||
grade="P7",
|
||||
)
|
||||
employee = Employee(
|
||||
id="steward-action-employee",
|
||||
employee_no="E90001",
|
||||
name="张三",
|
||||
email="zhangsan@example.com",
|
||||
position="实施工程师",
|
||||
grade="P4",
|
||||
manager=manager,
|
||||
)
|
||||
db.add_all([manager, employee])
|
||||
db.commit()
|
||||
|
||||
|
||||
def auth_headers() -> dict[str, str]:
|
||||
return {
|
||||
"x-auth-username": "zhangsan@example.com",
|
||||
"x-auth-name": "Zhang San",
|
||||
"x-auth-employee-no": "E90001",
|
||||
"x-auth-role-codes": "user",
|
||||
"x-auth-position": "Engineer",
|
||||
"x-auth-grade": "P4",
|
||||
"x-auth-manager-name": "Leader",
|
||||
}
|
||||
|
||||
|
||||
def base_application_task(requested_action: str = "save_draft") -> dict[str, object]:
|
||||
return {
|
||||
"task_id": "task_app_001",
|
||||
"task_type": "expense_application",
|
||||
"assigned_agent": "application_assistant",
|
||||
"title": "上海出差申请",
|
||||
"summary": "2026-02-20 至 2026-02-23 去上海出差，辅助国网仿生产服务器部署，火车出行。",
|
||||
"status": "needs_confirmation",
|
||||
"confidence": 0.96,
|
||||
"requested_action": requested_action,
|
||||
"ontology_fields": {
|
||||
"expense_type": "travel",
|
||||
"time_range": "2026-02-20 至 2026-02-23",
|
||||
"location": "上海",
|
||||
"reason": "辅助国网仿生产服务器部署",
|
||||
"transport_mode": "train",
|
||||
},
|
||||
"missing_fields": [],
|
||||
"confirmation_required": requested_action == "submit",
|
||||
"action_steps": [],
|
||||
}
|
||||
|
||||
|
||||
def base_reimbursement_task() -> dict[str, object]:
|
||||
return {
|
||||
"task_id": "task_reim_001",
|
||||
"task_type": "reimbursement",
|
||||
"assigned_agent": "reimbursement_assistant",
|
||||
"title": "客户现场交通费报销",
|
||||
"summary": "2026-03-04 打车去客户现场，交通费 32 元。",
|
||||
"status": "needs_confirmation",
|
||||
"confidence": 0.9,
|
||||
"requested_action": "save_draft",
|
||||
"ontology_fields": {
|
||||
"expense_type": "transport",
|
||||
"time_range": "2026-03-04",
|
||||
"location": "客户现场",
|
||||
"reason": "客户现场沟通",
|
||||
"amount": "32元",
|
||||
"transport_mode": "taxi",
|
||||
},
|
||||
"missing_fields": [],
|
||||
"confirmation_required": False,
|
||||
"action_steps": [],
|
||||
}
|
||||
|
||||
|
||||
def claim_count(db: Session) -> int:
|
||||
return len(db.scalars(select(ExpenseClaim)).all())
|
||||
|
||||
|
||||
def seed_approved_application(db: Session) -> None:
|
||||
application = ExpenseClaim(
|
||||
id="application-action-approved",
|
||||
claim_no="AAPPROVED1",
|
||||
employee_id="steward-action-employee",
|
||||
employee_name="张三",
|
||||
department_id="dept-delivery",
|
||||
department_name="交付部",
|
||||
project_code=None,
|
||||
expense_type="travel_application",
|
||||
reason="辅助国网仿生产服务器部署",
|
||||
location="上海",
|
||||
amount=3000,
|
||||
currency="CNY",
|
||||
invoice_count=0,
|
||||
occurred_at=datetime(2026, 2, 20, tzinfo=UTC),
|
||||
submitted_at=None,
|
||||
status="approved",
|
||||
approval_stage="已完成",
|
||||
risk_flags_json=[],
|
||||
)
|
||||
db.add(application)
|
||||
db.commit()
|
||||
|
||||
|
||||
def test_steward_action_executor_rejects_unknown_action_without_creating_claim() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
before_count = claim_count(db)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "delete_all_claims",
|
||||
"message": "请执行未知动作",
|
||||
"task": base_application_task(),
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "blocked"
|
||||
assert payload["action_type"] == "delete_all_claims"
|
||||
assert "不支持" in payload["message"]
|
||||
with session_factory() as db:
|
||||
assert claim_count(db) == before_count
|
||||
|
||||
|
||||
def test_steward_action_executor_blocks_attachment_action_without_receipts() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
before_count = claim_count(db)
|
||||
|
||||
task = base_reimbursement_task()
|
||||
task["ontology_fields"] = {
|
||||
**task["ontology_fields"],
|
||||
"attachments": "taxi.png",
|
||||
}
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "associate_attachments",
|
||||
"message": "关联附件 taxi.png",
|
||||
"task": task,
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "blocked"
|
||||
assert "receipt_id" in payload["message"] or "票据" in payload["message"]
|
||||
with session_factory() as db:
|
||||
assert claim_count(db) == before_count
|
||||
|
||||
|
||||
def test_steward_action_executor_records_pending_interrupt_in_conversation_state() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "submit_application",
|
||||
"message": "2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交",
|
||||
"conversation_id": "conv-action-submit",
|
||||
"client_trace_id": "trace-submit-pending",
|
||||
"task": base_application_task("submit"),
|
||||
"confirmed": False,
|
||||
"context_json": {
|
||||
"precheck_result": {
|
||||
"status": "ok",
|
||||
"blocking": False,
|
||||
}
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "needs_confirmation"
|
||||
with session_factory() as db:
|
||||
conversation = db.scalar(
|
||||
select(AgentConversation).where(
|
||||
AgentConversation.conversation_id == "conv-action-submit"
|
||||
)
|
||||
)
|
||||
assert conversation is not None
|
||||
checkpoint = conversation.state_json["steward_action_checkpoint"]
|
||||
assert checkpoint["pending_interrupt"]["client_trace_id"] == "trace-submit-pending"
|
||||
assert checkpoint["pending_interrupt"]["action_type"] == "submit_application"
|
||||
assert checkpoint["actions"]["trace-submit-pending"]["status"] == "needs_confirmation"
|
||||
|
||||
|
||||
def test_steward_action_executor_reuses_checkpoint_for_duplicate_trace_without_duplicate_draft() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
|
||||
request_payload = {
|
||||
"action_type": "save_application_draft",
|
||||
"message": "2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，保存草稿",
|
||||
"conversation_id": "conv-action-draft",
|
||||
"client_trace_id": "trace-save-draft",
|
||||
"task": base_application_task("save_draft"),
|
||||
}
|
||||
first_response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json=request_payload,
|
||||
)
|
||||
second_response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json=request_payload,
|
||||
)
|
||||
|
||||
assert first_response.status_code == 200
|
||||
assert second_response.status_code == 200
|
||||
first_payload = first_response.json()
|
||||
second_payload = second_response.json()
|
||||
assert first_payload["status"] == "succeeded"
|
||||
assert second_payload["status"] == "succeeded"
|
||||
assert (
|
||||
first_payload["result_payload"]["draft_payload"]["claim_id"]
|
||||
== second_payload["result_payload"]["draft_payload"]["claim_id"]
|
||||
)
|
||||
assert second_payload["result_payload"]["idempotent_replay"] is True
|
||||
with session_factory() as db:
|
||||
assert claim_count(db) == 1
|
||||
|
||||
|
||||
def test_steward_action_executor_requires_confirmation_before_submit_side_effect() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "submit_application",
|
||||
"message": "2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交",
|
||||
"task": base_application_task("submit"),
|
||||
"confirmed": False,
|
||||
"context_json": {
|
||||
"precheck_result": {
|
||||
"status": "ok",
|
||||
"blocking": False,
|
||||
}
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "needs_confirmation"
|
||||
assert payload["requires_confirmation"] is True
|
||||
with session_factory() as db:
|
||||
assert claim_count(db) == 0
|
||||
|
||||
|
||||
def test_steward_action_executor_saves_application_draft_from_action_step() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "save_application_draft",
|
||||
"message": "2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，保存草稿",
|
||||
"task": base_application_task("save_draft"),
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "succeeded"
|
||||
draft_payload = payload["result_payload"]["draft_payload"]
|
||||
assert draft_payload["draft_type"] == "expense_application"
|
||||
assert draft_payload["status"] == "draft"
|
||||
assert draft_payload["claim_no"].startswith("A")
|
||||
with session_factory() as db:
|
||||
claim = db.scalars(select(ExpenseClaim)).one()
|
||||
assert claim.status == "draft"
|
||||
assert claim.reason == "辅助国网仿生产服务器部署"
|
||||
|
||||
|
||||
def test_steward_action_executor_creates_reimbursement_draft_from_action_step() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "create_reimbursement_draft",
|
||||
"message": "2026-03-04，打车去客户现场，交通费32元，保存草稿",
|
||||
"task": base_reimbursement_task(),
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "succeeded"
|
||||
assert payload["result_payload"]["status"] == "draft"
|
||||
assert payload["result_payload"]["claim_id"]
|
||||
with session_factory() as db:
|
||||
claim = db.scalars(select(ExpenseClaim)).one()
|
||||
assert claim.status == "draft"
|
||||
assert claim.expense_type == "transport"
|
||||
assert claim.reason == "客户现场沟通"
|
||||
|
||||
|
||||
def test_steward_action_executor_links_application_when_creating_reimbursement_draft() -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
seed_approved_application(db)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "link_existing_application",
|
||||
"message": "关联申请单 AAPPROVED1，并保存报销草稿",
|
||||
"task": base_reimbursement_task(),
|
||||
"context_json": {
|
||||
"application_claim_id": "application-action-approved",
|
||||
"application_claim_no": "AAPPROVED1",
|
||||
"application_reason": "辅助国网仿生产服务器部署",
|
||||
"application_location": "上海",
|
||||
"application_business_time": "2026-02-20 至 2026-02-23",
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "succeeded"
|
||||
assert payload["result_payload"]["status"] == "draft"
|
||||
with session_factory() as db:
|
||||
claims = db.scalars(select(ExpenseClaim)).all()
|
||||
reimbursement = next(claim for claim in claims if claim.id != "application-action-approved")
|
||||
assert reimbursement.status == "draft"
|
||||
link_flags = [
|
||||
flag
|
||||
for flag in list(reimbursement.risk_flags_json or [])
|
||||
if isinstance(flag, dict) and flag.get("source") == "application_link"
|
||||
]
|
||||
assert link_flags
|
||||
assert link_flags[0]["application_claim_no"] == "AAPPROVED1"
|
||||
|
||||
|
||||
def test_steward_action_executor_associates_receipt_attachments(monkeypatch) -> None:
|
||||
client, session_factory = build_client()
|
||||
with session_factory() as db:
|
||||
seed_employee(db)
|
||||
|
||||
calls: list[dict[str, object]] = []
|
||||
|
||||
def fake_run(self, *, receipt_ids, current_user):
|
||||
calls.append({
|
||||
"receipt_ids": list(receipt_ids),
|
||||
"username": current_user.username,
|
||||
})
|
||||
return {
|
||||
"claim_id": "claim-associated",
|
||||
"claim_no": "BX-20260220-001",
|
||||
"uploaded_count": 2,
|
||||
"skipped_count": 0,
|
||||
}
|
||||
|
||||
monkeypatch.setattr(attachment_jobs_module.AttachmentAssociationJobRunner, "run", fake_run)
|
||||
|
||||
response = client.post(
|
||||
"/api/v1/steward/actions/execute",
|
||||
headers=auth_headers(),
|
||||
json={
|
||||
"action_type": "associate_attachments",
|
||||
"message": "把两张火车票关联到报销草稿",
|
||||
"task": base_reimbursement_task(),
|
||||
"context_json": {
|
||||
"receipt_ids": ["receipt-001", "receipt-002"],
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload["status"] == "succeeded"
|
||||
assert payload["result_payload"]["claim_no"] == "BX-20260220-001"
|
||||
assert calls == [
|
||||
{
|
||||
"receipt_ids": ["receipt-001", "receipt-002"],
|
||||
"username": "zhangsan@example.com",
|
||||
}
|
||||
]
|
||||
234
server/tests/test_steward_graph_planner.py
Normal file
234
server/tests/test_steward_graph_planner.py
Normal file
@@ -0,0 +1,234 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from app.api.v1.endpoints import steward as steward_endpoint
|
||||
from app.core.config import get_settings
|
||||
from app.schemas.steward import StewardPlanRequest
|
||||
from app.services.steward_graph_planner import StewardGraphPlannerService
|
||||
from app.services.steward_intent_agent import StewardIntentAgentResult
|
||||
from app.services.steward_planner import StewardPlannerService
|
||||
|
||||
|
||||
class GraphTravelApplicationIntentAgent:
|
||||
def __init__(self) -> None:
|
||||
self.calls = 0
|
||||
|
||||
def detect(self, request, *, base_date, canonical_fields):
|
||||
self.calls += 1
|
||||
return StewardIntentAgentResult(
|
||||
payload={
|
||||
"thinking_events": [
|
||||
{
|
||||
"stage": "task_split",
|
||||
"title": "识别出差申请草稿",
|
||||
"content": "模型识别到用户要创建上海出差申请，并保存草稿。",
|
||||
}
|
||||
],
|
||||
"tasks": [
|
||||
{
|
||||
"task_type": "expense_application",
|
||||
"title": "上海出差申请",
|
||||
"summary": (
|
||||
"2026-02-20 至 2026-02-23 前往上海，"
|
||||
"国网仿生产服务器部署，火车出行。"
|
||||
),
|
||||
"requested_action": "save_draft",
|
||||
"confidence": 0.95,
|
||||
"ontology_fields": {
|
||||
"time_range": "2026-02-20 至 2026-02-23",
|
||||
"location": "上海",
|
||||
"expense_type": "差旅",
|
||||
"reason": "国网仿生产服务器部署",
|
||||
"transport_type": "火车",
|
||||
},
|
||||
"missing_fields": [],
|
||||
}
|
||||
],
|
||||
"attachment_groups": [],
|
||||
},
|
||||
model_call_traces=[
|
||||
{
|
||||
"slot": "main",
|
||||
"provider": "MiniMax",
|
||||
"model": "abab-test",
|
||||
"attempt": 1,
|
||||
"status": "succeeded",
|
||||
}
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class GraphSubmitTravelApplicationIntentAgent:
|
||||
def __init__(self) -> None:
|
||||
self.calls = 0
|
||||
|
||||
def detect(self, request, *, base_date, canonical_fields):
|
||||
self.calls += 1
|
||||
return StewardIntentAgentResult(
|
||||
payload={
|
||||
"thinking_events": [
|
||||
{
|
||||
"stage": "task_split",
|
||||
"title": "识别出差申请提交",
|
||||
"content": "模型识别到用户要创建上海出差申请，并直接提交。",
|
||||
}
|
||||
],
|
||||
"tasks": [
|
||||
{
|
||||
"task_type": "expense_application",
|
||||
"title": "上海出差申请",
|
||||
"summary": (
|
||||
"2026-02-20 至 2026-02-23 前往上海，"
|
||||
"辅助国网仿生产服务器部署，火车出行。"
|
||||
),
|
||||
"requested_action": "submit",
|
||||
"confidence": 0.96,
|
||||
"ontology_fields": {
|
||||
"time_range": "2026-02-20 至 2026-02-23",
|
||||
"location": "上海",
|
||||
"expense_type": "差旅",
|
||||
"reason": "辅助国网仿生产服务器部署",
|
||||
"transport_mode": "火车",
|
||||
},
|
||||
"missing_fields": [],
|
||||
}
|
||||
],
|
||||
"attachment_groups": [],
|
||||
},
|
||||
model_call_traces=[
|
||||
{
|
||||
"slot": "main",
|
||||
"provider": "MiniMax",
|
||||
"model": "abab-test",
|
||||
"attempt": 1,
|
||||
"status": "succeeded",
|
||||
}
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class GraphEmptyIntentAgent:
|
||||
def __init__(self) -> None:
|
||||
self.calls = 0
|
||||
|
||||
def detect(self, request, *, base_date, canonical_fields):
|
||||
self.calls += 1
|
||||
return None
|
||||
|
||||
|
||||
def test_langgraph_planner_preserves_llm_save_draft_plan() -> None:
|
||||
intent_agent = GraphTravelApplicationIntentAgent()
|
||||
service = StewardGraphPlannerService(intent_agent=intent_agent)
|
||||
|
||||
result = service.build_plan(
|
||||
StewardPlanRequest(
|
||||
message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿",
|
||||
client_now_iso="2026-02-10T09:00:00+08:00",
|
||||
)
|
||||
)
|
||||
|
||||
assert intent_agent.calls == 1
|
||||
assert result.planning_source == "llm_function_call"
|
||||
assert result.tasks[0].requested_action == "save_draft"
|
||||
assert result.tasks[0].ontology_fields["time_range"] == "2026-02-20 至 2026-02-23"
|
||||
assert result.tasks[0].ontology_fields["transport_mode"] == "train"
|
||||
assert result.model_call_traces[0]["provider"] == "MiniMax"
|
||||
|
||||
|
||||
def test_langgraph_planner_builds_submit_action_steps_for_application() -> None:
|
||||
intent_agent = GraphSubmitTravelApplicationIntentAgent()
|
||||
service = StewardGraphPlannerService(intent_agent=intent_agent)
|
||||
|
||||
result = service.build_plan(
|
||||
StewardPlanRequest(
|
||||
message="2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交",
|
||||
client_now_iso="2026-02-10T09:00:00+08:00",
|
||||
)
|
||||
)
|
||||
|
||||
assert intent_agent.calls == 1
|
||||
assert result.planning_source == "llm_function_call"
|
||||
assert result.action_steps[0].action_type == "detect_intent"
|
||||
assert [step.action_type for step in result.tasks[0].action_steps] == [
|
||||
"fill_application_fields",
|
||||
"build_application_preview",
|
||||
"validate_required_fields",
|
||||
"run_duplicate_precheck",
|
||||
"submit_application",
|
||||
]
|
||||
assert result.tasks[0].action_steps[0].payload["ontology_fields"]["location"] == "上海"
|
||||
assert result.tasks[0].action_steps[-1].requires_confirmation is True
|
||||
assert result.tasks[0].action_steps[-1].status == "pending_confirmation"
|
||||
|
||||
|
||||
def test_langgraph_planner_falls_back_when_model_returns_no_tool_call() -> None:
|
||||
intent_agent = GraphEmptyIntentAgent()
|
||||
service = StewardGraphPlannerService(intent_agent=intent_agent)
|
||||
|
||||
result = service.build_plan(
|
||||
StewardPlanRequest(
|
||||
message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿",
|
||||
client_now_iso="2026-02-10T09:00:00+08:00",
|
||||
)
|
||||
)
|
||||
|
||||
assert intent_agent.calls == 1
|
||||
assert result.planning_source == "rule_fallback"
|
||||
assert result.tasks[0].requested_action == "save_draft"
|
||||
assert result.tasks[0].ontology_fields["time_range"] == "2026-02-20 至 2026-02-23"
|
||||
assert result.tasks[0].ontology_fields["transport_mode"] == "train"
|
||||
assert result.model_call_traces == []
|
||||
|
||||
|
||||
def test_langgraph_planner_rule_fallback_builds_save_draft_action_steps() -> None:
|
||||
intent_agent = GraphEmptyIntentAgent()
|
||||
service = StewardGraphPlannerService(intent_agent=intent_agent)
|
||||
|
||||
result = service.build_plan(
|
||||
StewardPlanRequest(
|
||||
message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿",
|
||||
client_now_iso="2026-02-10T09:00:00+08:00",
|
||||
)
|
||||
)
|
||||
|
||||
assert result.planning_source == "rule_fallback"
|
||||
assert result.tasks[0].requested_action == "save_draft"
|
||||
assert [step.action_type for step in result.tasks[0].action_steps] == [
|
||||
"fill_application_fields",
|
||||
"build_application_preview",
|
||||
"validate_required_fields",
|
||||
"save_application_draft",
|
||||
]
|
||||
assert result.tasks[0].action_steps[-1].status == "planned"
|
||||
|
||||
|
||||
def test_build_steward_planner_uses_langgraph_runtime_when_enabled(monkeypatch) -> None:
|
||||
monkeypatch.setenv("STEWARD_AGENT_RUNTIME", "langgraph")
|
||||
get_settings.cache_clear()
|
||||
try:
|
||||
planner = steward_endpoint._build_steward_planner(db=object())
|
||||
finally:
|
||||
get_settings.cache_clear()
|
||||
|
||||
assert isinstance(planner, StewardGraphPlannerService)
|
||||
|
||||
|
||||
def test_build_steward_planner_defaults_to_langgraph_runtime(monkeypatch) -> None:
|
||||
monkeypatch.delenv("STEWARD_AGENT_RUNTIME", raising=False)
|
||||
get_settings.cache_clear()
|
||||
try:
|
||||
planner = steward_endpoint._build_steward_planner(db=object())
|
||||
finally:
|
||||
get_settings.cache_clear()
|
||||
|
||||
assert isinstance(planner, StewardGraphPlannerService)
|
||||
|
||||
|
||||
def test_build_steward_planner_can_fall_back_to_legacy_runtime(monkeypatch) -> None:
|
||||
monkeypatch.setenv("STEWARD_AGENT_RUNTIME", "legacy")
|
||||
get_settings.cache_clear()
|
||||
try:
|
||||
planner = steward_endpoint._build_steward_planner(db=object())
|
||||
finally:
|
||||
get_settings.cache_clear()
|
||||
|
||||
assert isinstance(planner, StewardPlannerService)
|
||||
268
server/tests/test_steward_graph_runtime.py
Normal file
268
server/tests/test_steward_graph_runtime.py
Normal file
@@ -0,0 +1,268 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import pytest
|
||||
|
||||
from app.api.v1.endpoints import steward as steward_endpoint
|
||||
from app.core.config import get_settings
|
||||
from app.schemas.steward import (
|
||||
StewardRuntimeDecisionRequest,
|
||||
StewardSlotDecisionRequest,
|
||||
)
|
||||
from app.services.runtime_chat import (
|
||||
RuntimeChatCallTrace,
|
||||
RuntimeChatToolCall,
|
||||
RuntimeToolCallResult,
|
||||
)
|
||||
from app.services.steward_graph_runtime import StewardGraphRuntime
|
||||
from app.services.steward_runtime_decision_agent import STEWARD_RUNTIME_DECISION_FUNCTION_NAME
|
||||
from app.services.steward_slot_decision_agent import STEWARD_SLOT_DECISION_FUNCTION_NAME
|
||||
|
||||
|
||||
class _FakeRuntime:
|
||||
def __init__(
|
||||
self,
|
||||
payloads: dict[str, dict[str, Any] | None] | None = None,
|
||||
*,
|
||||
fail_functions: set[str] | None = None,
|
||||
) -> None:
|
||||
self.payloads = payloads or {}
|
||||
self.fail_functions = fail_functions or set()
|
||||
self.called_functions: list[str] = []
|
||||
self.last_messages: list[dict[str, Any]] = []
|
||||
|
||||
def complete_with_tool_call(self, messages, tools, tool_choice, **kwargs):
|
||||
function_name = str(tool_choice["function"]["name"])
|
||||
self.called_functions.append(function_name)
|
||||
self.last_messages = messages
|
||||
if function_name in self.fail_functions:
|
||||
raise RuntimeError(f"{function_name} failed")
|
||||
payload = self.payloads.get(function_name)
|
||||
if payload is None:
|
||||
return RuntimeToolCallResult(tool_call=None, calls=[])
|
||||
return RuntimeToolCallResult(
|
||||
tool_call=RuntimeChatToolCall(name=function_name, arguments=payload),
|
||||
calls=[
|
||||
RuntimeChatCallTrace(
|
||||
slot=function_name,
|
||||
provider="fake",
|
||||
model="fake",
|
||||
attempt=1,
|
||||
status="succeeded",
|
||||
)
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class _FailingGraphRuntime:
|
||||
def __init__(self, runtime_chat_service) -> None:
|
||||
self.runtime_chat_service = runtime_chat_service
|
||||
|
||||
def decide_slot(self, request):
|
||||
raise RuntimeError("langgraph runtime unavailable")
|
||||
|
||||
def decide_runtime(self, request):
|
||||
raise RuntimeError("langgraph runtime unavailable")
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _clear_settings_cache():
|
||||
get_settings.cache_clear()
|
||||
yield
|
||||
get_settings.cache_clear()
|
||||
|
||||
|
||||
def test_graph_runtime_routes_slot_decision_through_langgraph_tool_node() -> None:
|
||||
runtime = _FakeRuntime(
|
||||
{
|
||||
STEWARD_SLOT_DECISION_FUNCTION_NAME: {
|
||||
"next_action": "ask_user",
|
||||
"required_fields": ["expense_type", "time_range", "location", "reason", "transport_mode"],
|
||||
"missing_fields": ["transport_mode"],
|
||||
"question": "请问您这次打算怎么出行？",
|
||||
"options": [
|
||||
{"field_key": "transport_mode", "label": "火车", "value": "火车"},
|
||||
{"field_key": "transport_mode", "label": "飞机", "value": "飞机"},
|
||||
],
|
||||
"rationale": "出行方式会影响交通费用测算。",
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
result = StewardGraphRuntime(runtime).decide_slot(
|
||||
StewardSlotDecisionRequest(
|
||||
task_type="expense_application",
|
||||
user_message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署",
|
||||
ontology_fields={
|
||||
"expense_type": "travel",
|
||||
"time_range": "2026-02-20 至 2026-02-23",
|
||||
"location": "上海",
|
||||
"reason": "国网仿生产服务器部署",
|
||||
},
|
||||
missing_fields=["transport_mode"],
|
||||
)
|
||||
)
|
||||
|
||||
assert result.decision_source == "llm_function_call"
|
||||
assert result.next_action == "ask_user"
|
||||
assert result.missing_fields == ["transport_mode"]
|
||||
assert runtime.called_functions == [STEWARD_SLOT_DECISION_FUNCTION_NAME]
|
||||
|
||||
|
||||
def test_graph_runtime_slot_graph_falls_back_when_tool_node_fails() -> None:
|
||||
runtime = _FakeRuntime(fail_functions={STEWARD_SLOT_DECISION_FUNCTION_NAME})
|
||||
|
||||
result = StewardGraphRuntime(runtime).decide_slot(
|
||||
StewardSlotDecisionRequest(
|
||||
task_type="expense_application",
|
||||
user_message="上海出差，辅助国网仿生产部署",
|
||||
ontology_fields={
|
||||
"expense_type": "travel",
|
||||
"location": "上海",
|
||||
"reason": "辅助国网仿生产部署",
|
||||
},
|
||||
missing_fields=["transport_mode"],
|
||||
)
|
||||
)
|
||||
|
||||
assert result.decision_source == "rule_fallback"
|
||||
assert result.next_action == "ask_user"
|
||||
assert result.missing_fields == ["transport_mode"]
|
||||
assert any(
|
||||
trace.get("slot") == "langgraph_slot_decision"
|
||||
and trace.get("status") == "failed"
|
||||
for trace in result.model_call_traces
|
||||
)
|
||||
|
||||
|
||||
def test_graph_runtime_merges_memory_before_runtime_action_node() -> None:
|
||||
runtime = _FakeRuntime({STEWARD_RUNTIME_DECISION_FUNCTION_NAME: None})
|
||||
|
||||
result = StewardGraphRuntime(runtime).decide_runtime(
|
||||
StewardRuntimeDecisionRequest(
|
||||
user_message="我坐高铁",
|
||||
runtime_state={},
|
||||
context_json={
|
||||
"conversation_state": {
|
||||
"steward_state": {
|
||||
"active_flow": "travel_application",
|
||||
"flows": {
|
||||
"travel_application": {
|
||||
"flow_id": "travel_application",
|
||||
"intent": "travel_application_create",
|
||||
"fields": {
|
||||
"expense_type": "travel",
|
||||
"time_range": "2026-07-02",
|
||||
"location": "北京",
|
||||
"reason": "客户现场支撑",
|
||||
},
|
||||
"missing_fields": ["transport_mode"],
|
||||
}
|
||||
},
|
||||
}
|
||||
}
|
||||
},
|
||||
)
|
||||
)
|
||||
|
||||
assert result.decision_source == "rule_fallback"
|
||||
assert result.next_action == "fill_current_slot"
|
||||
assert result.field_key == "transport_mode"
|
||||
assert result.field_value == "我坐高铁"
|
||||
assert result.steward_state["flows"]["travel_application"]["fields"]["transport_mode"] == "我坐高铁"
|
||||
assert result.steward_state["flows"]["travel_application"]["missing_fields"] == []
|
||||
assert runtime.called_functions == [STEWARD_RUNTIME_DECISION_FUNCTION_NAME]
|
||||
assert "steward_state" in runtime.last_messages[-1]["content"]
|
||||
|
||||
|
||||
def test_graph_runtime_selected_flow_action_node_skips_model_call() -> None:
|
||||
runtime = _FakeRuntime()
|
||||
|
||||
result = StewardGraphRuntime(runtime).decide_runtime(
|
||||
StewardRuntimeDecisionRequest(
|
||||
user_message="补办出差申请",
|
||||
runtime_state={
|
||||
"steward_state": {
|
||||
"active_flow": "",
|
||||
"pending_flow_confirmation": {
|
||||
"status": "pending",
|
||||
"candidate_flows": [
|
||||
{"flow_id": "travel_application", "label": "补办出差申请"},
|
||||
{"flow_id": "travel_reimbursement", "label": "发起费用报销"},
|
||||
],
|
||||
},
|
||||
"flows": {
|
||||
"travel_application": {
|
||||
"flow_id": "travel_application",
|
||||
"intent": "travel_application_create",
|
||||
"status": "pending_flow_confirmation",
|
||||
"fields": {
|
||||
"time_range": "2026-02-20",
|
||||
"location": "上海",
|
||||
"expense_type": "travel",
|
||||
"reason": "辅助国网仿生产环境部署",
|
||||
},
|
||||
"missing_fields": ["transport_mode"],
|
||||
}
|
||||
},
|
||||
}
|
||||
},
|
||||
)
|
||||
)
|
||||
|
||||
assert result.decision_source == "rule_fallback"
|
||||
assert result.next_action == "continue_selected_flow"
|
||||
assert result.target_task_id == "travel_application"
|
||||
assert result.steward_state["active_flow"] == "travel_application"
|
||||
assert runtime.called_functions == []
|
||||
|
||||
|
||||
def test_slot_endpoint_helper_falls_back_to_legacy_agent_when_langgraph_runtime_fails(monkeypatch) -> None:
|
||||
monkeypatch.setenv("STEWARD_AGENT_RUNTIME", "langgraph")
|
||||
get_settings.cache_clear()
|
||||
monkeypatch.setattr(steward_endpoint, "StewardGraphRuntime", _FailingGraphRuntime)
|
||||
runtime = _FakeRuntime({STEWARD_SLOT_DECISION_FUNCTION_NAME: None})
|
||||
|
||||
result = steward_endpoint._decide_steward_slot(
|
||||
StewardSlotDecisionRequest(
|
||||
task_type="expense_application",
|
||||
user_message="上海出差，辅助国网仿生产部署",
|
||||
ontology_fields={
|
||||
"expense_type": "travel",
|
||||
"location": "上海",
|
||||
"reason": "辅助国网仿生产部署",
|
||||
},
|
||||
missing_fields=["transport_mode"],
|
||||
),
|
||||
runtime,
|
||||
)
|
||||
|
||||
assert result.decision_source == "rule_fallback"
|
||||
assert result.next_action == "ask_user"
|
||||
assert runtime.called_functions == [STEWARD_SLOT_DECISION_FUNCTION_NAME]
|
||||
|
||||
|
||||
def test_runtime_endpoint_helper_falls_back_to_legacy_agent_when_langgraph_runtime_fails(monkeypatch) -> None:
|
||||
monkeypatch.setenv("STEWARD_AGENT_RUNTIME", "langgraph")
|
||||
get_settings.cache_clear()
|
||||
monkeypatch.setattr(steward_endpoint, "StewardGraphRuntime", _FailingGraphRuntime)
|
||||
runtime = _FakeRuntime({STEWARD_RUNTIME_DECISION_FUNCTION_NAME: None})
|
||||
|
||||
result = steward_endpoint._decide_steward_runtime(
|
||||
StewardRuntimeDecisionRequest(
|
||||
user_message="确认",
|
||||
runtime_state={
|
||||
"pending_steward_action": {
|
||||
"message_id": "msg-next-task",
|
||||
"target_task_id": "task-reimbursement-meal",
|
||||
}
|
||||
},
|
||||
),
|
||||
runtime,
|
||||
)
|
||||
|
||||
assert result.decision_source == "rule_fallback"
|
||||
assert result.next_action == "continue_next_task"
|
||||
assert result.target_message_id == "msg-next-task"
|
||||
assert runtime.called_functions == [STEWARD_RUNTIME_DECISION_FUNCTION_NAME]
|
||||
@@ -2,6 +2,24 @@ from app.services.steward_intent_agent import (
|
||||
STEWARD_INTENT_FUNCTION_NAME,
|
||||
StewardIntentAgent,
|
||||
)
|
||||
from app.schemas.steward import StewardPlanRequest
|
||||
|
||||
|
||||
class _NoToolCallRuntimeChatService:
|
||||
def __init__(self) -> None:
|
||||
self.kwargs = {}
|
||||
|
||||
def complete_with_tool_call(self, messages, **kwargs):
|
||||
self.kwargs = kwargs
|
||||
|
||||
class _Result:
|
||||
tool_call = None
|
||||
|
||||
@staticmethod
|
||||
def calls_as_dicts():
|
||||
return []
|
||||
|
||||
return _Result()
|
||||
|
||||
|
||||
def test_steward_intent_tool_schema_supports_pending_flow_confirmation() -> None:
|
||||
@@ -12,9 +30,16 @@ def test_steward_intent_tool_schema_supports_pending_flow_confirmation() -> None
|
||||
function_schema = schema["function"]
|
||||
assert function_schema["name"] == STEWARD_INTENT_FUNCTION_NAME
|
||||
properties = function_schema["parameters"]["properties"]
|
||||
task_schema = properties["tasks"]["items"]
|
||||
pending_schema = properties["pending_flow_confirmation"]
|
||||
candidate_schema = pending_schema["properties"]["candidate_flows"]["items"]
|
||||
|
||||
assert task_schema["properties"]["requested_action"]["enum"] == [
|
||||
"preview",
|
||||
"save_draft",
|
||||
"submit",
|
||||
]
|
||||
assert "requested_action" in task_schema["required"]
|
||||
assert "pending_flow_confirmation" in properties
|
||||
assert pending_schema["properties"]["status"]["enum"] == ["none", "pending"]
|
||||
assert candidate_schema["properties"]["flow_id"]["enum"] == [
|
||||
@@ -28,3 +53,18 @@ def test_steward_intent_tool_schema_supports_pending_flow_confirmation() -> None
|
||||
"reason",
|
||||
"transport_mode",
|
||||
]
|
||||
|
||||
|
||||
def test_steward_intent_agent_uses_ten_second_timeout_and_three_attempts() -> None:
|
||||
runtime_chat = _NoToolCallRuntimeChatService()
|
||||
agent = StewardIntentAgent(runtime_chat)
|
||||
|
||||
agent.detect(
|
||||
StewardPlanRequest(message="2026-02-20 至 2026-02-23，上海出差，火车，保存草稿。"),
|
||||
base_date=__import__("datetime").date(2026, 6, 24),
|
||||
canonical_fields=["expense_type", "time_range", "location", "reason", "transport_mode"],
|
||||
)
|
||||
|
||||
assert runtime_chat.kwargs["timeout_seconds"] == 10
|
||||
assert runtime_chat.kwargs["max_attempts"] == 3
|
||||
assert runtime_chat.kwargs["use_failure_cooldown"] is False
|
||||
|
||||
@@ -135,6 +135,7 @@ class ApplicationFunctionCallingIntentAgent:
|
||||
"task_type": "expense_application",
|
||||
"title": "北京出差申请",
|
||||
"summary": "明天前往北京出差3天，支撑国网仿生产部署。",
|
||||
"requested_action": "save_draft",
|
||||
"confidence": 0.94,
|
||||
"ontology_fields": {
|
||||
"time_range": "明天",
|
||||
@@ -151,6 +152,52 @@ class ApplicationFunctionCallingIntentAgent:
|
||||
)
|
||||
|
||||
|
||||
class SingleTravelApplicationFunctionCallingIntentAgent:
|
||||
def __init__(self) -> None:
|
||||
self.calls = 0
|
||||
|
||||
def detect(self, request, *, base_date, canonical_fields):
|
||||
self.calls += 1
|
||||
return StewardIntentAgentResult(
|
||||
payload={
|
||||
"thinking_events": [
|
||||
{
|
||||
"stage": "task_split",
|
||||
"title": "识别出差申请草稿",
|
||||
"content": "模型识别到用户要创建上海出差申请，并保存草稿。",
|
||||
}
|
||||
],
|
||||
"tasks": [
|
||||
{
|
||||
"task_type": "expense_application",
|
||||
"title": "上海出差申请",
|
||||
"summary": "2026-02-20 至 2026-02-23 前往上海，国网仿生产服务器部署，火车出行。",
|
||||
"requested_action": "save_draft",
|
||||
"confidence": 0.95,
|
||||
"ontology_fields": {
|
||||
"time_range": "2026-02-20 至 2026-02-23",
|
||||
"location": "上海",
|
||||
"expense_type": "差旅",
|
||||
"reason": "国网仿生产服务器部署",
|
||||
"transport_mode": "火车",
|
||||
},
|
||||
"missing_fields": [],
|
||||
}
|
||||
],
|
||||
"attachment_groups": [],
|
||||
},
|
||||
model_call_traces=[
|
||||
{
|
||||
"slot": "main",
|
||||
"provider": "OpenAI Compatible",
|
||||
"model": "gpt-test",
|
||||
"attempt": 1,
|
||||
"status": "succeeded",
|
||||
}
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class PendingFlowFunctionCallingIntentAgent:
|
||||
def detect(self, request, *, base_date, canonical_fields):
|
||||
return StewardIntentAgentResult(
|
||||
@@ -255,6 +302,17 @@ def _create_steward_test_client_with_db():
|
||||
return TestClient(app), TestingSessionLocal, app
|
||||
|
||||
|
||||
def _build_fast_rule_fallback_steward_planner(_db):
|
||||
return StewardPlannerService(intent_agent=EmptyFunctionCallingIntentAgent())
|
||||
|
||||
|
||||
def _patch_steward_endpoint_planner(monkeypatch) -> None:
|
||||
monkeypatch.setattr(
|
||||
"app.api.v1.endpoints.steward._build_steward_planner",
|
||||
_build_fast_rule_fallback_steward_planner,
|
||||
)
|
||||
|
||||
|
||||
def _build_endpoint_application_claim(
|
||||
*,
|
||||
claim_no: str = "AP-202602-001",
|
||||
@@ -341,6 +399,7 @@ def test_steward_planner_enforces_application_transport_gap_after_function_calli
|
||||
result = StewardPlannerService(intent_agent=ApplicationFunctionCallingIntentAgent()).build_plan(payload)
|
||||
|
||||
assert result.planning_source == "llm_function_call"
|
||||
assert result.tasks[0].requested_action == "save_draft"
|
||||
assert result.tasks[0].missing_fields == ["transport_mode"]
|
||||
gap_events = [event for event in result.thinking_events if event.stage == "business_gap_check"]
|
||||
assert gap_events
|
||||
@@ -356,7 +415,7 @@ def test_steward_planner_returns_pending_flow_confirmation_from_llm() -> None:
|
||||
|
||||
result = StewardPlannerService(intent_agent=PendingFlowFunctionCallingIntentAgent()).build_plan(payload)
|
||||
|
||||
assert result.planning_source == "rule_fallback"
|
||||
assert result.planning_source == "llm_function_call"
|
||||
assert result.next_action == "confirm_flow"
|
||||
assert result.plan_status == "needs_flow_confirmation"
|
||||
assert result.pending_flow_confirmation.status == "pending"
|
||||
@@ -364,12 +423,12 @@ def test_steward_planner_returns_pending_flow_confirmation_from_llm() -> None:
|
||||
"travel_application",
|
||||
"travel_reimbursement",
|
||||
]
|
||||
assert result.candidate_flows[0].ontology_fields["time_range"] == "2026-02-20"
|
||||
assert result.candidate_flows[0].ontology_fields["time_range"] == "2026-02-20 至 2026-02-23"
|
||||
assert result.candidate_flows[0].ontology_fields["location"] == "上海"
|
||||
assert "申请" in result.summary and "报销" in result.summary
|
||||
|
||||
|
||||
def test_steward_planner_skips_llm_for_single_ambiguous_travel_flow() -> None:
|
||||
def test_steward_planner_tries_llm_before_rule_fallback_for_single_ambiguous_travel_flow() -> None:
|
||||
payload = StewardPlanRequest(
|
||||
message="\u0032\u6708\u0032\u0030-\u0032\u0033\u65e5\u53bb\u4e0a\u6d77\u51fa\u5dee\u8f85\u52a9\u56fd\u7f51\u4eff\u751f\u4ea7\u73af\u5883\u90e8\u7f72",
|
||||
client_now_iso="2026-06-15T09:30:00+08:00",
|
||||
@@ -379,7 +438,7 @@ def test_steward_planner_skips_llm_for_single_ambiguous_travel_flow() -> None:
|
||||
|
||||
result = StewardPlannerService(intent_agent=intent_agent).build_plan(payload)
|
||||
|
||||
assert intent_agent.calls == 0
|
||||
assert intent_agent.calls == 1
|
||||
assert result.planning_source == "rule_fallback"
|
||||
assert result.next_action == "confirm_flow"
|
||||
assert result.plan_status == "needs_flow_confirmation"
|
||||
@@ -404,6 +463,37 @@ def test_steward_planner_uses_llm_for_multi_financial_demands() -> None:
|
||||
assert result.model_call_traces[0]["status"] == "succeeded"
|
||||
|
||||
|
||||
def test_steward_planner_uses_llm_for_single_explicit_travel_save_draft() -> None:
|
||||
payload = StewardPlanRequest(
|
||||
message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。",
|
||||
client_now_iso="2026-06-24T14:20:00+08:00",
|
||||
)
|
||||
intent_agent = SingleTravelApplicationFunctionCallingIntentAgent()
|
||||
|
||||
result = StewardPlannerService(intent_agent=intent_agent).build_plan(payload)
|
||||
|
||||
assert intent_agent.calls == 1
|
||||
assert result.planning_source == "llm_function_call"
|
||||
assert result.tasks[0].requested_action == "save_draft"
|
||||
assert result.tasks[0].ontology_fields["time_range"] == "2026-02-20 至 2026-02-23"
|
||||
assert result.tasks[0].ontology_fields["reason"] == "国网仿生产服务器部署"
|
||||
assert result.model_call_traces[0]["status"] == "succeeded"
|
||||
|
||||
|
||||
def test_steward_planner_rule_fallback_keeps_save_draft_action_and_date_range() -> None:
|
||||
payload = StewardPlanRequest(
|
||||
message="2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。",
|
||||
client_now_iso="2026-06-24T14:20:00+08:00",
|
||||
)
|
||||
|
||||
result = StewardPlannerService(intent_agent=EmptyFunctionCallingIntentAgent()).build_plan(payload)
|
||||
|
||||
assert result.planning_source == "rule_fallback"
|
||||
assert result.tasks[0].requested_action == "save_draft"
|
||||
assert result.tasks[0].ontology_fields["time_range"] == "2026-02-20 至 2026-02-23"
|
||||
assert result.tasks[0].ontology_fields["reason"] == "国网仿生产服务器部署"
|
||||
|
||||
|
||||
def test_steward_planner_overrides_llm_direct_application_for_ambiguous_travel_flow() -> None:
|
||||
payload = StewardPlanRequest(
|
||||
message="2月20-23日去上海出差辅助国网仿生产环境部署",
|
||||
@@ -412,7 +502,7 @@ def test_steward_planner_overrides_llm_direct_application_for_ambiguous_travel_f
|
||||
|
||||
result = StewardPlannerService(intent_agent=AmbiguousApplicationFunctionCallingIntentAgent()).build_plan(payload)
|
||||
|
||||
assert result.planning_source == "rule_fallback"
|
||||
assert result.planning_source == "llm_function_call"
|
||||
assert result.next_action == "confirm_flow"
|
||||
assert result.plan_status == "needs_flow_confirmation"
|
||||
assert result.tasks == []
|
||||
@@ -557,6 +647,34 @@ def test_steward_planner_keeps_bare_reimbursement_intent_generic() -> None:
|
||||
assert task.ontology_fields.get("expense_type") == "other"
|
||||
assert "reason" not in task.ontology_fields
|
||||
assert task.missing_fields == ["time_range", "reason"]
|
||||
assert [step.action_type for step in task.action_steps] == [
|
||||
"fill_reimbursement_fields",
|
||||
"build_reimbursement_preview",
|
||||
"validate_required_fields",
|
||||
"create_reimbursement_draft",
|
||||
]
|
||||
assert task.action_steps[-1].status == "blocked"
|
||||
|
||||
|
||||
def test_steward_planner_builds_reimbursement_action_steps() -> None:
|
||||
payload = StewardPlanRequest(
|
||||
message="我要报销昨天客户现场沟通的交通费",
|
||||
user_id="u001",
|
||||
client_now_iso="2026-06-04T09:30:00+08:00",
|
||||
context_json={"review_form_values": {"amount": "128.50"}},
|
||||
)
|
||||
|
||||
result = StewardPlannerService().build_plan(payload)
|
||||
|
||||
assert result.tasks[0].task_type == "reimbursement"
|
||||
assert [step.action_type for step in result.tasks[0].action_steps] == [
|
||||
"fill_reimbursement_fields",
|
||||
"build_reimbursement_preview",
|
||||
"validate_required_fields",
|
||||
"create_reimbursement_draft",
|
||||
]
|
||||
assert result.tasks[0].action_steps[0].payload["ontology_fields"]["amount"] == "128.50"
|
||||
assert result.tasks[0].action_steps[-1].status == "planned"
|
||||
|
||||
|
||||
def test_steward_planner_treats_future_travel_without_apply_word_as_application() -> None:
|
||||
@@ -636,7 +754,8 @@ def test_steward_planner_builds_travel_attachment_group_with_exclusions() -> Non
|
||||
assert len(attachment_actions) == 1
|
||||
|
||||
|
||||
def test_steward_stream_endpoint_emits_thinking_before_plan() -> None:
|
||||
def test_steward_stream_endpoint_emits_thinking_before_plan(monkeypatch) -> None:
|
||||
_patch_steward_endpoint_planner(monkeypatch)
|
||||
client = TestClient(create_app())
|
||||
|
||||
with client.stream(
|
||||
@@ -660,7 +779,8 @@ def test_steward_stream_endpoint_emits_thinking_before_plan() -> None:
|
||||
assert events[-1]["data"]["tasks"][0]["ontology_fields"]["time_range"] == "2026-06-03"
|
||||
|
||||
|
||||
def test_steward_plan_endpoint_persists_application_and_reimbursement_state() -> None:
|
||||
def test_steward_plan_endpoint_persists_application_and_reimbursement_state(monkeypatch) -> None:
|
||||
_patch_steward_endpoint_planner(monkeypatch)
|
||||
client = TestClient(create_app())
|
||||
|
||||
response = client.post(
|
||||
@@ -685,7 +805,8 @@ def test_steward_plan_endpoint_persists_application_and_reimbursement_state() ->
|
||||
assert all("invented_field" not in flow["fields"] for flow in state["flows"].values())
|
||||
|
||||
|
||||
def test_steward_plan_endpoint_queries_applications_before_ambiguous_travel_choice() -> None:
|
||||
def test_steward_plan_endpoint_queries_applications_before_ambiguous_travel_choice(monkeypatch) -> None:
|
||||
_patch_steward_endpoint_planner(monkeypatch)
|
||||
client, SessionLocal, app = _create_steward_test_client_with_db()
|
||||
try:
|
||||
response = client.post(
|
||||
|
||||
663
server/uv.lock
generated
663
server/uv.lock
generated
@@ -933,6 +933,12 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12", size = 7484, upload-time = "2025-10-18T21:55:41.639Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "jieba"
|
||||
version = "0.42.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/c6/cb/18eeb235f833b726522d7ebed54f2278ce28ba9438e3135ab0278d9792a2/jieba-0.42.1.tar.gz", hash = "sha256:055ca12f62674fafed09427f176506079bc135638a14e23e25be909131928db2", size = 19214172, upload-time = "2020-01-20T14:27:23.5Z" }
|
||||
|
||||
[[package]]
|
||||
name = "json-repair"
|
||||
version = "0.59.10"
|
||||
@@ -942,6 +948,143 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ee/87/49b20c6b81493d55c311f711ed87319d0fbad8bd0bbfbe36e52103af36bd/json_repair-0.59.10-py3-none-any.whl", hash = "sha256:5468fa3eaadcc9b4a5646776bc4176e2fe5f374b5848a15f468cce3b60e3db0e", size = 47742, upload-time = "2026-05-14T06:41:49.812Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "jsonpatch"
|
||||
version = "1.33"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jsonpointer" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/42/78/18813351fe5d63acad16aec57f94ec2b70a09e53ca98145589e185423873/jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c", size = 21699, upload-time = "2023-06-26T12:07:29.144Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/73/07/02e16ed01e04a374e644b575638ec7987ae846d25ad97bcc9945a3ee4b0e/jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade", size = 12898, upload-time = "2023-06-16T21:01:28.466Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "jsonpointer"
|
||||
version = "3.1.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/18/c7/af399a2e7a67fd18d63c40c5e62d3af4e67b836a2107468b6a5ea24c4304/jsonpointer-3.1.1.tar.gz", hash = "sha256:0b801c7db33a904024f6004d526dcc53bbb8a4a0f4e32bfd10beadf60adf1900", size = 9068, upload-time = "2026-03-23T22:32:32.458Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/9e/6a/a83720e953b1682d2d109d3c2dbb0bc9bf28cc1cbc205be4ef4be5da709d/jsonpointer-3.1.1-py3-none-any.whl", hash = "sha256:8ff8b95779d071ba472cf5bc913028df06031797532f08a7d5b602d8b2a488ca", size = 7659, upload-time = "2026-03-23T22:32:31.568Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "1.4.8"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jsonpatch" },
|
||||
{ name = "langchain-protocol" },
|
||||
{ name = "langsmith" },
|
||||
{ name = "packaging" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "pyyaml" },
|
||||
{ name = "tenacity" },
|
||||
{ name = "typing-extensions" },
|
||||
{ name = "uuid-utils" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/12/e3/bea6d0080acf183332f24dcd74c208aee5857cf8f783c3fb0bd86027d8fb/langchain_core-1.4.8.tar.gz", hash = "sha256:5bf1f8411077c904182ad8f975943d36adcbf579c4e017b3a118b719229ebf9a", size = 957974, upload-time = "2026-06-18T19:39:23.636Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/13/d6/bdf6f0481cc57ef300d6b1eb48cf1400c0409be715d6eb3cabadd1142a09/langchain_core-1.4.8-py3-none-any.whl", hash = "sha256:d84c28b05e3ba8d4271d0827aad5b592ccdaaf986e76768c23503f0a2045e8aa", size = 557416, upload-time = "2026-06-18T19:39:21.902Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langchain-protocol"
|
||||
version = "0.0.18"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d2/59/b5959aea96faa9146e2e49a7a22882b3528c62efafe9a6a95beab30c2305/langchain_protocol-0.0.18.tar.gz", hash = "sha256:ec3e11782f1ed0c9db38e5a9ed01b0e7a0d3fba406faa8aef6594b73c56a63e6", size = 6150, upload-time = "2026-06-18T17:08:26.959Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/99/2e/d82db9eec13ad0f72e7aaad5c4bc730ab111934fdc83c85523206eb9b0a0/langchain_protocol-0.0.18-py3-none-any.whl", hash = "sha256:70b53a86fbf9cedc863555effe44da192ab02d556ddbf2cf95b8873adcf41b5a", size = 7221, upload-time = "2026-06-18T17:08:25.996Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.2.6"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langgraph-checkpoint" },
|
||||
{ name = "langgraph-prebuilt" },
|
||||
{ name = "langgraph-sdk" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "xxhash" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/02/7a/ea09b05bb0cbddfa43bd34fc581357e87fc3f21a751cc0d419688c3106da/langgraph-1.2.6.tar.gz", hash = "sha256:f9b45a34f13930c94d96cdb76277447ad2cc70ec2d18cd2764d7fdadb36cdc1b", size = 714400, upload-time = "2026-06-18T20:58:21.514Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/89/32/772db1b00a9fe42f50320d1aa20caefb76e621eff1f7218b9918093d631d/langgraph-1.2.6-py3-none-any.whl", hash = "sha256:1cf94d3ca124f84f77ce408fa1b06c3dee680a8aafffe364a8fd5d7d03eb8695", size = 246132, upload-time = "2026-06-18T20:58:20.335Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.1.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "ormsgpack" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/83/47/886af6f886f0bff2273164a45f008694e48a96ff3cd25ff0228f2aa9480e/langgraph_checkpoint-4.1.1.tar.gz", hash = "sha256:6c2bdb530c91f91d7d9c1bd100925d0fc4f498d418c17f3587d1526279482a25", size = 184020, upload-time = "2026-05-22T16:57:38.503Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/bd/b4/71425e3e38be92611300b9cc5e46a5bf98ab23f5ea8a75b73d02a2f1413c/langgraph_checkpoint-4.1.1-py3-none-any.whl", hash = "sha256:25d29144b082827218e7bc3f1e9b0566a4bb007895cd6cc26f66a8428739f56e", size = 56212, upload-time = "2026-05-22T16:57:37.203Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-prebuilt"
|
||||
version = "1.1.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langgraph-checkpoint" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/29/66/ed9b93f56bc17ef22d551892f0ac2b225a97fe0fcf23a511b857f70d590b/langgraph_prebuilt-1.1.0.tar.gz", hash = "sha256:3c579cf6eed2d17f9c157c2d0fcaddcd8688524e7022d3b22b37a3bf4589d528", size = 178833, upload-time = "2026-05-12T03:37:49.332Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/e9/43/3fe1a700b8490ed02679cdbbc8c915eb23a092faf496c9c1118abcd10be3/langgraph_prebuilt-1.1.0-py3-none-any.whl", hash = "sha256:51e311747d755b751d5c6b39b0c1446124d3a7643d2515017e6714b323508fc9", size = 41043, upload-time = "2026-05-12T03:37:48.007Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-sdk"
|
||||
version = "0.4.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langchain-protocol" },
|
||||
{ name = "orjson" },
|
||||
{ name = "websockets" },
|
||||
]
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]
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||||
|
||||
@@ -549,59 +549,156 @@
|
||||
}
|
||||
|
||||
.associate-hint {
|
||||
margin: 0;
|
||||
margin: 0 0 2px 0;
|
||||
color: #64748b;
|
||||
font-size: 13px;
|
||||
line-height: 1.4;
|
||||
}
|
||||
|
||||
.receipt-checkbox-list,
|
||||
.draft-choice-list {
|
||||
max-height: 360px;
|
||||
max-height: 340px;
|
||||
display: grid;
|
||||
gap: 8px;
|
||||
overflow-y: auto;
|
||||
padding: 1px;
|
||||
}
|
||||
|
||||
.receipt-checkbox-list :deep(.el-checkbox),
|
||||
.draft-choice {
|
||||
min-height: 50px;
|
||||
display: flex !important;
|
||||
min-height: 52px;
|
||||
align-items: center;
|
||||
margin-right: 0;
|
||||
padding: 9px 10px;
|
||||
border: 1px solid #dbe4ee;
|
||||
padding: 10px 14px;
|
||||
border: 1px solid #e2e8f0;
|
||||
border-radius: 4px;
|
||||
background: #fff;
|
||||
transition: all 150ms ease;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
.receipt-checkbox-list :deep(.el-checkbox:hover),
|
||||
.draft-choice:hover {
|
||||
border-color: #cbd5e1;
|
||||
background: #f8fafc;
|
||||
}
|
||||
|
||||
.receipt-checkbox-list :deep(.el-checkbox.is-checked) {
|
||||
border-color: var(--theme-primary);
|
||||
background: rgba(58, 124, 165, 0.04);
|
||||
}
|
||||
|
||||
.receipt-checkbox-list :deep(.el-checkbox__label) {
|
||||
flex: 1;
|
||||
display: grid;
|
||||
gap: 3px;
|
||||
gap: 2px;
|
||||
color: #0f172a;
|
||||
font-weight: 750;
|
||||
font-size: 13px;
|
||||
font-weight: 600;
|
||||
line-height: 1.35;
|
||||
}
|
||||
|
||||
.receipt-checkbox-list small,
|
||||
.draft-choice small {
|
||||
color: #64748b;
|
||||
font-size: 12px;
|
||||
font-weight: 650;
|
||||
font-size: 11.5px;
|
||||
font-weight: 400;
|
||||
line-height: 1.35;
|
||||
}
|
||||
|
||||
.draft-choice {
|
||||
display: grid;
|
||||
grid-template-columns: auto minmax(0, 1fr);
|
||||
gap: 9px;
|
||||
gap: 10px;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.draft-choice.active {
|
||||
border-color: rgba(58, 124, 165, .42);
|
||||
background: rgba(58, 124, 165, .07);
|
||||
border-color: var(--theme-primary);
|
||||
background: rgba(58, 124, 165, 0.04);
|
||||
}
|
||||
|
||||
.draft-choice span {
|
||||
display: grid;
|
||||
gap: 3px;
|
||||
gap: 2px;
|
||||
}
|
||||
|
||||
.draft-choice strong {
|
||||
color: #0f172a;
|
||||
font-size: 13px;
|
||||
font-weight: 600;
|
||||
line-height: 1.35;
|
||||
}
|
||||
|
||||
/* Global styles for the association dialog */
|
||||
:global(.receipt-associate-dialog.el-dialog) {
|
||||
border-radius: 6px;
|
||||
box-shadow: 0 16px 36px rgba(15, 23, 42, 0.12);
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__header) {
|
||||
padding: 20px 24px 12px 24px;
|
||||
margin-right: 0;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__headerbtn) {
|
||||
top: 20px;
|
||||
right: 24px;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__title) {
|
||||
font-size: 15px;
|
||||
font-weight: 600;
|
||||
color: #0f172a;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__body) {
|
||||
padding: 0 24px 20px 24px;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__footer) {
|
||||
padding: 12px 24px 16px 24px;
|
||||
background: #f8fafc;
|
||||
border-top: 1px solid #e2e8f0;
|
||||
display: flex;
|
||||
justify-content: flex-end;
|
||||
gap: 8px;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__footer .apply-btn),
|
||||
:global(.receipt-associate-dialog .el-dialog__footer .ghost-btn) {
|
||||
min-height: 36px;
|
||||
height: 36px;
|
||||
padding: 0 16px;
|
||||
border-radius: 4px;
|
||||
font-size: 13px;
|
||||
font-weight: 500;
|
||||
transition: all 150ms ease;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__footer .ghost-btn) {
|
||||
border-color: #cbd5e1;
|
||||
color: #334155;
|
||||
background: #fff;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__footer .ghost-btn:hover) {
|
||||
background: #f8fafc;
|
||||
border-color: #94a3b8;
|
||||
color: #0f172a;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__footer .apply-btn) {
|
||||
background: var(--theme-primary);
|
||||
border-color: var(--theme-primary);
|
||||
color: #fff;
|
||||
}
|
||||
|
||||
:global(.receipt-associate-dialog .el-dialog__footer .apply-btn:hover:not(:disabled)) {
|
||||
background: var(--theme-primary-active);
|
||||
border-color: var(--theme-primary-active);
|
||||
box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);
|
||||
}
|
||||
|
||||
@media (max-width: 1180px) {
|
||||
|
||||
@@ -35,7 +35,20 @@ import { useWorkbenchAiMessageActions } from './useWorkbenchAiMessageActions.js'
|
||||
import { useWorkbenchAiMessageExpansion } from './useWorkbenchAiMessageExpansion.js'
|
||||
import { useWorkbenchAiSessionCommands } from './useWorkbenchAiSessionCommands.js'
|
||||
import { useWorkbenchAiStewardFlow } from './useWorkbenchAiStewardFlow.js'
|
||||
import { isReimbursementCreationIntent } from './workbenchAiApplicationGateModel.js'
|
||||
import {
|
||||
isReimbursementCreationIntent
|
||||
} from './workbenchAiApplicationGateModel.js'
|
||||
import {
|
||||
buildRuleFallbackWorkbenchAiIntentPlan,
|
||||
normalizeWorkbenchAiIntentPlan,
|
||||
resolveExecutableTravelApplicationPlan,
|
||||
shouldRequestWorkbenchAiIntentPlan
|
||||
} from './workbenchAiIntentPlannerModel.js'
|
||||
import {
|
||||
buildInitialModelPlanningThinkingEvents,
|
||||
buildModelPlanningProgressSchedule,
|
||||
mergeWorkbenchAiThinkingEvents
|
||||
} from './workbenchAiPlanningThinkingModel.js'
|
||||
|
||||
const AI_SEARCH_CONVERSATION_ID = 'ai-search'
|
||||
const INLINE_ANSWER_STREAM_CHUNK_SIZE = 6
|
||||
@@ -251,11 +264,16 @@ export function usePersonalWorkbenchAiMode(props, emit) {
|
||||
applicationFlow,
|
||||
assistantDraft,
|
||||
attachmentFlow,
|
||||
conversationMessages,
|
||||
createInlineMessage,
|
||||
emit,
|
||||
expenseFlow,
|
||||
focusAiModeInput,
|
||||
hasInlineAttachmentOcrDetails,
|
||||
persistCurrentConversation,
|
||||
replaceInlineMessage,
|
||||
resolveLatestInlineUserPrompt,
|
||||
scrollInlineConversationToBottom,
|
||||
selectedFiles,
|
||||
startInlineConversation,
|
||||
toast,
|
||||
@@ -560,6 +578,131 @@ export function usePersonalWorkbenchAiMode(props, emit) {
|
||||
return false
|
||||
}
|
||||
|
||||
function isModelPlannedReimbursementTask(modelPlan = {}) {
|
||||
const tasks = Array.isArray(modelPlan?.tasks) ? modelPlan.tasks : []
|
||||
return tasks.some((task) => {
|
||||
const taskType = String(task?.task_type || task?.taskType || '').trim()
|
||||
const assignedAgent = String(task?.assigned_agent || task?.assignedAgent || '').trim()
|
||||
return taskType === 'reimbursement' || assignedAgent === 'reimbursement_assistant'
|
||||
})
|
||||
}
|
||||
|
||||
function updateModelPlanningThinkingEvent(messageId, event) {
|
||||
const message = conversationMessages.value.find((item) => item.id === messageId)
|
||||
if (!message) {
|
||||
return
|
||||
}
|
||||
const currentPlan = message.stewardPlan || {}
|
||||
message.stewardPlan = {
|
||||
...currentPlan,
|
||||
streamStatus: 'streaming',
|
||||
thinkingEvents: mergeWorkbenchAiThinkingEvents(resolveInlineThinkingEvents(message), [event])
|
||||
}
|
||||
persistCurrentConversation()
|
||||
scrollInlineConversationToBottom({ force: inlineConversationAutoScrollPinned.value })
|
||||
}
|
||||
|
||||
function startModelPlanningProgressUpdates(messageId) {
|
||||
const timerIds = buildModelPlanningProgressSchedule().map(({ delayMs, event }) => (
|
||||
globalThis.setTimeout(() => {
|
||||
updateModelPlanningThinkingEvent(messageId, event)
|
||||
}, delayMs)
|
||||
))
|
||||
return () => {
|
||||
timerIds.forEach((timerId) => globalThis.clearTimeout(timerId))
|
||||
}
|
||||
}
|
||||
|
||||
function startModelPlanningConversation(cleanPrompt, entry = {}) {
|
||||
if (conversationId.value === AI_SEARCH_CONVERSATION_ID) {
|
||||
conversationId.value = ''
|
||||
conversationMessages.value = []
|
||||
activeConversationTitle.value = ''
|
||||
}
|
||||
activateInlineConversation({
|
||||
title: entry.label || cleanPrompt.slice(0, 18) || '新对话'
|
||||
})
|
||||
inlineConversationAutoScrollPinned.value = true
|
||||
conversationMessages.value.push(createInlineMessage('user', cleanPrompt))
|
||||
assistantDraft.value = ''
|
||||
removeWorkbenchDateTag()
|
||||
closeWorkbenchDatePicker()
|
||||
filesFlow.clearAiModeFiles()
|
||||
const pendingMessage = createInlineMessage('assistant', '正在识别意图，准备拆解申请、报销和附件任务。', {
|
||||
pending: true,
|
||||
stewardPlan: {
|
||||
streamStatus: 'streaming',
|
||||
thinkingEvents: buildInitialModelPlanningThinkingEvents()
|
||||
}
|
||||
})
|
||||
conversationMessages.value.push(pendingMessage)
|
||||
scrollInlineConversationToBottom()
|
||||
persistCurrentConversation()
|
||||
return pendingMessage
|
||||
}
|
||||
|
||||
function startModelPlannedApplicationPreview(travelApplicationRequest, plannerPendingMessage = null) {
|
||||
void applicationFlow.startAiApplicationPreview(
|
||||
travelApplicationRequest.expenseType,
|
||||
travelApplicationRequest.expenseTypeLabel,
|
||||
travelApplicationRequest.sourceText,
|
||||
{
|
||||
userMessage: travelApplicationRequest.sourceText,
|
||||
pushUserMessage: !plannerPendingMessage,
|
||||
pendingMessageId: plannerPendingMessage?.id,
|
||||
ontologyFields: travelApplicationRequest.ontologyFields,
|
||||
autoSubmit: travelApplicationRequest.autoSubmit,
|
||||
autoSaveDraft: travelApplicationRequest.autoSaveDraft
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
async function executeModelPlannedWorkbenchIntent(cleanPrompt, entry = {}, files = []) {
|
||||
let intentPlan = null
|
||||
let modelPlan = null
|
||||
const plannerPendingMessage = startModelPlanningConversation(cleanPrompt, entry)
|
||||
const stopPlanningProgressUpdates = startModelPlanningProgressUpdates(plannerPendingMessage.id)
|
||||
sending.value = true
|
||||
try {
|
||||
modelPlan = await stewardFlow.resolveInlineExecutionPlan(cleanPrompt, entry, files, {
|
||||
pendingMessageId: plannerPendingMessage.id
|
||||
})
|
||||
intentPlan = normalizeWorkbenchAiIntentPlan(modelPlan, { prompt: cleanPrompt })
|
||||
} catch (error) {
|
||||
console.warn('AI mode intent planner failed, using local fallback:', error)
|
||||
const rulePlan = buildRuleFallbackWorkbenchAiIntentPlan(cleanPrompt)
|
||||
const ruleRequest = resolveExecutableTravelApplicationPlan(rulePlan)
|
||||
if (ruleRequest) {
|
||||
sending.value = false
|
||||
startModelPlannedApplicationPreview(ruleRequest, plannerPendingMessage)
|
||||
return
|
||||
}
|
||||
} finally {
|
||||
stopPlanningProgressUpdates()
|
||||
sending.value = false
|
||||
}
|
||||
|
||||
const travelApplicationRequest = resolveExecutableTravelApplicationPlan(intentPlan)
|
||||
if (travelApplicationRequest) {
|
||||
startModelPlannedApplicationPreview(travelApplicationRequest, plannerPendingMessage)
|
||||
return
|
||||
}
|
||||
|
||||
if (isModelPlannedReimbursementTask(modelPlan) || isReimbursementCreationIntent(cleanPrompt)) {
|
||||
replaceInlineMessage(plannerPendingMessage.id, createInlineMessage('assistant', '已识别为报销任务，正在进入报销流程。', {
|
||||
id: plannerPendingMessage.id,
|
||||
stewardPlan: {
|
||||
streamStatus: 'completed',
|
||||
thinkingEvents: resolveInlineThinkingEvents(plannerPendingMessage).map((item) => ({ ...item, status: 'completed' }))
|
||||
}
|
||||
}))
|
||||
void expenseFlow.startAiReimbursementAssociationGate(cleanPrompt, entry.label || cleanPrompt)
|
||||
return
|
||||
}
|
||||
|
||||
void stewardFlow.requestInlineAssistantReply(cleanPrompt, entry, files, { pendingMessageId: plannerPendingMessage.id })
|
||||
}
|
||||
|
||||
function handleAiAnswerMarkdownClick(event) {
|
||||
const target = event?.target
|
||||
const link = target?.closest?.('a[href^="#ai-open-document-detail:"], a[href^="#ai-open-application-detail:"]')
|
||||
@@ -594,6 +737,11 @@ export function usePersonalWorkbenchAiMode(props, emit) {
|
||||
return
|
||||
}
|
||||
|
||||
if (shouldRequestWorkbenchAiIntentPlan(cleanPrompt)) {
|
||||
void executeModelPlannedWorkbenchIntent(cleanPrompt, entry, files)
|
||||
return
|
||||
}
|
||||
|
||||
if (isReimbursementCreationIntent(cleanPrompt)) {
|
||||
void expenseFlow.startAiReimbursementAssociationGate(cleanPrompt, entry.label || '我要报销')
|
||||
return
|
||||
|
||||
@@ -2,6 +2,7 @@ import {
|
||||
AI_APPLICATION_ACTION_SAVE_DRAFT,
|
||||
AI_APPLICATION_ACTION_SUBMIT
|
||||
} from '../../services/aiApplicationPreviewActions.js'
|
||||
import { executeStewardAction } from '../../services/steward.js'
|
||||
import { buildAiDocumentDetailRequest } from '../../utils/aiDocumentDetailReference.js'
|
||||
import {
|
||||
mergeComposerPrefill,
|
||||
@@ -25,11 +26,16 @@ export function useWorkbenchAiActionRouter({
|
||||
applicationFlow,
|
||||
assistantDraft,
|
||||
attachmentFlow,
|
||||
conversationMessages,
|
||||
createInlineMessage,
|
||||
emit,
|
||||
expenseFlow,
|
||||
focusAiModeInput,
|
||||
hasInlineAttachmentOcrDetails,
|
||||
persistCurrentConversation,
|
||||
replaceInlineMessage,
|
||||
resolveLatestInlineUserPrompt,
|
||||
scrollInlineConversationToBottom,
|
||||
selectedFiles,
|
||||
startInlineConversation,
|
||||
toast,
|
||||
@@ -45,6 +51,9 @@ export function useWorkbenchAiActionRouter({
|
||||
|
||||
const actionType = String(action?.action_type || '').trim()
|
||||
const actionPayload = action?.payload && typeof action.payload === 'object' ? action.payload : {}
|
||||
if (actionPayload.steward_execute_action) {
|
||||
return executeInlineStewardAction(action, sourceMessage)
|
||||
}
|
||||
if (actionType === AI_ATTACHMENT_OCR_DETAIL_ACTION) {
|
||||
if (!hasInlineAttachmentOcrDetails(sourceMessage)) {
|
||||
toast('当前消息没有可查看的附件识别明细。')
|
||||
@@ -162,6 +171,191 @@ export function useWorkbenchAiActionRouter({
|
||||
}, action?.payload?.carry_files ? Array.from(selectedFiles.value) : [])
|
||||
}
|
||||
|
||||
async function executeInlineStewardAction(action = {}, sourceMessage = null) {
|
||||
const actionPayload = action?.payload && typeof action.payload === 'object' ? action.payload : {}
|
||||
const actionType = String(actionPayload.steward_action_type || '').trim()
|
||||
if (!actionType || !actionPayload.steward_current_task) {
|
||||
toast('当前动作缺少可执行任务快照，请重新发起规划。')
|
||||
return false
|
||||
}
|
||||
if (sourceMessage?.suggestedActionsLocked) {
|
||||
return true
|
||||
}
|
||||
if (sourceMessage) {
|
||||
sourceMessage.suggestedActionsLocked = true
|
||||
}
|
||||
|
||||
const pendingMessage = appendStewardActionMessage(
|
||||
`正在执行：${String(action.label || '小财管家动作').trim() || '小财管家动作'}...`,
|
||||
{ pending: true }
|
||||
)
|
||||
|
||||
try {
|
||||
let precheckResult = null
|
||||
if (actionType === 'submit_application') {
|
||||
precheckResult = await executeStewardAction(
|
||||
buildStewardActionExecutePayload(action, 'run_duplicate_precheck')
|
||||
)
|
||||
if (!isSuccessfulStewardPrecheck(precheckResult)) {
|
||||
finalizeStewardActionMessage(pendingMessage, buildStewardActionResultText(precheckResult), {
|
||||
suggestedActions: []
|
||||
})
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
const contextJson = precheckResult
|
||||
? { precheck_result: precheckResult.result_payload || precheckResult.resultPayload || {} }
|
||||
: {}
|
||||
const result = await executeStewardAction(
|
||||
buildStewardActionExecutePayload(action, actionType, contextJson)
|
||||
)
|
||||
finalizeStewardActionMessage(pendingMessage, buildStewardActionResultText(result), {
|
||||
suggestedActions: buildStewardActionResultActions(result)
|
||||
})
|
||||
return true
|
||||
} catch (error) {
|
||||
if (sourceMessage) {
|
||||
sourceMessage.suggestedActionsLocked = false
|
||||
}
|
||||
finalizeStewardActionMessage(
|
||||
pendingMessage,
|
||||
`动作执行失败：${String(error?.message || '请稍后重试。').trim()}`
|
||||
)
|
||||
return false
|
||||
}
|
||||
}
|
||||
|
||||
function buildStewardActionExecutePayload(action = {}, actionType = '', contextJson = {}) {
|
||||
const actionPayload = action?.payload && typeof action.payload === 'object' ? action.payload : {}
|
||||
const currentTask = actionPayload.steward_current_task || null
|
||||
return {
|
||||
action_type: actionType,
|
||||
message: resolveStewardActionMessage(action),
|
||||
plan_id: String(actionPayload.steward_plan_id || '').trim(),
|
||||
conversation_id: String(actionPayload.conversation_id || actionPayload.conversationId || '').trim() || null,
|
||||
task: currentTask,
|
||||
action_step: resolveStewardActionStep(actionPayload, actionType),
|
||||
confirmed: true,
|
||||
context_json: contextJson,
|
||||
client_trace_id: buildStewardActionClientTraceId(actionPayload, actionType)
|
||||
}
|
||||
}
|
||||
|
||||
function resolveStewardActionMessage(action = {}) {
|
||||
const actionPayload = action?.payload && typeof action.payload === 'object' ? action.payload : {}
|
||||
return String(
|
||||
actionPayload.carry_text ||
|
||||
actionPayload.original_message ||
|
||||
resolveLatestInlineUserPrompt?.() ||
|
||||
action.label ||
|
||||
''
|
||||
).trim()
|
||||
}
|
||||
|
||||
function resolveStewardActionStep(actionPayload = {}, actionType = '') {
|
||||
if (String(actionPayload.steward_action_step?.action_type || '').trim() === actionType) {
|
||||
return actionPayload.steward_action_step
|
||||
}
|
||||
const steps = Array.isArray(actionPayload.steward_current_task?.action_steps)
|
||||
? actionPayload.steward_current_task.action_steps
|
||||
: []
|
||||
return steps.find((step) => String(step?.action_type || '').trim() === actionType) || null
|
||||
}
|
||||
|
||||
function buildStewardActionClientTraceId(actionPayload = {}, actionType = '') {
|
||||
const planId = String(actionPayload.steward_plan_id || 'steward').trim() || 'steward'
|
||||
const taskId = String(actionPayload.steward_action_task_id || actionPayload.steward_current_task?.task_id || 'task').trim() || 'task'
|
||||
return `${planId}:${taskId}:${actionType}:${Date.now()}`
|
||||
}
|
||||
|
||||
function isSuccessfulStewardPrecheck(result = {}) {
|
||||
const status = String(result?.status || '').trim()
|
||||
const payload = result?.result_payload || result?.resultPayload || {}
|
||||
return status === 'succeeded' && payload?.blocking !== true
|
||||
}
|
||||
|
||||
function appendStewardActionMessage(content, options = {}) {
|
||||
if (!conversationMessages?.value || typeof createInlineMessage !== 'function') {
|
||||
toast(String(content || '').trim())
|
||||
return null
|
||||
}
|
||||
const message = createInlineMessage('assistant', content, options)
|
||||
conversationMessages.value.push(message)
|
||||
persistStewardActionConversation()
|
||||
return message
|
||||
}
|
||||
|
||||
function finalizeStewardActionMessage(pendingMessage, content, options = {}) {
|
||||
if (!conversationMessages?.value || typeof createInlineMessage !== 'function') {
|
||||
toast(String(content || '').trim())
|
||||
return
|
||||
}
|
||||
const finalMessage = createInlineMessage('assistant', content, {
|
||||
...options,
|
||||
id: pendingMessage?.id
|
||||
})
|
||||
if (pendingMessage?.id && typeof replaceInlineMessage === 'function') {
|
||||
replaceInlineMessage(pendingMessage.id, finalMessage)
|
||||
} else if (pendingMessage?.id) {
|
||||
const index = conversationMessages.value.findIndex((item) => item.id === pendingMessage.id)
|
||||
if (index >= 0) {
|
||||
conversationMessages.value.splice(index, 1, finalMessage)
|
||||
} else {
|
||||
conversationMessages.value.push(finalMessage)
|
||||
}
|
||||
} else {
|
||||
conversationMessages.value.push(finalMessage)
|
||||
}
|
||||
persistStewardActionConversation()
|
||||
}
|
||||
|
||||
function persistStewardActionConversation() {
|
||||
persistCurrentConversation?.()
|
||||
scrollInlineConversationToBottom?.({ force: true })
|
||||
}
|
||||
|
||||
function buildStewardActionResultText(result = {}) {
|
||||
const status = String(result?.status || '').trim()
|
||||
const message = String(result?.message || '').trim()
|
||||
if (status === 'succeeded') {
|
||||
return message || '动作已完成。'
|
||||
}
|
||||
if (status === 'needs_confirmation') {
|
||||
return message || '这一步还需要您确认后才能继续。'
|
||||
}
|
||||
if (status === 'blocked') {
|
||||
return ['这一步暂时不能继续。', message].filter(Boolean).join('\n\n')
|
||||
}
|
||||
if (status === 'failed') {
|
||||
return `动作执行失败：${message || '请稍后重试。'}`
|
||||
}
|
||||
return message || '动作已返回结果。'
|
||||
}
|
||||
|
||||
function buildStewardActionResultActions(result = {}) {
|
||||
if (String(result?.status || '').trim() !== 'succeeded') {
|
||||
return []
|
||||
}
|
||||
const resultPayload = result?.result_payload || result?.resultPayload || {}
|
||||
const draftPayload = resultPayload?.draft_payload || resultPayload?.draftPayload || resultPayload
|
||||
const claimNo = String(draftPayload?.claim_no || draftPayload?.claimNo || '').trim()
|
||||
const claimId = String(draftPayload?.claim_id || draftPayload?.claimId || '').trim()
|
||||
if (!claimNo && !claimId) {
|
||||
return []
|
||||
}
|
||||
return [{
|
||||
label: claimNo ? `查看单据 ${claimNo}` : '查看单据',
|
||||
description: '打开刚生成的单据详情。',
|
||||
icon: 'mdi mdi-open-in-new',
|
||||
action_type: 'open_application_detail',
|
||||
payload: {
|
||||
claim_id: claimId,
|
||||
claim_no: claimNo
|
||||
}
|
||||
}]
|
||||
}
|
||||
|
||||
return {
|
||||
handleInlineSuggestedAction
|
||||
}
|
||||
|
||||
@@ -27,6 +27,10 @@ import {
|
||||
extractInlineApplicationDraftPayload
|
||||
} from './workbenchAiApplicationPreviewModel.js'
|
||||
import { AI_ATTACHMENT_ASSOCIATION_CONFIRM_ACTION } from './workbenchAiMessageModel.js'
|
||||
import {
|
||||
completeWorkbenchAiThinkingEvents,
|
||||
mergeWorkbenchAiThinkingEvents
|
||||
} from './workbenchAiPlanningThinkingModel.js'
|
||||
import {
|
||||
isOrphanInlineApplicationPreviewMessage,
|
||||
resolveInlineApplicationPreviewTextAction,
|
||||
@@ -202,6 +206,26 @@ export function useWorkbenchAiApplicationPreviewFlow({
|
||||
].join('\n\n')
|
||||
}
|
||||
|
||||
function hasSavedInlineApplicationDraft(message = {}, options = {}) {
|
||||
const draftPayload = message?.draftPayload || options.draftPayload || null
|
||||
if (!draftPayload || typeof draftPayload !== 'object') {
|
||||
return false
|
||||
}
|
||||
const claimId = String(draftPayload.claim_id || draftPayload.claimId || '').trim()
|
||||
const claimNo = String(draftPayload.claim_no || draftPayload.claimNo || '').trim()
|
||||
const status = String(draftPayload.status || '').trim().toLowerCase()
|
||||
return Boolean((claimId || claimNo) && status !== 'submitted')
|
||||
}
|
||||
|
||||
function isContextualInlineApplicationSubmitText(text = '') {
|
||||
const normalized = String(text || '').replace(/\s+/g, '').trim()
|
||||
return Boolean(
|
||||
normalized &&
|
||||
/提交/.test(normalized) &&
|
||||
/(这个|这张|当前|上面|上述|刚才|申请单|单据|草稿|领导|审核|审批)/.test(normalized)
|
||||
)
|
||||
}
|
||||
|
||||
function resolveLatestInlineApplicationPreviewMessage() {
|
||||
return resolveLatestApplicationPreviewMessage(conversationMessages.value)
|
||||
}
|
||||
@@ -334,7 +358,12 @@ export function useWorkbenchAiApplicationPreviewFlow({
|
||||
return true
|
||||
}
|
||||
|
||||
if (isSubmit && !options.confirmed) {
|
||||
const shouldSubmitSavedDraftDirectly = isSubmit &&
|
||||
!options.confirmed &&
|
||||
hasSavedInlineApplicationDraft(targetMessage, options) &&
|
||||
isContextualInlineApplicationSubmitText(userText)
|
||||
|
||||
if (isSubmit && !options.confirmed && !shouldSubmitSavedDraftDirectly) {
|
||||
requestInlineApplicationSubmitConfirmation(targetMessage, { ...options, userText })
|
||||
return true
|
||||
}
|
||||
@@ -474,11 +503,16 @@ export function useWorkbenchAiApplicationPreviewFlow({
|
||||
pushInlineUserMessage(options.userMessage || '确认发起出差申请')
|
||||
}
|
||||
|
||||
const existingPendingMessage = options.pendingMessageId
|
||||
? conversationMessages.value.find((item) => item.id === options.pendingMessageId)
|
||||
: null
|
||||
const previousThinkingEvents = completeWorkbenchAiThinkingEvents(resolveInlineThinkingEvents(existingPendingMessage))
|
||||
const pendingMessage = createInlineMessage('assistant', '正在生成申请核对表，请稍等...', {
|
||||
id: options.pendingMessageId,
|
||||
pending: true,
|
||||
stewardPlan: {
|
||||
streamStatus: 'streaming',
|
||||
thinkingEvents: [
|
||||
thinkingEvents: mergeWorkbenchAiThinkingEvents(previousThinkingEvents, [
|
||||
{
|
||||
eventId: 'application-preview-build',
|
||||
title: '整理申请表字段',
|
||||
@@ -491,19 +525,25 @@ export function useWorkbenchAiApplicationPreviewFlow({
|
||||
content: '正在刷新差旅规则和费用测算，完成后会直接展示核对表。',
|
||||
status: 'pending'
|
||||
}
|
||||
]
|
||||
])
|
||||
}
|
||||
})
|
||||
conversationMessages.value.push(pendingMessage)
|
||||
if (options.pendingMessageId) {
|
||||
replaceInlineMessage(options.pendingMessageId, pendingMessage)
|
||||
} else {
|
||||
conversationMessages.value.push(pendingMessage)
|
||||
}
|
||||
persistCurrentConversation()
|
||||
scrollInlineConversationToBottom()
|
||||
|
||||
try {
|
||||
const preview = await refreshApplicationPreviewEstimate(
|
||||
buildInlineApplicationPreview(expenseTypeLabel || expenseType, previewSourceText, currentUser.value || {})
|
||||
buildInlineApplicationPreview(expenseTypeLabel || expenseType, previewSourceText, currentUser.value || {}, {
|
||||
ontologyFields: options.ontologyFields
|
||||
})
|
||||
)
|
||||
const content = buildLocalApplicationPreviewMessage(preview)
|
||||
replaceInlineMessage(pendingMessage.id, createInlineMessage('assistant', content, {
|
||||
const previewMessage = createInlineMessage('assistant', content, {
|
||||
id: pendingMessage.id,
|
||||
applicationPreview: preview,
|
||||
suggestedActions: buildInlineApplicationPreviewSuggestedActions(preview),
|
||||
@@ -512,7 +552,20 @@ export function useWorkbenchAiApplicationPreviewFlow({
|
||||
thinkingEvents: completeInlineThinkingEvents(resolveInlineThinkingEvents(pendingMessage))
|
||||
},
|
||||
text: content
|
||||
}))
|
||||
})
|
||||
replaceInlineMessage(pendingMessage.id, previewMessage)
|
||||
if (options.autoSubmit && normalizeApplicationPreview(preview).readyToSubmit) {
|
||||
await executeInlineApplicationPreviewAction(AI_APPLICATION_ACTION_SUBMIT, previewMessage, {
|
||||
confirmed: true,
|
||||
skipUserMessage: true,
|
||||
userText: options.userMessage || '直接提交'
|
||||
})
|
||||
} else if (options.autoSaveDraft) {
|
||||
await executeInlineApplicationPreviewAction(AI_APPLICATION_ACTION_SAVE_DRAFT, previewMessage, {
|
||||
skipUserMessage: true,
|
||||
userText: options.userMessage || '保存草稿'
|
||||
})
|
||||
}
|
||||
} catch (error) {
|
||||
replaceInlineMessage(pendingMessage.id, createInlineMessage('assistant', error?.message || '申请核对表生成失败，请稍后重试。', {
|
||||
id: pendingMessage.id,
|
||||
|
||||
@@ -21,6 +21,10 @@ import {
|
||||
import {
|
||||
buildInlineAttachmentOcrDetails
|
||||
} from './workbenchAiMessageModel.js'
|
||||
import {
|
||||
completeWorkbenchAiThinkingEvents,
|
||||
mergeWorkbenchAiThinkingEvents
|
||||
} from './workbenchAiPlanningThinkingModel.js'
|
||||
|
||||
function shouldCheckAiRequiredApplicationGate(prompt) {
|
||||
const compact = String(prompt || '').replace(/\s+/g, '')
|
||||
@@ -187,13 +191,16 @@ export function useWorkbenchAiStewardFlow({
|
||||
return planRequest
|
||||
}
|
||||
|
||||
function handleInlineStewardStreamEvent(messageId, event) {
|
||||
function handleInlineStewardStreamEvent(messageId, event, options = {}) {
|
||||
const message = conversationMessages.value.find((item) => item.id === messageId)
|
||||
if (!message) {
|
||||
return
|
||||
}
|
||||
|
||||
if (event?.event === 'answer_delta') {
|
||||
if (options.includeAnswerDelta === false) {
|
||||
return
|
||||
}
|
||||
const data = event?.data && typeof event.data === 'object' ? event.data : {}
|
||||
const shouldAutoScroll = inlineConversationAutoScrollPinned.value
|
||||
appendInlineMessageContent(message, data.delta || data.content || data.text || '')
|
||||
@@ -226,16 +233,23 @@ export function useWorkbenchAiStewardFlow({
|
||||
scrollInlineConversationToBottom({ force: shouldAutoScroll })
|
||||
}
|
||||
|
||||
async function fetchInlineStewardPlan(messageId, payload) {
|
||||
async function fetchInlineStewardPlan(messageId, payload, options = {}) {
|
||||
const {
|
||||
includeAnswerDelta = true,
|
||||
idleTimeoutMs = 90000,
|
||||
timeoutMs = 0,
|
||||
timeoutMessage = '小财管家仍在规划任务，已停止等待。您可以稍后继续追问。'
|
||||
} = options
|
||||
try {
|
||||
return await fetchStewardPlanStream(
|
||||
payload,
|
||||
{
|
||||
onEvent: (event) => handleInlineStewardStreamEvent(messageId, event)
|
||||
onEvent: (event) => handleInlineStewardStreamEvent(messageId, event, { includeAnswerDelta })
|
||||
},
|
||||
{
|
||||
idleTimeoutMs: 90000,
|
||||
timeoutMessage: '小财管家仍在规划任务，已停止等待。您可以稍后继续追问。'
|
||||
idleTimeoutMs,
|
||||
timeoutMs,
|
||||
timeoutMessage
|
||||
}
|
||||
)
|
||||
} catch (error) {
|
||||
@@ -249,23 +263,67 @@ export function useWorkbenchAiStewardFlow({
|
||||
}
|
||||
}
|
||||
|
||||
async function requestInlineAssistantReply(prompt, entry = {}, files = []) {
|
||||
async function resolveInlineExecutionPlan(prompt, entry = {}, files = [], options = {}) {
|
||||
const receiptContext = await collectAiModeReceiptContext(files)
|
||||
const planRequest = buildStewardPlanRequest({
|
||||
rawText: prompt,
|
||||
files,
|
||||
currentUser: currentUser.value || {},
|
||||
conversationId: conversationId.value,
|
||||
stewardState: stewardState.value
|
||||
})
|
||||
planRequest.context_json = {
|
||||
...planRequest.context_json,
|
||||
entry_source: 'workbench_ai_inline_execution_plan',
|
||||
source: entry.source || 'workbench',
|
||||
attachment_names: receiptContext.attachmentNames,
|
||||
attachment_count: receiptContext.attachmentCount,
|
||||
ocr_summary: receiptContext.ocrSummary,
|
||||
ocr_documents: receiptContext.ocrDocuments,
|
||||
ocr_source_file_names: receiptContext.ocrSourceFileNames,
|
||||
requested_execution_mode: 'plan_then_execute',
|
||||
...(receiptContext.ocrError ? { ocr_error: receiptContext.ocrError } : {})
|
||||
}
|
||||
await attachAiRequiredApplicationGate(planRequest, prompt)
|
||||
const planningMessageId = String(options.pendingMessageId || '').trim()
|
||||
if (planningMessageId) {
|
||||
return fetchInlineStewardPlan(planningMessageId, planRequest, {
|
||||
includeAnswerDelta: false,
|
||||
idleTimeoutMs: 45000,
|
||||
timeoutMs: 35000,
|
||||
timeoutMessage: '小财管家意图规划超时，已切换到本地保守计划。'
|
||||
})
|
||||
}
|
||||
return fetchStewardPlan(planRequest, {
|
||||
timeoutMs: 35000,
|
||||
timeoutMessage: '小财管家意图规划超时，已切换到本地保守计划。'
|
||||
})
|
||||
}
|
||||
|
||||
async function requestInlineAssistantReply(prompt, entry = {}, files = [], options = {}) {
|
||||
let shouldAutoScrollOnFinish = true
|
||||
const reusablePendingMessageId = String(options.pendingMessageId || '').trim()
|
||||
const reusablePendingMessage = reusablePendingMessageId
|
||||
? conversationMessages.value.find((item) => item.id === reusablePendingMessageId)
|
||||
: null
|
||||
const previousThinkingEvents = resolveInlineThinkingEvents(reusablePendingMessage)
|
||||
const completedPreviousThinkingEvents = completeWorkbenchAiThinkingEvents(previousThinkingEvents)
|
||||
const pendingMessage = createInlineMessage('assistant', '', {
|
||||
id: reusablePendingMessageId || undefined,
|
||||
pending: true,
|
||||
stewardPlan: {
|
||||
streamStatus: 'streaming',
|
||||
thinkingEvents: [
|
||||
thinkingEvents: mergeWorkbenchAiThinkingEvents(completedPreviousThinkingEvents, [
|
||||
{
|
||||
eventId: 'init',
|
||||
title: '小财管家正在接入业务流程',
|
||||
content: '正在识别您的意图、上下文和附件信息。',
|
||||
status: 'running'
|
||||
}
|
||||
]
|
||||
])
|
||||
}
|
||||
})
|
||||
conversationMessages.value.push(pendingMessage)
|
||||
reusablePendingMessageId ? replaceInlineMessage(reusablePendingMessageId, pendingMessage) : conversationMessages.value.push(pendingMessage)
|
||||
scrollInlineConversationToBottom()
|
||||
|
||||
try {
|
||||
@@ -303,8 +361,8 @@ export function useWorkbenchAiStewardFlow({
|
||||
})
|
||||
const previousThinkingEvents = resolveInlineThinkingEvents(pendingMessage)
|
||||
const nextThinkingEvents = normalizedPlan.thinkingEvents.length
|
||||
? normalizedPlan.thinkingEvents
|
||||
: previousThinkingEvents.map((item) => ({ ...item, status: 'completed' }))
|
||||
? mergeWorkbenchAiThinkingEvents(previousThinkingEvents, normalizedPlan.thinkingEvents)
|
||||
: completeWorkbenchAiThinkingEvents(previousThinkingEvents)
|
||||
const previousConversationId = conversationId.value
|
||||
const nextConversationId = String(normalizedPlan.conversationId || '').trim()
|
||||
if (nextConversationId) {
|
||||
@@ -374,6 +432,7 @@ export function useWorkbenchAiStewardFlow({
|
||||
buildRequiredApplicationMissingText,
|
||||
buildRequiredApplicationSelectionText,
|
||||
filterRequiredApplicationCandidates,
|
||||
resolveInlineExecutionPlan,
|
||||
requestInlineAssistantReply
|
||||
}
|
||||
}
|
||||
|
||||
@@ -17,15 +17,45 @@ export function isReimbursementCreationIntent(prompt = '') {
|
||||
)
|
||||
}
|
||||
|
||||
export function resolveInlineTravelApplicationRequest(prompt = '') {
|
||||
const sourceText = String(prompt || '').trim()
|
||||
const compact = sourceText.replace(/\s+/g, '')
|
||||
if (!compact) {
|
||||
return null
|
||||
}
|
||||
if (/标准|制度|规则|政策|口径|怎么|如何|能不能|可以吗|查一下|查询|状态|进度|多少钱|多少/.test(compact)) {
|
||||
return null
|
||||
}
|
||||
|
||||
const hasTravelIntent = /出差|差旅|差旅费|交通/.test(compact)
|
||||
const hasTravelDetail = (
|
||||
/去[\u4e00-\u9fa5A-Za-z0-9]{2,24}/.test(compact) ||
|
||||
/[\u4e00-\u9fa5A-Za-z0-9]{2,24}出差/.test(compact) ||
|
||||
/地点[:：]?[\u4e00-\u9fa5A-Za-z0-9]{2,24}/.test(compact) ||
|
||||
/交通(?:方式)?[:：]?(火车|高铁|动车|飞机|航班|轮船|轮渡|汽车|网约车|自驾)/.test(compact) ||
|
||||
/(火车|高铁|动车|飞机|航班|轮船|轮渡|汽车|网约车|自驾)/.test(compact)
|
||||
)
|
||||
if (!hasTravelIntent || !hasTravelDetail) {
|
||||
return null
|
||||
}
|
||||
|
||||
return {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText,
|
||||
autoSubmit: /直接提交|提交申请|确认提交|提交审批/.test(compact)
|
||||
}
|
||||
}
|
||||
|
||||
export function resolveInlineApplicationPreviewTextAction(text = '') {
|
||||
const normalized = String(text || '').replace(/\s+/g, '').trim()
|
||||
if (!normalized) {
|
||||
return ''
|
||||
}
|
||||
if (/^(保存草稿|保存|存草稿|先保存)$/.test(normalized)) {
|
||||
if (/^(保存草稿|保存|存草稿|先保存|保存这个单据|保存这个申请|保存这个申请单|保存这张单据|保存这张申请单|保存当前单据|保存当前申请|保存上面的单据|保存刚才的草稿)$/.test(normalized)) {
|
||||
return AI_APPLICATION_ACTION_SAVE_DRAFT
|
||||
}
|
||||
if (/^(提交|提交申请|确认提交|提交审批|直接提交)$/.test(normalized)) {
|
||||
if (/^(提交|提交申请|确认提交|提交审批|直接提交|提交这个单据|提交这个申请|提交这个申请单|提交这张单据|提交这张申请单|提交当前单据|提交当前申请|提交上面的单据|提交刚才保存的草稿|提交刚才的草稿|把这个单据提交|把这个申请单提交|提交到领导审批|提交给领导审核)$/.test(normalized)) {
|
||||
return AI_APPLICATION_ACTION_SUBMIT
|
||||
}
|
||||
return ''
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
import {
|
||||
buildApplicationTemplatePreview,
|
||||
buildLocalApplicationPreview,
|
||||
buildModelRefinedApplicationPreview,
|
||||
normalizeApplicationPreview
|
||||
} from '../../utils/expenseApplicationPreview.js'
|
||||
import {
|
||||
@@ -187,11 +188,74 @@ export function normalizeInlineApplicationTypeLabel(expenseTypeLabel, fallback =
|
||||
return `${label}申请`
|
||||
}
|
||||
|
||||
export function buildInlineApplicationPreview(expenseTypeLabel, sourceText = '', currentUser = {}) {
|
||||
function buildOntologyTimeRangeFromCanonical(value = '') {
|
||||
const raw = String(value || '').trim()
|
||||
if (!raw) {
|
||||
return {}
|
||||
}
|
||||
const normalized = raw.replace(/\s+/g, ' ')
|
||||
const [startDate, endDate] = normalized
|
||||
.split(/\s*(?:至|到|~|--|—)\s*/)
|
||||
.map((item) => item.trim())
|
||||
.filter(Boolean)
|
||||
if (/^20\d{2}-\d{1,2}-\d{1,2}$/.test(startDate || '')) {
|
||||
return {
|
||||
raw,
|
||||
start_date: startDate,
|
||||
end_date: /^20\d{2}-\d{1,2}-\d{1,2}$/.test(endDate || '') ? endDate : startDate
|
||||
}
|
||||
}
|
||||
return { raw }
|
||||
}
|
||||
|
||||
function buildEntityFromCanonicalField(type, value) {
|
||||
const normalizedValue = String(value || '').trim()
|
||||
if (!type || !normalizedValue) {
|
||||
return null
|
||||
}
|
||||
return {
|
||||
type,
|
||||
value: normalizedValue,
|
||||
normalized_value: normalizedValue
|
||||
}
|
||||
}
|
||||
|
||||
function buildApplicationOntologyFromCanonicalFields(fields = {}) {
|
||||
const source = fields && typeof fields === 'object' ? fields : {}
|
||||
const entityKeys = [
|
||||
'expense_type',
|
||||
'location',
|
||||
'reason',
|
||||
'amount',
|
||||
'transport_mode',
|
||||
'customer_name',
|
||||
'merchant_name',
|
||||
'department_name',
|
||||
'employee_name',
|
||||
'employee_no'
|
||||
]
|
||||
return {
|
||||
parse_strategy: 'llm_primary',
|
||||
time_range: buildOntologyTimeRangeFromCanonical(source.time_range),
|
||||
entities: entityKeys
|
||||
.map((key) => buildEntityFromCanonicalField(key, source[key]))
|
||||
.filter(Boolean)
|
||||
}
|
||||
}
|
||||
|
||||
export function buildInlineApplicationPreview(expenseTypeLabel, sourceText = '', currentUser = {}, options = {}) {
|
||||
const rawText = String(sourceText || '').trim()
|
||||
const preview = rawText
|
||||
const basePreview = rawText
|
||||
? buildLocalApplicationPreview(rawText, currentUser)
|
||||
: buildApplicationTemplatePreview(currentUser)
|
||||
const preview = options.ontologyFields && typeof options.ontologyFields === 'object'
|
||||
? buildModelRefinedApplicationPreview(
|
||||
basePreview,
|
||||
buildApplicationOntologyFromCanonicalFields(options.ontologyFields),
|
||||
rawText,
|
||||
currentUser
|
||||
)
|
||||
: basePreview
|
||||
const normalized = normalizeApplicationPreview(preview)
|
||||
return normalizeApplicationPreview({
|
||||
...normalized,
|
||||
|
||||
@@ -0,0 +1,276 @@
|
||||
import { resolveInlineTravelApplicationRequest } from './workbenchAiApplicationGateModel.js'
|
||||
|
||||
export const WORKBENCH_AI_INTENT_SOURCE_MODEL = 'llm_function_call'
|
||||
export const WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK = 'rule_fallback'
|
||||
|
||||
export const WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW = 'build_application_preview'
|
||||
export const WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS = 'validate_required_fields'
|
||||
export const WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT = 'save_application_draft'
|
||||
export const WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK = 'run_duplicate_precheck'
|
||||
export const WORKBENCH_AI_STEP_SUBMIT_APPLICATION = 'submit_application'
|
||||
|
||||
const TRAVEL_APPLICATION_INTENT = 'create_travel_application'
|
||||
|
||||
function normalizePromptAction(prompt = '') {
|
||||
const compact = String(prompt || '').replace(/\s+/g, '')
|
||||
if (/直接提交|提交申请|确认提交|提交审批/.test(compact)) {
|
||||
return 'submit'
|
||||
}
|
||||
if (/保存草稿|保存|存草稿|先保存/.test(compact)) {
|
||||
return 'save_draft'
|
||||
}
|
||||
return 'preview'
|
||||
}
|
||||
|
||||
function normalizePlannerSource(value = '') {
|
||||
return String(value || '').trim() === WORKBENCH_AI_INTENT_SOURCE_MODEL
|
||||
? WORKBENCH_AI_INTENT_SOURCE_MODEL
|
||||
: WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK
|
||||
}
|
||||
|
||||
function normalizeSlotKey(key = '') {
|
||||
const normalized = String(key || '').trim()
|
||||
if (['time_range', 'business_time', 'occurred_date', 'application_time'].includes(normalized)) {
|
||||
return 'timeRange'
|
||||
}
|
||||
if (['transport_mode', 'transportType', 'transport_type', 'trafficMode'].includes(normalized)) {
|
||||
return 'transportMode'
|
||||
}
|
||||
if (['business_reason', 'businessPurpose', 'purpose'].includes(normalized)) {
|
||||
return 'reason'
|
||||
}
|
||||
return normalized
|
||||
}
|
||||
|
||||
function normalizeSlots(rawSlots = {}) {
|
||||
if (!rawSlots || typeof rawSlots !== 'object') {
|
||||
return {}
|
||||
}
|
||||
return Object.entries(rawSlots).reduce((slots, [key, value]) => {
|
||||
const normalizedKey = normalizeSlotKey(key)
|
||||
const normalizedValue = String(value || '').trim()
|
||||
if (normalizedKey && normalizedValue) {
|
||||
slots[normalizedKey] = normalizedValue
|
||||
}
|
||||
return slots
|
||||
}, {})
|
||||
}
|
||||
|
||||
const ONTOLOGY_FIELD_ALIASES = {
|
||||
business_time: 'time_range',
|
||||
occurred_date: 'time_range',
|
||||
application_time: 'time_range',
|
||||
transportType: 'transport_mode',
|
||||
transport_type: 'transport_mode',
|
||||
trafficMode: 'transport_mode',
|
||||
business_reason: 'reason',
|
||||
businessPurpose: 'reason',
|
||||
purpose: 'reason'
|
||||
}
|
||||
|
||||
const SUPPORTED_ONTOLOGY_FIELDS = new Set([
|
||||
'expense_type',
|
||||
'time_range',
|
||||
'location',
|
||||
'reason',
|
||||
'amount',
|
||||
'transport_mode',
|
||||
'attachments',
|
||||
'customer_name',
|
||||
'merchant_name',
|
||||
'department_name',
|
||||
'employee_name',
|
||||
'employee_no'
|
||||
])
|
||||
|
||||
function normalizeOntologyFields(rawFields = {}) {
|
||||
if (!rawFields || typeof rawFields !== 'object') {
|
||||
return {}
|
||||
}
|
||||
return Object.entries(rawFields).reduce((fields, [key, value]) => {
|
||||
const normalizedKey = ONTOLOGY_FIELD_ALIASES[String(key || '').trim()] || String(key || '').trim()
|
||||
const normalizedValue = String(value || '').trim()
|
||||
if (SUPPORTED_ONTOLOGY_FIELDS.has(normalizedKey) && normalizedValue) {
|
||||
fields[normalizedKey] = normalizedValue
|
||||
}
|
||||
return fields
|
||||
}, {})
|
||||
}
|
||||
|
||||
function buildApplicationSteps(requestedAction = 'preview') {
|
||||
const steps = [
|
||||
WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
|
||||
WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS
|
||||
]
|
||||
if (requestedAction === 'submit') {
|
||||
steps.push(
|
||||
WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
|
||||
WORKBENCH_AI_STEP_SUBMIT_APPLICATION
|
||||
)
|
||||
} else if (requestedAction === 'save_draft') {
|
||||
steps.push(WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT)
|
||||
}
|
||||
return steps
|
||||
}
|
||||
|
||||
function normalizeServerApplicationSteps(rawSteps = []) {
|
||||
if (!Array.isArray(rawSteps)) {
|
||||
return []
|
||||
}
|
||||
const mappedSteps = rawSteps
|
||||
.map((step) => String(step?.action_type || step?.actionType || '').trim())
|
||||
.map((actionType) => {
|
||||
if (actionType === WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW) {
|
||||
return WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW
|
||||
}
|
||||
if (actionType === WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS) {
|
||||
return WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS
|
||||
}
|
||||
if (actionType === WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT) {
|
||||
return WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT
|
||||
}
|
||||
if (actionType === WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK) {
|
||||
return WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK
|
||||
}
|
||||
if (actionType === WORKBENCH_AI_STEP_SUBMIT_APPLICATION) {
|
||||
return WORKBENCH_AI_STEP_SUBMIT_APPLICATION
|
||||
}
|
||||
return ''
|
||||
})
|
||||
.filter(Boolean)
|
||||
return [...new Set(mappedSteps)]
|
||||
}
|
||||
|
||||
function findModelTravelApplicationTask(rawPlan = {}) {
|
||||
const tasks = Array.isArray(rawPlan?.tasks) ? rawPlan.tasks : []
|
||||
return tasks.find((task) => {
|
||||
const taskType = String(task?.task_type || task?.taskType || '').trim()
|
||||
const assignedAgent = String(task?.assigned_agent || task?.assignedAgent || '').trim()
|
||||
return taskType === 'expense_application' || assignedAgent === 'application_assistant'
|
||||
}) || null
|
||||
}
|
||||
|
||||
function resolveCandidateFlows(rawPlan = {}) {
|
||||
const pendingFlow = rawPlan?.pending_flow_confirmation || rawPlan?.pendingFlowConfirmation || {}
|
||||
const pendingCandidates = pendingFlow?.candidate_flows || pendingFlow?.candidateFlows
|
||||
const rootCandidates = rawPlan?.candidate_flows || rawPlan?.candidateFlows
|
||||
if (Array.isArray(pendingCandidates)) {
|
||||
return pendingCandidates
|
||||
}
|
||||
return Array.isArray(rootCandidates) ? rootCandidates : []
|
||||
}
|
||||
|
||||
function findSingleApplicationCandidateFlow(rawPlan = {}) {
|
||||
const pendingFlow = rawPlan?.pending_flow_confirmation || rawPlan?.pendingFlowConfirmation || {}
|
||||
if (String(pendingFlow?.status || '').trim() !== 'pending') {
|
||||
return null
|
||||
}
|
||||
const candidateFlows = resolveCandidateFlows(rawPlan)
|
||||
if (candidateFlows.length !== 1) {
|
||||
return null
|
||||
}
|
||||
const [candidate] = candidateFlows
|
||||
const flowId = String(candidate?.flow_id || candidate?.flowId || '').trim()
|
||||
const label = String(candidate?.label || '').trim()
|
||||
if (flowId === 'travel_application' && /先发起出差申请/.test(label)) {
|
||||
return candidate
|
||||
}
|
||||
return null
|
||||
}
|
||||
|
||||
export function normalizeWorkbenchAiIntentPlan(rawPlan = {}, options = {}) {
|
||||
const prompt = String(options.prompt || rawPlan?.sourceText || rawPlan?.source_text || '').trim()
|
||||
const task = findModelTravelApplicationTask(rawPlan)
|
||||
if (!task) {
|
||||
const candidateFlow = findSingleApplicationCandidateFlow(rawPlan)
|
||||
if (!candidateFlow) {
|
||||
return null
|
||||
}
|
||||
const ontologyFields = normalizeOntologyFields(candidateFlow.ontology_fields || candidateFlow.ontologyFields)
|
||||
const requestedAction = normalizePromptAction(prompt)
|
||||
return {
|
||||
source: normalizePlannerSource(rawPlan.planning_source || rawPlan.planningSource),
|
||||
intent: TRAVEL_APPLICATION_INTENT,
|
||||
requestedAction,
|
||||
confidence: Number(candidateFlow.confidence || rawPlan.confidence || 0),
|
||||
sourceText: prompt,
|
||||
ontologyFields,
|
||||
slots: normalizeSlots(ontologyFields),
|
||||
missingFields: Array.isArray(candidateFlow.missing_fields || candidateFlow.missingFields)
|
||||
? candidateFlow.missing_fields || candidateFlow.missingFields
|
||||
: [],
|
||||
steps: buildApplicationSteps(requestedAction)
|
||||
}
|
||||
}
|
||||
|
||||
const rawOntologyFields = task.ontology_fields || task.ontologyFields || rawPlan.slots
|
||||
const ontologyFields = normalizeOntologyFields(rawOntologyFields)
|
||||
const requestedAction = String(
|
||||
task.requested_action ||
|
||||
task.requestedAction ||
|
||||
rawPlan.requested_action ||
|
||||
rawPlan.requestedAction ||
|
||||
''
|
||||
).trim() || normalizePromptAction(prompt)
|
||||
const serverSteps = normalizeServerApplicationSteps(task.action_steps || task.actionSteps)
|
||||
return {
|
||||
source: normalizePlannerSource(rawPlan.planning_source || rawPlan.planningSource),
|
||||
intent: TRAVEL_APPLICATION_INTENT,
|
||||
requestedAction,
|
||||
confidence: Number(task.confidence || rawPlan.confidence || 0),
|
||||
sourceText: prompt,
|
||||
ontologyFields,
|
||||
slots: normalizeSlots(ontologyFields),
|
||||
missingFields: Array.isArray(task.missing_fields || task.missingFields)
|
||||
? task.missing_fields || task.missingFields
|
||||
: [],
|
||||
steps: serverSteps.length ? serverSteps : buildApplicationSteps(requestedAction)
|
||||
}
|
||||
}
|
||||
|
||||
export function buildRuleFallbackWorkbenchAiIntentPlan(prompt = '') {
|
||||
const request = resolveInlineTravelApplicationRequest(prompt)
|
||||
if (!request) {
|
||||
return null
|
||||
}
|
||||
const requestedAction = request.autoSubmit ? 'submit' : normalizePromptAction(prompt)
|
||||
return {
|
||||
source: WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK,
|
||||
intent: TRAVEL_APPLICATION_INTENT,
|
||||
requestedAction,
|
||||
confidence: 0.72,
|
||||
sourceText: request.sourceText,
|
||||
ontologyFields: {},
|
||||
slots: {},
|
||||
missingFields: [],
|
||||
steps: buildApplicationSteps(requestedAction)
|
||||
}
|
||||
}
|
||||
|
||||
export function shouldRequestWorkbenchAiIntentPlan(prompt = '') {
|
||||
const compact = String(prompt || '').replace(/\s+/g, '')
|
||||
if (!compact) {
|
||||
return false
|
||||
}
|
||||
if (compact.length < 2 || /^[\d\s.,，。:：;；!?！？-]+$/.test(compact)) {
|
||||
return false
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
export function resolveExecutableTravelApplicationPlan(plan = null) {
|
||||
if (!plan || plan.intent !== TRAVEL_APPLICATION_INTENT) {
|
||||
return null
|
||||
}
|
||||
if (!Array.isArray(plan.steps) || !plan.steps.includes(WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW)) {
|
||||
return null
|
||||
}
|
||||
return {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText: String(plan.sourceText || '').trim(),
|
||||
ontologyFields: normalizeOntologyFields(plan.ontologyFields || {}),
|
||||
autoSubmit: plan.steps.includes(WORKBENCH_AI_STEP_SUBMIT_APPLICATION),
|
||||
autoSaveDraft: plan.steps.includes(WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT)
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,80 @@
|
||||
export function mergeWorkbenchAiThinkingEvents(...groups) {
|
||||
const merged = []
|
||||
const indexById = new Map()
|
||||
groups.flat().filter(Boolean).forEach((event) => {
|
||||
const eventId = String(event.eventId || event.event_id || '').trim()
|
||||
if (!eventId || !indexById.has(eventId)) {
|
||||
if (eventId) {
|
||||
indexById.set(eventId, merged.length)
|
||||
}
|
||||
merged.push(event)
|
||||
return
|
||||
}
|
||||
const index = indexById.get(eventId)
|
||||
merged.splice(index, 1, {
|
||||
...merged[index],
|
||||
...event,
|
||||
eventId
|
||||
})
|
||||
})
|
||||
return merged
|
||||
}
|
||||
|
||||
export function completeWorkbenchAiThinkingEvents(events = []) {
|
||||
return events.map((event) => ({
|
||||
...event,
|
||||
status: event.status === 'failed' ? 'failed' : 'completed'
|
||||
}))
|
||||
}
|
||||
|
||||
export function buildInitialModelPlanningThinkingEvents() {
|
||||
return [
|
||||
{
|
||||
eventId: 'model-planning-intent',
|
||||
title: '判断办理意图',
|
||||
content: '正在判断这句话是要办申请、做报销、处理附件，还是普通咨询。',
|
||||
status: 'running'
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
export function buildModelPlanningProgressSchedule() {
|
||||
return [
|
||||
{
|
||||
delayMs: 900,
|
||||
event: {
|
||||
eventId: 'model-planning-slots',
|
||||
title: '抽取关键信息',
|
||||
content: '正在整理日期、地点、事由、交通方式、附件和“保存/提交”等动作线索。',
|
||||
status: 'running'
|
||||
}
|
||||
},
|
||||
{
|
||||
delayMs: 2200,
|
||||
event: {
|
||||
eventId: 'model-planning-steps',
|
||||
title: '规划执行步骤',
|
||||
content: '正在生成可执行动作序列，例如填充申请表、校验必填项、保存草稿或发起提交。',
|
||||
status: 'running'
|
||||
}
|
||||
},
|
||||
{
|
||||
delayMs: 5200,
|
||||
event: {
|
||||
eventId: 'model-planning-tools',
|
||||
title: '匹配业务工具',
|
||||
content: '正在把模型计划映射到白名单工具，避免未确认的提交或附件关联直接产生副作用。',
|
||||
status: 'running'
|
||||
}
|
||||
},
|
||||
{
|
||||
delayMs: 9000,
|
||||
event: {
|
||||
eventId: 'model-planning-fallback',
|
||||
title: '准备兜底策略',
|
||||
content: '如果模型等待过久或调用失败，会按保守规则继续识别，保证申请、报销和草稿流程还能推进。',
|
||||
status: 'running'
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -24,6 +24,14 @@ export function fetchStewardRuntimeDecision(payload, options = {}) {
|
||||
})
|
||||
}
|
||||
|
||||
export function executeStewardAction(payload, options = {}) {
|
||||
return apiRequest('/steward/actions/execute', {
|
||||
method: 'POST',
|
||||
body: JSON.stringify(payload),
|
||||
...options
|
||||
})
|
||||
}
|
||||
|
||||
export async function fetchStewardPlanStream(payload, handlers = {}, options = {}) {
|
||||
const {
|
||||
timeoutMs = 0,
|
||||
|
||||
@@ -28,6 +28,13 @@ const AGENT_LABELS = {
|
||||
expense: '报销助手'
|
||||
}
|
||||
|
||||
const EXECUTABLE_STEWARD_ACTION_TYPES = new Set([
|
||||
'save_application_draft',
|
||||
'submit_application',
|
||||
'create_reimbursement_draft',
|
||||
'associate_attachments'
|
||||
])
|
||||
|
||||
export function buildStewardPlanRequest({
|
||||
rawText = '',
|
||||
files = [],
|
||||
@@ -102,10 +109,12 @@ export function normalizeStewardPlan(rawPlan = {}, options = {}) {
|
||||
summary: String(item.summary || ''),
|
||||
status: String(item.status || ''),
|
||||
confidence: Number(item.confidence || 0),
|
||||
requestedAction: String(item.requested_action || item.requestedAction || ''),
|
||||
ontologyFields: item.ontology_fields || item.ontologyFields || {},
|
||||
missingFields,
|
||||
missingFieldItems: buildStewardFieldItems(missingFields, taskType),
|
||||
confirmationRequired: item.confirmation_required ?? item.confirmationRequired ?? true
|
||||
confirmationRequired: item.confirmation_required ?? item.confirmationRequired ?? true,
|
||||
actionSteps: normalizeStewardActionSteps(item.action_steps || item.actionSteps)
|
||||
}
|
||||
})
|
||||
: [],
|
||||
@@ -137,6 +146,26 @@ export function normalizeStewardPlan(rawPlan = {}, options = {}) {
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeStewardActionSteps(rawSteps = []) {
|
||||
if (!Array.isArray(rawSteps)) {
|
||||
return []
|
||||
}
|
||||
return rawSteps
|
||||
.map((step) => ({
|
||||
step_id: String(step?.step_id || step?.stepId || ''),
|
||||
action_type: String(step?.action_type || step?.actionType || ''),
|
||||
label: String(step?.label || ''),
|
||||
target_task_id: String(step?.target_task_id || step?.targetTaskId || ''),
|
||||
status: String(step?.status || 'planned'),
|
||||
requires_confirmation: Boolean(step?.requires_confirmation ?? step?.requiresConfirmation),
|
||||
depends_on: Array.isArray(step?.depends_on || step?.dependsOn)
|
||||
? step.depends_on || step.dependsOn
|
||||
: [],
|
||||
payload: step?.payload && typeof step.payload === 'object' ? step.payload : {}
|
||||
}))
|
||||
.filter((step) => step.step_id && step.action_type)
|
||||
}
|
||||
|
||||
export function buildStewardPlanMessageText(plan) {
|
||||
const normalized = normalizeStewardPlan(plan)
|
||||
if (isOffTopicPlan(normalized)) {
|
||||
@@ -353,6 +382,7 @@ export function buildStewardSuggestedActions(plan) {
|
||||
const targetSessionType = actionType === 'confirm_create_application'
|
||||
? SESSION_TYPE_APPLICATION
|
||||
: SESSION_TYPE_EXPENSE
|
||||
const executableStep = resolveExecutableStewardActionStep(task)
|
||||
return [
|
||||
{
|
||||
label: buildNextActionLabel(actionType, task),
|
||||
@@ -372,6 +402,7 @@ export function buildStewardSuggestedActions(plan) {
|
||||
steward_confirmation_id: String(action.confirmation_id || action.confirmationId || ''),
|
||||
steward_plan_id: normalized.planId,
|
||||
steward_next_task_id: task?.taskId || '',
|
||||
...buildStewardExecuteActionPayload(executableStep, task),
|
||||
steward_current_task: buildStewardTaskPayload(task),
|
||||
steward_remaining_task_count: normalized.tasks.filter((item) => item.taskId !== task?.taskId).length,
|
||||
steward_remaining_tasks: buildRemainingTaskPayload(normalized, task?.taskId)
|
||||
@@ -380,6 +411,26 @@ export function buildStewardSuggestedActions(plan) {
|
||||
]
|
||||
}
|
||||
|
||||
function resolveExecutableStewardActionStep(task = null) {
|
||||
const steps = Array.isArray(task?.actionSteps || task?.action_steps)
|
||||
? task.actionSteps || task.action_steps
|
||||
: []
|
||||
return [...steps].reverse().find((step) => EXECUTABLE_STEWARD_ACTION_TYPES.has(String(step.action_type || step.actionType || ''))) || null
|
||||
}
|
||||
|
||||
function buildStewardExecuteActionPayload(step, task) {
|
||||
if (!step) {
|
||||
return {}
|
||||
}
|
||||
return {
|
||||
steward_execute_action: true,
|
||||
steward_action_type: String(step.action_type || step.actionType || ''),
|
||||
steward_action_step: step,
|
||||
steward_action_requires_confirmation: Boolean(step.requires_confirmation ?? step.requiresConfirmation),
|
||||
steward_action_task_id: task?.taskId || task?.task_id || ''
|
||||
}
|
||||
}
|
||||
|
||||
function normalizePendingFlowConfirmation(rawPlan = {}) {
|
||||
const rawPending = rawPlan.pending_flow_confirmation || rawPlan.pendingFlowConfirmation || {}
|
||||
const rawCandidates = Array.isArray(rawPlan.candidate_flows || rawPlan.candidateFlows)
|
||||
@@ -779,7 +830,9 @@ function buildStewardTaskPayload(task) {
|
||||
title: task.title || '',
|
||||
summary: task.summary || '',
|
||||
assigned_agent: task.assignedAgent || task.assigned_agent || '',
|
||||
requested_action: task.requestedAction || task.requested_action || '',
|
||||
ontology_fields: task.ontologyFields || task.ontology_fields || {},
|
||||
missing_fields: task.missingFields || task.missing_fields || []
|
||||
missing_fields: task.missingFields || task.missing_fields || [],
|
||||
action_steps: task.actionSteps || task.action_steps || []
|
||||
}
|
||||
}
|
||||
|
||||
@@ -51,6 +51,9 @@ import {
|
||||
import {
|
||||
shouldUseBudgetCompileReport
|
||||
} from '../src/views/scripts/budgetAssistantReportModel.js'
|
||||
import {
|
||||
buildInlineApplicationPreview
|
||||
} from '../src/composables/workbenchAiMode/workbenchAiApplicationPreviewModel.js'
|
||||
import { resolveStewardTypewriterNextIndex } from '../src/views/scripts/stewardTypewriter.js'
|
||||
import {
|
||||
ASSISTANT_SCOPE_ACTION_SWITCH,
|
||||
@@ -140,6 +143,14 @@ const flowScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/views/scripts/useTravelReimbursementFlow.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
const personalWorkbenchAiModeScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/composables/workbenchAiMode/usePersonalWorkbenchAiMode.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
const applicationPreviewFlowScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/composables/workbenchAiMode/useWorkbenchAiApplicationPreviewFlow.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
|
||||
function createFlowHarness() {
|
||||
return useTravelReimbursementFlow({
|
||||
@@ -241,6 +252,32 @@ test('application intent uses local preview instead of immediate orchestrator ca
|
||||
assert.match(buildLocalApplicationPreviewMessage(preview), /点击对应行即可直接编辑/)
|
||||
})
|
||||
|
||||
test('AI workbench routes compact travel direct-submit planner into application preview auto submit', () => {
|
||||
assert.match(personalWorkbenchAiModeScript, /buildRuleFallbackWorkbenchAiIntentPlan/)
|
||||
assert.match(personalWorkbenchAiModeScript, /normalizeWorkbenchAiIntentPlan/)
|
||||
assert.match(personalWorkbenchAiModeScript, /resolveExecutableTravelApplicationPlan/)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/async function executeModelPlannedWorkbenchIntent\(cleanPrompt, entry = \{\}, files = \[\]\)/
|
||||
)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/modelPlan = await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files\)/
|
||||
)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/const rulePlan = buildRuleFallbackWorkbenchAiIntentPlan\(cleanPrompt\)/
|
||||
)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/applicationFlow\.startAiApplicationPreview\([\s\S]*travelApplicationRequest\.expenseType[\s\S]*travelApplicationRequest\.expenseTypeLabel[\s\S]*travelApplicationRequest\.sourceText[\s\S]*ontologyFields:\s*travelApplicationRequest\.ontologyFields[\s\S]*autoSubmit:\s*travelApplicationRequest\.autoSubmit/
|
||||
)
|
||||
assert.doesNotMatch(personalWorkbenchAiModeScript, /fallbackIntentPlan/)
|
||||
assert.match(applicationPreviewFlowScript, /if \(options\.autoSubmit && normalizeApplicationPreview\(preview\)\.readyToSubmit\)/)
|
||||
assert.match(applicationPreviewFlowScript, /confirmed:\s*true/)
|
||||
assert.match(applicationPreviewFlowScript, /skipUserMessage:\s*true/)
|
||||
})
|
||||
|
||||
test('unsupported business guidance opens in assistant conversation form', () => {
|
||||
const conversation = buildUnsupportedBusinessScopeConversation('你好')
|
||||
|
||||
@@ -366,6 +403,20 @@ test('application preview renders ordered editable rows and submit text uses edi
|
||||
assert.match(buildApplicationPreviewSubmitText(editedPreview), /系统预估费用：1900元/)
|
||||
})
|
||||
|
||||
test('application preview keeps compact direct-submit command out of business reason', () => {
|
||||
const preview = buildInlineApplicationPreview(
|
||||
'差旅费',
|
||||
'去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交',
|
||||
{ grade: 'P5' }
|
||||
)
|
||||
|
||||
assert.equal(preview.fields.location, '上海')
|
||||
assert.equal(preview.fields.reason, '辅助国网仿生产服务器部署')
|
||||
assert.equal(preview.fields.transportMode, '火车')
|
||||
assert.equal(preview.readyToSubmit, false)
|
||||
assert.deepEqual(preview.missingFields, ['出发时间', '天数'])
|
||||
})
|
||||
|
||||
test('application estimate builds deterministic mock transport amount and total', () => {
|
||||
const trainEstimate = buildMockApplicationTransportEstimate({ transportMode: '高铁', location: '上海' })
|
||||
const datedTrainEstimate = buildMockApplicationTransportEstimate({
|
||||
|
||||
54
web/tests/steward-actions-service.test.mjs
Normal file
54
web/tests/steward-actions-service.test.mjs
Normal file
@@ -0,0 +1,54 @@
|
||||
import assert from 'node:assert/strict'
|
||||
|
||||
import { executeStewardAction } from '../src/services/steward.js'
|
||||
|
||||
async function testExecuteStewardActionUsesActionEndpoint() {
|
||||
let capturedUrl = ''
|
||||
let capturedOptions = null
|
||||
|
||||
global.fetch = async (url, options) => {
|
||||
capturedUrl = String(url)
|
||||
capturedOptions = options
|
||||
return {
|
||||
ok: true,
|
||||
async json() {
|
||||
return {
|
||||
action_type: 'save_application_draft',
|
||||
status: 'succeeded',
|
||||
message: '申请草稿已保存。',
|
||||
result_payload: {
|
||||
draft_payload: {
|
||||
claim_id: 'claim-action-draft',
|
||||
claim_no: 'A12345678',
|
||||
status: 'draft'
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const payload = await executeStewardAction({
|
||||
action_type: 'save_application_draft',
|
||||
message: '保存草稿',
|
||||
task: {
|
||||
task_id: 'task-app-1',
|
||||
task_type: 'expense_application'
|
||||
}
|
||||
})
|
||||
|
||||
assert.equal(capturedUrl, '/api/v1/steward/actions/execute')
|
||||
assert.equal(capturedOptions.method, 'POST')
|
||||
assert.equal(JSON.parse(capturedOptions.body).action_type, 'save_application_draft')
|
||||
assert.equal(payload.status, 'succeeded')
|
||||
}
|
||||
|
||||
async function run() {
|
||||
await testExecuteStewardActionUsesActionEndpoint()
|
||||
console.log('steward actions service tests passed')
|
||||
}
|
||||
|
||||
run().catch((error) => {
|
||||
console.error(error)
|
||||
process.exit(1)
|
||||
})
|
||||
@@ -71,3 +71,55 @@ test('steward plan summary guides bare reimbursement intent into scene selection
|
||||
assert.match(action.description, /先进入报销助手选择具体费用类型/)
|
||||
assert.equal(action.payload.carry_text, '我要报销')
|
||||
})
|
||||
|
||||
test('steward suggested action carries server executable application action step', () => {
|
||||
const plan = {
|
||||
plan_id: 'plan-application-submit',
|
||||
tasks: [
|
||||
{
|
||||
task_id: 'task-app-1',
|
||||
task_type: 'expense_application',
|
||||
title: '上海出差申请',
|
||||
assigned_agent: 'application_assistant',
|
||||
requested_action: 'submit',
|
||||
ontology_fields: {
|
||||
expense_type: 'travel',
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: 'train'
|
||||
},
|
||||
missing_fields: [],
|
||||
action_steps: [
|
||||
{ step_id: 'task-app-1:01', action_type: 'fill_application_fields', status: 'planned' },
|
||||
{ step_id: 'task-app-1:02', action_type: 'build_application_preview', status: 'planned' },
|
||||
{ step_id: 'task-app-1:03', action_type: 'validate_required_fields', status: 'planned' },
|
||||
{ step_id: 'task-app-1:04', action_type: 'run_duplicate_precheck', status: 'planned' },
|
||||
{
|
||||
step_id: 'task-app-1:05',
|
||||
action_type: 'submit_application',
|
||||
status: 'pending_confirmation',
|
||||
requires_confirmation: true
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
confirmation_groups: [
|
||||
{
|
||||
confirmation_id: 'confirm-task-app-1',
|
||||
action_type: 'confirm_create_application',
|
||||
target_task_id: 'task-app-1'
|
||||
}
|
||||
],
|
||||
next_action: 'confirm_task'
|
||||
}
|
||||
|
||||
const [action] = buildStewardSuggestedActions(plan)
|
||||
|
||||
assert.equal(action.payload.steward_execute_action, true)
|
||||
assert.equal(action.payload.steward_action_type, 'submit_application')
|
||||
assert.equal(action.payload.steward_action_step.step_id, 'task-app-1:05')
|
||||
assert.equal(action.payload.steward_action_requires_confirmation, true)
|
||||
assert.equal(action.payload.steward_current_task.requested_action, 'submit')
|
||||
assert.equal(action.payload.steward_current_task.action_steps.at(-1).action_type, 'submit_application')
|
||||
})
|
||||
|
||||
@@ -245,3 +245,147 @@ test('workbench standalone draft action asks before creating a new reimbursement
|
||||
label: '独立新建报销单'
|
||||
})
|
||||
})
|
||||
|
||||
test('workbench steward executable submit action runs precheck before submit and writes result message', async () => {
|
||||
const requests = []
|
||||
const originalFetch = globalThis.fetch
|
||||
globalThis.fetch = async (_url, options = {}) => {
|
||||
const body = JSON.parse(String(options.body || '{}'))
|
||||
requests.push(body)
|
||||
if (body.action_type === 'run_duplicate_precheck') {
|
||||
return {
|
||||
ok: true,
|
||||
async json() {
|
||||
return {
|
||||
action_type: 'run_duplicate_precheck',
|
||||
status: 'succeeded',
|
||||
message: '未发现重复或冲突申请，可以继续提交。',
|
||||
result_payload: {
|
||||
status: 'ok',
|
||||
blocking: false
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return {
|
||||
ok: true,
|
||||
async json() {
|
||||
return {
|
||||
action_type: 'submit_application',
|
||||
status: 'succeeded',
|
||||
message: '申请已提交审批。',
|
||||
result_payload: {
|
||||
draft_payload: {
|
||||
claim_id: 'claim-app-1',
|
||||
claim_no: 'A1BCDEF2'
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
try {
|
||||
const messages = []
|
||||
let messageSeq = 0
|
||||
const createInlineMessage = (role, content, options = {}) => ({
|
||||
id: options.id || `msg-${++messageSeq}`,
|
||||
role,
|
||||
content,
|
||||
pending: Boolean(options.pending),
|
||||
suggestedActions: Array.isArray(options.suggestedActions) ? options.suggestedActions : []
|
||||
})
|
||||
const replaceInlineMessage = (id, nextMessage) => {
|
||||
const index = messages.findIndex((item) => item.id === id)
|
||||
if (index >= 0) {
|
||||
messages.splice(index, 1, nextMessage)
|
||||
}
|
||||
}
|
||||
let persisted = false
|
||||
const router = useWorkbenchAiActionRouter({
|
||||
aiExpenseDraft: { value: null },
|
||||
applicationFlow: {
|
||||
isInlineSuggestedActionDisabled: () => false,
|
||||
executeInlineApplicationPreviewAction: () => {}
|
||||
},
|
||||
assistantDraft: { value: '' },
|
||||
attachmentFlow: {
|
||||
confirmAiAttachmentAssociation: () => {}
|
||||
},
|
||||
conversationMessages: { value: messages },
|
||||
createInlineMessage,
|
||||
emit: () => {},
|
||||
expenseFlow: {
|
||||
linkAiExpenseApplication: () => {},
|
||||
pushInlineExpenseSceneSelectionPrompt: () => {},
|
||||
startAiApplicationPreviewFromAction: () => {},
|
||||
startAiExpenseDraft: () => {}
|
||||
},
|
||||
focusAiModeInput: () => {},
|
||||
hasInlineAttachmentOcrDetails: () => false,
|
||||
persistCurrentConversation: () => {
|
||||
persisted = true
|
||||
},
|
||||
replaceInlineMessage,
|
||||
resolveLatestInlineUserPrompt: () => '2026-02-20 至 2026-02-23，去上海出差，交通火车，直接提交',
|
||||
scrollInlineConversationToBottom: () => {},
|
||||
selectedFiles: { value: [] },
|
||||
startInlineConversation: () => {},
|
||||
toast: () => {},
|
||||
toggleInlineAttachmentOcrDetails: () => {}
|
||||
})
|
||||
const sourceMessage = {
|
||||
suggestedActionsLocked: false
|
||||
}
|
||||
|
||||
await router.handleInlineSuggestedAction({
|
||||
label: '确认提交申请',
|
||||
action_type: 'switch_session',
|
||||
payload: {
|
||||
steward_execute_action: true,
|
||||
steward_plan_id: 'plan-submit-1',
|
||||
steward_action_type: 'submit_application',
|
||||
steward_action_requires_confirmation: true,
|
||||
steward_action_step: {
|
||||
step_id: 'task-app-1:05',
|
||||
action_type: 'submit_application',
|
||||
requires_confirmation: true
|
||||
},
|
||||
steward_current_task: {
|
||||
task_id: 'task-app-1',
|
||||
task_type: 'expense_application',
|
||||
assigned_agent: 'application_assistant',
|
||||
title: '上海出差申请',
|
||||
summary: '2026-02-20 至 2026-02-23 去上海出差，交通火车。',
|
||||
requested_action: 'submit',
|
||||
ontology_fields: {
|
||||
expense_type: 'travel',
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: 'train'
|
||||
},
|
||||
missing_fields: [],
|
||||
action_steps: [
|
||||
{ step_id: 'task-app-1:04', action_type: 'run_duplicate_precheck' },
|
||||
{ step_id: 'task-app-1:05', action_type: 'submit_application', requires_confirmation: true }
|
||||
]
|
||||
},
|
||||
carry_text: '2026-02-20 至 2026-02-23，去上海出差，交通火车，直接提交'
|
||||
}
|
||||
}, sourceMessage)
|
||||
|
||||
assert.equal(requests.length, 2)
|
||||
assert.equal(requests[0].action_type, 'run_duplicate_precheck')
|
||||
assert.equal(requests[1].action_type, 'submit_application')
|
||||
assert.equal(requests[1].confirmed, true)
|
||||
assert.equal(requests[1].context_json.precheck_result.status, 'ok')
|
||||
assert.equal(sourceMessage.suggestedActionsLocked, true)
|
||||
assert.equal(persisted, true)
|
||||
assert.match(messages.at(-1).content, /申请已提交审批/)
|
||||
assert.equal(messages.at(-1).suggestedActions[0].action_type, 'open_application_detail')
|
||||
} finally {
|
||||
globalThis.fetch = originalFetch
|
||||
}
|
||||
})
|
||||
|
||||
166
web/tests/workbench-ai-application-context-submit.test.mjs
Normal file
166
web/tests/workbench-ai-application-context-submit.test.mjs
Normal file
@@ -0,0 +1,166 @@
|
||||
import assert from 'node:assert/strict'
|
||||
import test from 'node:test'
|
||||
|
||||
import { useWorkbenchAiApplicationPreviewFlow } from '../src/composables/workbenchAiMode/useWorkbenchAiApplicationPreviewFlow.js'
|
||||
|
||||
function createRef(value) {
|
||||
return { value }
|
||||
}
|
||||
|
||||
function createInlineMessage(role, content, options = {}) {
|
||||
return {
|
||||
id: options.id || `msg-${Math.random().toString(16).slice(2)}`,
|
||||
role,
|
||||
content,
|
||||
text: content,
|
||||
paragraphs: String(content || '').split(/\n+/).filter(Boolean),
|
||||
pending: Boolean(options.pending),
|
||||
...options
|
||||
}
|
||||
}
|
||||
|
||||
function buildApplicationPreviewFlowHarness(messages) {
|
||||
const conversationMessages = createRef(messages)
|
||||
const applicationSubmitConfirmOpen = createRef(false)
|
||||
const applicationSubmitConfirmContext = createRef(null)
|
||||
const persisted = createRef(0)
|
||||
|
||||
const flow = useWorkbenchAiApplicationPreviewFlow({
|
||||
activateInlineConversation: () => {},
|
||||
applicationPreviewEditor: createRef({}),
|
||||
applicationSubmitConfirmContext,
|
||||
applicationSubmitConfirmOpen,
|
||||
assistantDraft: createRef(''),
|
||||
cancelApplicationPreviewEditor: () => {},
|
||||
clearAiModeFiles: () => {},
|
||||
closeWorkbenchDatePicker: () => {},
|
||||
commitApplicationPreviewEditor: async () => true,
|
||||
conversationId: createRef('conversation-context-submit'),
|
||||
conversationMessages,
|
||||
conversationStarted: createRef(true),
|
||||
createInlineMessage,
|
||||
currentUser: createRef({ username: 'zhangsan@example.com', name: '张三' }),
|
||||
handleApplicationPreviewEditorKeydown: () => {},
|
||||
inlineConversationAutoScrollPinned: createRef(true),
|
||||
isApplicationPreviewEditing: createRef(false),
|
||||
openApplicationPreviewEditor: () => {},
|
||||
persistCurrentConversation: () => { persisted.value += 1 },
|
||||
pushInlineApplicationActionUserMessage: (text) => {
|
||||
conversationMessages.value.push(createInlineMessage('user', text))
|
||||
},
|
||||
pushInlineUserMessage: (text) => {
|
||||
conversationMessages.value.push(createInlineMessage('user', text))
|
||||
},
|
||||
refreshApplicationPreviewEstimate: async (preview) => preview,
|
||||
removeWorkbenchDateTag: () => {},
|
||||
replaceInlineMessage: (id, nextMessage) => {
|
||||
const index = conversationMessages.value.findIndex((item) => item.id === id)
|
||||
if (index >= 0) {
|
||||
conversationMessages.value.splice(index, 1, nextMessage)
|
||||
} else {
|
||||
conversationMessages.value.push(nextMessage)
|
||||
}
|
||||
},
|
||||
resolveApplicationPreviewEditorDateMax: () => '',
|
||||
resolveApplicationPreviewEditorDateMin: () => '',
|
||||
resolveApplicationPreviewEditorControl: () => null,
|
||||
resolveApplicationPreviewEditorOptions: () => [],
|
||||
resolveInlineThinkingEvents: (message) => message?.stewardPlan?.thinkingEvents || [],
|
||||
resolveLatestInlineUserPrompt: () => '2026-02-20 至 2026-02-23，去上海出差，交通火车，保存草稿',
|
||||
scrollInlineConversationToBottom: () => {},
|
||||
sending: createRef(false),
|
||||
toast: () => {}
|
||||
})
|
||||
|
||||
return {
|
||||
applicationSubmitConfirmOpen,
|
||||
conversationMessages,
|
||||
flow,
|
||||
persisted
|
||||
}
|
||||
}
|
||||
|
||||
test('workbench saved application draft can be submitted by contextual text without re-planning', async () => {
|
||||
const originalFetch = globalThis.fetch
|
||||
const requests = []
|
||||
globalThis.fetch = async (url, options = {}) => {
|
||||
const normalizedUrl = String(url)
|
||||
if (normalizedUrl.includes('/reimbursements/claims')) {
|
||||
return {
|
||||
ok: true,
|
||||
async json() {
|
||||
return { items: [] }
|
||||
}
|
||||
}
|
||||
}
|
||||
if (normalizedUrl.includes('/reimbursements/application-preview-action')) {
|
||||
const body = JSON.parse(String(options.body || '{}'))
|
||||
requests.push({ url: normalizedUrl, body })
|
||||
return {
|
||||
ok: true,
|
||||
async json() {
|
||||
return {
|
||||
status: 'succeeded',
|
||||
result: {
|
||||
draft_payload: {
|
||||
claim_id: 'claim-saved-draft',
|
||||
claim_no: 'A20260220',
|
||||
status: 'submitted',
|
||||
approval_stage: '直属领导审批'
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
throw new Error(`unexpected request: ${normalizedUrl}`)
|
||||
}
|
||||
|
||||
try {
|
||||
const previewMessage = createInlineMessage('assistant', '申请核对表', {
|
||||
id: 'application-preview-1',
|
||||
applicationPreview: {
|
||||
readyToSubmit: true,
|
||||
fields: {
|
||||
applicationType: '差旅费用申请',
|
||||
time: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
days: '4天',
|
||||
transportMode: '火车',
|
||||
amount: '1200元'
|
||||
},
|
||||
missingFields: [],
|
||||
validationIssues: []
|
||||
},
|
||||
draftPayload: {
|
||||
claim_id: 'claim-saved-draft',
|
||||
claim_no: 'A20260220',
|
||||
status: 'draft'
|
||||
}
|
||||
})
|
||||
const harness = buildApplicationPreviewFlowHarness([
|
||||
createInlineMessage('user', '2026-02-20 至 2026-02-23，去上海出差，交通火车，保存草稿'),
|
||||
previewMessage,
|
||||
createInlineMessage('assistant', '### 申请草稿已保存', {
|
||||
draftPayload: previewMessage.draftPayload
|
||||
})
|
||||
])
|
||||
|
||||
const handled = harness.flow.handleInlineApplicationPreviewTextAction(
|
||||
'提交这个单据',
|
||||
createRef(false)
|
||||
)
|
||||
assert.equal(handled, true)
|
||||
await new Promise((resolve) => setTimeout(resolve, 0))
|
||||
|
||||
assert.equal(harness.applicationSubmitConfirmOpen.value, false)
|
||||
assert.equal(requests.length, 1)
|
||||
assert.equal(requests[0].body.context_json.application_edit_claim_id, 'claim-saved-draft')
|
||||
assert.equal(requests[0].body.context_json.application_edit_mode, true)
|
||||
assert.match(harness.conversationMessages.value.at(-1).content, /申请单据已生成/)
|
||||
assert.ok(harness.persisted.value > 0)
|
||||
} finally {
|
||||
globalThis.fetch = originalFetch
|
||||
}
|
||||
})
|
||||
@@ -4,6 +4,7 @@ import test from 'node:test'
|
||||
import {
|
||||
isOrphanInlineApplicationPreviewMessage,
|
||||
isReimbursementCreationIntent,
|
||||
resolveInlineTravelApplicationRequest,
|
||||
resolveInlineApplicationPreviewTextAction,
|
||||
resolveLatestApplicationPreviewMessage,
|
||||
resolveLatestOrphanApplicationPreviewMessage
|
||||
@@ -28,9 +29,24 @@ test('workbench application gate resolves save and submit text actions consisten
|
||||
assert.equal(resolveInlineApplicationPreviewTextAction(' 先保存 '), AI_APPLICATION_ACTION_SAVE_DRAFT)
|
||||
assert.equal(resolveInlineApplicationPreviewTextAction('确认提交'), AI_APPLICATION_ACTION_SUBMIT)
|
||||
assert.equal(resolveInlineApplicationPreviewTextAction('直接提交'), AI_APPLICATION_ACTION_SUBMIT)
|
||||
assert.equal(resolveInlineApplicationPreviewTextAction('提交这个单据'), AI_APPLICATION_ACTION_SUBMIT)
|
||||
assert.equal(resolveInlineApplicationPreviewTextAction('提交这个申请单'), AI_APPLICATION_ACTION_SUBMIT)
|
||||
assert.equal(resolveInlineApplicationPreviewTextAction('继续修改'), '')
|
||||
})
|
||||
|
||||
test('workbench application gate detects compact travel application direct submit intent', () => {
|
||||
const request = resolveInlineTravelApplicationRequest('去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交')
|
||||
|
||||
assert.deepEqual(request, {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText: '去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交',
|
||||
autoSubmit: true
|
||||
})
|
||||
assert.equal(resolveInlineTravelApplicationRequest('去上海出差，辅助国网仿生产服务器部署，交通火车')?.autoSubmit, false)
|
||||
assert.equal(resolveInlineTravelApplicationRequest('帮我查询上海差旅标准'), null)
|
||||
})
|
||||
|
||||
test('workbench application gate resolves latest live or orphan preview message', () => {
|
||||
const messages = [
|
||||
{ id: 'user-1', role: 'user', content: '2月去上海出差' },
|
||||
|
||||
331
web/tests/workbench-ai-intent-planner-model.test.mjs
Normal file
331
web/tests/workbench-ai-intent-planner-model.test.mjs
Normal file
@@ -0,0 +1,331 @@
|
||||
import assert from 'node:assert/strict'
|
||||
import { readFileSync } from 'node:fs'
|
||||
import test from 'node:test'
|
||||
import { fileURLToPath } from 'node:url'
|
||||
|
||||
import {
|
||||
WORKBENCH_AI_INTENT_SOURCE_MODEL,
|
||||
WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK,
|
||||
WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
|
||||
WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT,
|
||||
WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
|
||||
WORKBENCH_AI_STEP_SUBMIT_APPLICATION,
|
||||
WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
|
||||
buildRuleFallbackWorkbenchAiIntentPlan,
|
||||
normalizeWorkbenchAiIntentPlan,
|
||||
resolveExecutableTravelApplicationPlan,
|
||||
shouldRequestWorkbenchAiIntentPlan
|
||||
} from '../src/composables/workbenchAiMode/workbenchAiIntentPlannerModel.js'
|
||||
import { buildInlineApplicationPreview } from '../src/composables/workbenchAiMode/workbenchAiApplicationPreviewModel.js'
|
||||
|
||||
const personalWorkbenchAiModeScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/composables/workbenchAiMode/usePersonalWorkbenchAiMode.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
const stewardFlowScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/composables/workbenchAiMode/useWorkbenchAiStewardFlow.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
const applicationPreviewFlowScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/composables/workbenchAiMode/useWorkbenchAiApplicationPreviewFlow.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
const planningThinkingModelScript = readFileSync(
|
||||
fileURLToPath(new URL('../src/composables/workbenchAiMode/workbenchAiPlanningThinkingModel.js', import.meta.url)),
|
||||
'utf8'
|
||||
)
|
||||
|
||||
test('workbench AI intent planner normalizes model travel application submit plan into executable steps', () => {
|
||||
const plan = normalizeWorkbenchAiIntentPlan({
|
||||
planning_source: 'llm_function_call',
|
||||
tasks: [{
|
||||
task_type: 'expense_application',
|
||||
assigned_agent: 'application_assistant',
|
||||
requested_action: 'submit',
|
||||
confidence: 0.91,
|
||||
ontology_fields: {
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
}
|
||||
}]
|
||||
}, {
|
||||
prompt: '去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交'
|
||||
})
|
||||
|
||||
assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_MODEL)
|
||||
assert.equal(plan.intent, 'create_travel_application')
|
||||
assert.equal(plan.requestedAction, 'submit')
|
||||
assert.deepEqual(plan.steps, [
|
||||
WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
|
||||
WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
|
||||
WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
|
||||
WORKBENCH_AI_STEP_SUBMIT_APPLICATION
|
||||
])
|
||||
assert.deepEqual(plan.ontologyFields, {
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
})
|
||||
assert.deepEqual(plan.slots, {
|
||||
timeRange: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transportMode: '火车'
|
||||
})
|
||||
})
|
||||
|
||||
test('workbench AI intent planner prefers server action steps when present', () => {
|
||||
const plan = normalizeWorkbenchAiIntentPlan({
|
||||
planning_source: 'llm_function_call',
|
||||
tasks: [{
|
||||
task_type: 'expense_application',
|
||||
assigned_agent: 'application_assistant',
|
||||
requested_action: 'submit',
|
||||
confidence: 0.91,
|
||||
ontology_fields: {
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
},
|
||||
action_steps: [
|
||||
{ action_type: 'fill_application_fields' },
|
||||
{ action_type: 'build_application_preview' },
|
||||
{ action_type: 'validate_required_fields' },
|
||||
{ action_type: 'save_application_draft' }
|
||||
]
|
||||
}]
|
||||
}, {
|
||||
prompt: '2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交'
|
||||
})
|
||||
|
||||
assert.deepEqual(plan.steps, [
|
||||
WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
|
||||
WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
|
||||
WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT
|
||||
])
|
||||
})
|
||||
|
||||
test('workbench AI intent planner falls back to rule plan for compact travel direct submit', () => {
|
||||
const plan = buildRuleFallbackWorkbenchAiIntentPlan('去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交')
|
||||
|
||||
assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
|
||||
assert.equal(plan.intent, 'create_travel_application')
|
||||
assert.equal(plan.requestedAction, 'submit')
|
||||
assert.deepEqual(plan.steps, [
|
||||
WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
|
||||
WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
|
||||
WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
|
||||
WORKBENCH_AI_STEP_SUBMIT_APPLICATION
|
||||
])
|
||||
})
|
||||
|
||||
test('workbench AI intent planner detects compact travel save-draft variant before rules are enough', () => {
|
||||
const prompt = '2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。'
|
||||
const plan = buildRuleFallbackWorkbenchAiIntentPlan(prompt)
|
||||
|
||||
assert.equal(shouldRequestWorkbenchAiIntentPlan(prompt), true)
|
||||
assert.equal(shouldRequestWorkbenchAiIntentPlan('帮我查询上海差旅标准'), true)
|
||||
assert.equal(shouldRequestWorkbenchAiIntentPlan('1'), false)
|
||||
assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
|
||||
assert.equal(plan.intent, 'create_travel_application')
|
||||
assert.equal(plan.requestedAction, 'save_draft')
|
||||
assert.deepEqual(plan.steps, [
|
||||
WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
|
||||
WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
|
||||
WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT
|
||||
])
|
||||
assert.deepEqual(resolveExecutableTravelApplicationPlan(plan), {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText: prompt,
|
||||
ontologyFields: {},
|
||||
autoSubmit: false,
|
||||
autoSaveDraft: true
|
||||
})
|
||||
})
|
||||
|
||||
test('workbench AI intent planner turns model fields and action into executable application preview payload', () => {
|
||||
const prompt = '2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。'
|
||||
const plan = normalizeWorkbenchAiIntentPlan({
|
||||
planning_source: 'llm_function_call',
|
||||
tasks: [{
|
||||
task_type: 'expense_application',
|
||||
assigned_agent: 'application_assistant',
|
||||
requested_action: 'save_draft',
|
||||
confidence: 0.95,
|
||||
ontology_fields: {
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
},
|
||||
missing_fields: []
|
||||
}]
|
||||
}, { prompt })
|
||||
|
||||
assert.deepEqual(resolveExecutableTravelApplicationPlan(plan), {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText: prompt,
|
||||
ontologyFields: {
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
},
|
||||
autoSubmit: false,
|
||||
autoSaveDraft: true
|
||||
})
|
||||
})
|
||||
|
||||
test('workbench AI intent planner turns single application candidate flow into executable preview payload', () => {
|
||||
const prompt = '2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车'
|
||||
const plan = normalizeWorkbenchAiIntentPlan({
|
||||
planning_source: 'rule_fallback',
|
||||
plan_status: 'needs_flow_confirmation',
|
||||
pending_flow_confirmation: {
|
||||
status: 'pending',
|
||||
candidate_flows: [{
|
||||
flow_id: 'travel_application',
|
||||
label: '先发起出差申请',
|
||||
confidence: 0.86,
|
||||
ontology_fields: {
|
||||
expense_type: 'travel',
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
},
|
||||
missing_fields: []
|
||||
}]
|
||||
}
|
||||
}, { prompt })
|
||||
|
||||
assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
|
||||
assert.equal(plan.intent, 'create_travel_application')
|
||||
assert.equal(plan.requestedAction, 'preview')
|
||||
assert.deepEqual(resolveExecutableTravelApplicationPlan(plan), {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText: prompt,
|
||||
ontologyFields: {
|
||||
expense_type: 'travel',
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '辅助国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
},
|
||||
autoSubmit: false,
|
||||
autoSaveDraft: false
|
||||
})
|
||||
})
|
||||
|
||||
test('workbench AI application preview prefers model ontology fields over local text guesses', () => {
|
||||
const preview = buildInlineApplicationPreview(
|
||||
'差旅费',
|
||||
'2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。',
|
||||
{ name: '李文静', grade: 'P5', location: '武汉' },
|
||||
{
|
||||
ontologyFields: {
|
||||
time_range: '2026-02-20 至 2026-02-23',
|
||||
location: '上海',
|
||||
reason: '国网仿生产服务器部署',
|
||||
transport_mode: '火车'
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
assert.equal(preview.fields.time, '2026-02-20 至 2026-02-23')
|
||||
assert.equal(preview.fields.location, '上海')
|
||||
assert.equal(preview.fields.reason, '国网仿生产服务器部署')
|
||||
assert.equal(preview.fields.transportMode, '火车')
|
||||
})
|
||||
|
||||
test('workbench AI intent planner rejects policy question and resolves executable application request', () => {
|
||||
assert.equal(buildRuleFallbackWorkbenchAiIntentPlan('帮我查询上海差旅标准'), null)
|
||||
|
||||
const request = resolveExecutableTravelApplicationPlan(
|
||||
buildRuleFallbackWorkbenchAiIntentPlan('去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交')
|
||||
)
|
||||
|
||||
assert.deepEqual(request, {
|
||||
expenseType: 'travel',
|
||||
expenseTypeLabel: '差旅费',
|
||||
sourceText: '去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交',
|
||||
ontologyFields: {},
|
||||
autoSubmit: true,
|
||||
autoSaveDraft: false
|
||||
})
|
||||
})
|
||||
|
||||
test('workbench AI mode asks steward model plan before fallback execution', () => {
|
||||
assert.match(stewardFlowScript, /async function resolveInlineExecutionPlan\(prompt, entry = \{\}, files = \[\], options = \{\}\)/)
|
||||
assert.match(stewardFlowScript, /fetchStewardPlan\(planRequest/)
|
||||
assert.match(stewardFlowScript, /timeoutMs:\s*35000/)
|
||||
assert.match(personalWorkbenchAiModeScript, /async function executeModelPlannedWorkbenchIntent\(cleanPrompt, entry = \{\}, files = \[\]\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files,\s*\{/)
|
||||
assert.match(personalWorkbenchAiModeScript, /normalizeWorkbenchAiIntentPlan\(modelPlan,\s*\{\s*prompt:\s*cleanPrompt/)
|
||||
assert.match(personalWorkbenchAiModeScript, /buildRuleFallbackWorkbenchAiIntentPlan\(cleanPrompt\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /shouldRequestWorkbenchAiIntentPlan\(cleanPrompt\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /resolveExecutableTravelApplicationPlan\(intentPlan\)/)
|
||||
assert.doesNotMatch(personalWorkbenchAiModeScript, /fallbackIntentPlan/)
|
||||
assert.match(personalWorkbenchAiModeScript, /autoSaveDraft:\s*travelApplicationRequest\.autoSaveDraft/)
|
||||
assert.match(personalWorkbenchAiModeScript, /ontologyFields:\s*travelApplicationRequest\.ontologyFields/)
|
||||
assert.match(applicationPreviewFlowScript, /options\.autoSaveDraft/)
|
||||
assert.match(applicationPreviewFlowScript, /ontologyFields:\s*options\.ontologyFields/)
|
||||
assert.match(applicationPreviewFlowScript, /executeInlineApplicationPreviewAction\(AI_APPLICATION_ACTION_SAVE_DRAFT/)
|
||||
assert.match(applicationPreviewFlowScript, /buildInlineApplicationPreview\([\s\S]*ontologyFields:\s*options\.ontologyFields/)
|
||||
assert.doesNotMatch(personalWorkbenchAiModeScript, /const travelApplicationRequest = resolveInlineTravelApplicationRequest\(cleanPrompt\)/)
|
||||
})
|
||||
|
||||
test('workbench AI mode shows a visible planning response before waiting for steward model plan', () => {
|
||||
assert.match(personalWorkbenchAiModeScript, /function startModelPlanningConversation\(cleanPrompt, entry = \{\}\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /conversationMessages\.value\.push\(createInlineMessage\('user', cleanPrompt\)\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /正在识别意图，准备拆解申请、报销和附件任务/)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/const plannerPendingMessage = startModelPlanningConversation\(cleanPrompt, entry\)[\s\S]*await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files,\s*\{/
|
||||
)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/pendingMessageId:\s*plannerPendingMessage\?\.id/
|
||||
)
|
||||
assert.match(applicationPreviewFlowScript, /options\.pendingMessageId/)
|
||||
})
|
||||
|
||||
test('workbench AI mode streams planning thinking into the pending message', () => {
|
||||
assert.match(planningThinkingModelScript, /buildModelPlanningProgressSchedule/)
|
||||
assert.match(planningThinkingModelScript, /判断办理意图/)
|
||||
assert.match(planningThinkingModelScript, /抽取关键信息/)
|
||||
assert.match(planningThinkingModelScript, /规划执行步骤/)
|
||||
assert.match(planningThinkingModelScript, /准备兜底策略/)
|
||||
assert.match(personalWorkbenchAiModeScript, /function startModelPlanningProgressUpdates\(messageId\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /globalThis\.setTimeout\(\(\) => \{\s*updateModelPlanningThinkingEvent\(messageId, event\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /const stopPlanningProgressUpdates = startModelPlanningProgressUpdates\(plannerPendingMessage\.id\)/)
|
||||
assert.match(personalWorkbenchAiModeScript, /stopPlanningProgressUpdates\(\)/)
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files,\s*\{\s*pendingMessageId:\s*plannerPendingMessage\.id\s*\}\)/
|
||||
)
|
||||
assert.match(stewardFlowScript, /async function resolveInlineExecutionPlan\(prompt, entry = \{\}, files = \[\], options = \{\}\)/)
|
||||
assert.match(stewardFlowScript, /fetchInlineStewardPlan\(planningMessageId, planRequest,\s*\{[\s\S]*includeAnswerDelta:\s*false/)
|
||||
assert.match(applicationPreviewFlowScript, /mergeWorkbenchAiThinkingEvents\(previousThinkingEvents,\s*\[/)
|
||||
})
|
||||
|
||||
test('workbench AI mode reuses planning pending message for regular steward replies', () => {
|
||||
assert.match(
|
||||
personalWorkbenchAiModeScript,
|
||||
/stewardFlow\.requestInlineAssistantReply\(cleanPrompt, entry, files,\s*\{\s*pendingMessageId:\s*plannerPendingMessage\.id\s*\}\)/
|
||||
)
|
||||
assert.doesNotMatch(
|
||||
personalWorkbenchAiModeScript,
|
||||
/replaceInlineMessage\(plannerPendingMessage\.id,\s*createInlineMessage\('assistant', '已完成意图识别，继续为您整理回复。'/
|
||||
)
|
||||
assert.match(stewardFlowScript, /async function requestInlineAssistantReply\(prompt, entry = \{\}, files = \[\], options = \{\}\)/)
|
||||
assert.match(stewardFlowScript, /const reusablePendingMessageId = String\(options\.pendingMessageId \|\| ''\)\.trim\(\)/)
|
||||
assert.match(stewardFlowScript, /reusablePendingMessageId \? replaceInlineMessage\(reusablePendingMessageId, pendingMessage\) : conversationMessages\.value\.push\(pendingMessage\)/)
|
||||
})
|
||||
Reference in New Issue
Block a user