feat: 新增风险图谱算法与系统仪表盘及操作反馈体系

后端新增风险图谱算法模块、风险观察与反馈服务、规则 DSL
校验器和可解释性引擎,完善系统仪表盘和财务仪表盘统计,
优化 agent 运行和编排执行链路,清理旧开发文档,前端新增
系统趋势、负载热力图等多种仪表盘图表组件,完善操作反馈
对话框和工作台日期选择器,优化报销创建和审批详情交互,
补充单元测试覆盖。
This commit is contained in:
caoxiaozhu
2026-05-30 15:46:51 +08:00
parent 4c59941ec6
commit 7989f3a159
314 changed files with 30073 additions and 20626 deletions

View File

@@ -44,8 +44,10 @@ class AccountBehaviorProfileService(EmployeeBehaviorProfileMetricHelpers):
empty_reason="当前账号未匹配员工目录,无法形成审批场景员工画像。",
)
runs = self._fetch_account_runs(identifiers, datetime.now(UTC) - timedelta(days=window_days))
if not runs:
cutoff = datetime.now(UTC) - timedelta(days=window_days)
runs = self._fetch_account_runs(identifiers, cutoff)
usage_duration_metrics = self._resolve_usage_duration_metrics(identifiers, cutoff, runs)
if not runs and not usage_duration_metrics["online_duration_ms"]:
return EmployeeProfileLatestRead(
employee_id=account_id,
employee_name=account_name,
@@ -57,6 +59,7 @@ class AccountBehaviorProfileService(EmployeeBehaviorProfileMetricHelpers):
result = self._calculate_account_ai_usage_profile(
runs=runs,
usage_duration_metrics=usage_duration_metrics,
window_days=window_days,
expense_type_scope=expense_type_scope,
)
@@ -100,6 +103,7 @@ class AccountBehaviorProfileService(EmployeeBehaviorProfileMetricHelpers):
self,
*,
runs: list[AgentRun],
usage_duration_metrics: dict[str, Any],
window_days: int,
expense_type_scope: str,
):
@@ -108,7 +112,6 @@ class AccountBehaviorProfileService(EmployeeBehaviorProfileMetricHelpers):
tool for tool in tool_calls if str(tool.status or "").lower() not in {"success", "ok"}
]
estimated_tokens = self._estimate_tokens(runs)
duration_ms = self._sum_agent_run_duration_ms(runs)
token_mode = "estimated_token_count" if estimated_tokens else "unavailable"
return evaluate_weighted_profile(
@@ -159,8 +162,7 @@ class AccountBehaviorProfileService(EmployeeBehaviorProfileMetricHelpers):
"token_count_mode": token_mode,
"estimated_token_count": estimated_tokens,
"exact_token_count": None,
"ai_run_duration_ms": duration_ms,
"ai_run_duration_mode": "elapsed_or_tool_call_fallback",
**usage_duration_metrics,
},
)