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。

server/src/app/services/risk_rule_generation_interpreter.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+from typing import Any
+
 COMPOSITE_RULE_TEMPLATE_KEY = "composite_rule_v1"
 
 COMPOSITE_RULE_OPERATORS = {
@@ -12,6 +14,62 @@ COMPOSITE_RULE_OPERATORS = {
     "overlap",
     "not_overlap",
     "date_outside_range",
+    "numeric_compare",
+    "duplicate_value",
     "contains_any",
     "not_contains_any",
 }
+
+
+def build_dsl_from_semantic_plan(semantic_plan: dict[str, Any]) -> dict[str, Any]:
+    """把模型语义计划转换成可交给 validator 继续规范化的 DSL 草稿。"""
+
+    if not isinstance(semantic_plan, dict):
+        return {}
+    text_parts = _semantic_text_parts(semantic_plan)
+    field_keys = _semantic_field_keys(semantic_plan)
+    if not text_parts and not field_keys:
+        return {}
+    return {
+        "template_key": COMPOSITE_RULE_TEMPLATE_KEY,
+        "field_keys": field_keys,
+        "description": str(semantic_plan.get("rule_intent") or "").strip(),
+        "condition_summary": "；".join(text_parts)[:800],
+        "keywords": [],
+        "rule_ir": {
+            "facts": field_keys,
+            "conditions": text_parts,
+            "hit_logic": "由 DSL validator 根据字段本体和语义步骤生成受控条件",
+        },
+    }
+
+
+def _semantic_text_parts(semantic_plan: dict[str, Any]) -> list[str]:
+    parts: list[str] = []
+    for key in ("rule_intent", "scope", "judgment_steps", "exception_conditions", "risk_action"):
+        parts.extend(_flatten_semantic_text(semantic_plan.get(key)))
+    return [item for index, item in enumerate(parts) if item and item not in parts[:index]]
+
+
+def _semantic_field_keys(semantic_plan: dict[str, Any]) -> list[str]:
+    keys: list[str] = []
+    for value in (semantic_plan.get("required_fields"), semantic_plan.get("fields")):
+        for item in value if isinstance(value, list) else []:
+            key = item if isinstance(item, str) else next(
+                (item.get(name) for name in ("field", "key", "field_key") if isinstance(item, dict) and item.get(name)),
+                "",
+            )
+            text = str(key or "").strip()
+            if "." in text and text not in keys:
+                keys.append(text)
+    return keys
+
+
+def _flatten_semantic_text(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [value.strip()] if value.strip() else []
+    if isinstance(value, list):
+        return [item for value_item in value for item in _flatten_semantic_text(value_item)]
+    if isinstance(value, dict):
+        return [item for value_item in value.values() for item in _flatten_semantic_text(value_item)]
+    return []