feat: 完成 issue #74 [Ti-1] 报警解释 Prompt 模板与 RAG 接入

templates/ti-cl4/llm-scenarios/scenarios.py

@@ -19,7 +19,7 @@ from typing import Callable, Dict, List, Optional
 from llm_gateway.gateway import GatewayResult, LLMGateway
 from llm_gateway.prompts import PromptRegistry
 from llm_gateway.router import SensitivityRouter
-from rag_kb import RagKnowledgeBase, load_kb_config
+from rag_kb import KnowledgeSourceKind, RagKnowledgeBase, load_kb_config
 
 # ---------------------------------------------------------------------------
 # 场景配置资产路径
@@ -41,6 +41,12 @@ def scenarios_config_path() -> str:
     return os.path.join(_scenarios_dir(), "config", "scenarios.template.yaml")
 
 
+def alarm_config_path() -> str:
+    """报警解释场景配置资产（alarm_explain.template.yaml）路径。"""
+    return os.path.join(_scenarios_dir(), "config",
+                        "alarm_explain.template.yaml")
+
+
 def prompts_config_path() -> str:
     """复用 llm-gateway 提示词版本库资产路径。"""
     return os.path.join(_repo_root(), "core", "llm-gateway", "config",
@@ -110,6 +116,7 @@ class TiScenarioRunner:
         prompts: Optional[PromptRegistry] = None,
         router: Optional[SensitivityRouter] = None,
         kb_loader: Callable[[str], str] = demo_kb_loader,
+        alarm_config: Optional[dict] = None,
     ) -> None:
         prompts = prompts or PromptRegistry.from_template_config(prompts_config_path())
         kb = kb or RagKnowledgeBase.from_template_config(
@@ -117,6 +124,8 @@ class TiScenarioRunner:
         )
         router = router or SensitivityRouter.from_template_config(router_config_path())
         self.kb = kb
+        # 报警解释场景配置（issue #74：sop 类目检索 + 检索阈值）
+        self.alarm_cfg = alarm_config or self._load_alarm_config()
         if gateway is not None:
             # 注入 gateway：由调用方负责 prompt_name / 高利害配置
             self._gateways = {
@@ -141,12 +150,35 @@ class TiScenarioRunner:
 
     # -- 场景 1：报警根因解释（高利害） -----------------------------------
 
+    @staticmethod
+    def _load_alarm_config() -> dict:
+        """加载报警解释场景配置资产（issue #74）。"""
+        import yaml
+
+        with open(alarm_config_path(), "r", encoding="utf-8") as fh:
+            return (yaml.safe_load(fh) or {}).get("alarm_explain", {})
+
     def explain_alarm(self, alarm: str, confidence: float = 1.0,
-                      top_k: int = 3) -> GatewayResult:
-        """解释一条报警的可能原因与处置建议（RAG 检索异常处置 SOP）。"""
-        hits = self.kb.search(alarm, top_k=top_k,
-                              categories=None)
-        sources = [h.source for h in hits]
+                      top_k: Optional[int] = None) -> GatewayResult:
+        """解释一条报警的可能原因与处置建议。
+
+        RAG 接入（issue #74）：只检索 **sop 知识域**（异常处置 SOP），
+        并按 min_score 过滤——低于阈值视为未命中，降级提示人工确认
+        （高利害场景宁缺毋滥，避免无据回答）。
+        """
+        rag = self.alarm_cfg.get("rag", {}) or {}
+        cat_names = rag.get("categories")
+        categories = ([KnowledgeSourceKind(c) for c in cat_names]
+                      if cat_names else None)
+        top_k = top_k or int(rag.get("top_k", 3))
+        min_score = float(rag.get("min_score", 0.0))
+        hits = self.kb.search(alarm, top_k=top_k, categories=categories)
+        hits = [h for h in hits if h.score >= min_score]
+        if hits:
+            sources = [h.source for h in hits]
+        else:
+            # 未检索到 SOP：降级提示人工确认（来源占位，阻断无据回答）
+            sources = ["未检索到相关 SOP，请人工确认"]
         return self._gateways["alarm_explain"].ask(
             alarm, rag_context=sources, confidence=confidence,
         )