fix(auto-repair): 修復三個阻礙自動修復的根本原因

1. playbook_rag: Ollama embedding http_client 滾動重啟後 is_closed
   - 新增 _get_http_client() 偵測 is_closed 自動重建
   - singleton get_playbook_rag_service() 加 is_closed 重建判斷

2. telegram: 加入 ai_model 欄位顯示底層判斷模型
   - TelegramMessage.ai_model 欄位
   - format() / format_with_nemotron() 顯示 "Nemotron (nemotron-70b)"
   - openclaw proposal_dict 加入 model 欄位
   - decision_manager / send_approval_card 串接

3. DB: 清除 9 筆 3/26 殭屍 PENDING (mock_fallback CRITICAL 測試記錄)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

apps/api/src/services/decision_manager.py

@@ -110,6 +110,7 @@ async def _push_decision_to_telegram(
         confidence = proposal_data.get("confidence", 0.0)  # 🔴 預設 0.0 表示未經 AI 分析
         source = proposal_data.get("source", "unknown")
         ai_provider = proposal_data.get("provider", "")  # 2026-03-29 ogt: AI 模型來源
+        ai_model = proposal_data.get("model", "")  # 2026-04-04 ogt: 底層模型名稱
 
         # 2026-04-02 ogt: Phase 22 Nemotron 協作資料
         nemotron_enabled = proposal_data.get("nemotron_enabled", False)
@@ -132,6 +133,7 @@ async def _push_decision_to_telegram(
             confidence=confidence,
             namespace=incident.signals[0].labels.get("namespace", "default") if incident.signals else "default",
             ai_provider=ai_provider,  # 2026-03-29 ogt: 顯示 AI 模型來源
+            ai_model=ai_model,  # 2026-04-04 ogt: 底層模型名稱
             # 2026-04-02 ogt: Phase 22 Nemotron 協作 (ADR-044)
             nemotron_enabled=nemotron_enabled,
             nemotron_tools=nemotron_tools,

apps/api/src/services/openclaw.py

@@ -1553,6 +1553,7 @@ Focus on:
                 "signoz_correlation": result.signoz_correlation,
                 "from_cache": from_cache,
                 "provider": provider,
+                "model": self._get_model_name(provider),  # 2026-04-04 ogt: 底層模型名稱
                 "ai_tokens": ai_tokens,
                 "ai_cost": ai_cost,
             }

apps/api/src/services/playbook_rag.py

@@ -153,11 +153,24 @@ class PlaybookRAGService:
     # Embedding Operations
     # =========================================================================
 
+    async def _get_http_client(self) -> httpx.AsyncClient:
+        """
+        取得有效的 HTTP Client，若已關閉則重建
+
+        2026-04-04 ogt: 修復滾動重啟後 is_closed=True 導致 embedding 失敗
+        """
+        if self._http_client.is_closed:
+            logger.warning("playbook_rag_http_client_closed_rebuilding")
+            from src.core.http_client import get_general_client
+            self._http_client = await get_general_client()
+        return self._http_client
+
     async def embed_text(self, text: str) -> list[float] | None:
         """
         使用 Ollama 生成文字 embedding
 
         2026-03-27 ogt: 改用 DI 注入的 http_client (P1 違規修復)
+        2026-04-04 ogt: 加入 is_closed 自動重建機制
 
         Args:
             text: 要向量化的文字
@@ -166,8 +179,8 @@ class PlaybookRAGService:
             向量 (768 維) 或 None (失敗時)
         """
         try:
-            # 使用 DI 注入的 http_client，設置單次請求 timeout
-            response = await self._http_client.post(
+            client = await self._get_http_client()
+            response = await client.post(
                 f"{self.ollama_url}/api/embeddings",
                 json={
                     "model": self.embedding_model,
@@ -545,7 +558,8 @@ async def get_playbook_rag_service() -> PlaybookRAGService:
     2026-03-27 ogt: 改用 DI 注入，從 Lifespan 取得 http_client 和 Redis
     """
     global _rag_service
-    if _rag_service is None:
+    # 2026-04-04 ogt: 滾動重啟後 http_client is_closed，需重建 singleton
+    if _rag_service is None or _rag_service._http_client.is_closed:
         # 延遲導入避免循環依賴
         from src.core.http_client import get_general_client
         from src.core.redis_client import get_redis

apps/api/src/services/telegram_gateway.py

@@ -162,6 +162,8 @@ class TelegramMessage:
     anomaly_frequency: dict | None = None  # AnomalyCounter 統計
     # 2026-03-29 ogt: AI Provider 來源顯示
     ai_provider: str = ""  # ollama/gemini/claude/expert_system/mock
+    # 2026-04-04 ogt: 底層模型名稱 (e.g. qwen2.5:7b-instruct, nemotron-70b)
+    ai_model: str = ""
 
     # ==========================================================================
     # Phase 22: Nemotron 協作欄位 (ADR-044)
@@ -250,18 +252,20 @@ class TelegramMessage:
 
         # 2026-03-29 ogt: 根據 confidence + ai_provider 動態顯示來源
         # confidence > 0 = 真實 AI 分析, confidence == 0 = 規則匹配/降級
+        # 2026-04-04 ogt: 加入 ai_model 顯示底層模型名稱
         if self.confidence > 0 and self.ai_provider:
-            # 顯示具體 AI 模型
             provider_names = {
                 "ollama": "Ollama",
                 "gemini": "Gemini",
                 "claude": "Claude",
+                "nvidia": "Nemotron",
                 "openclaw_nemo": "OpenClaw Nemo",
                 "openclaw_nvidia_nim": "OpenClaw Nemo",
                 "openclaw_qwen": "OpenClaw Nemo",
             }
             provider_display = provider_names.get(self.ai_provider.lower(), self.ai_provider.upper())
-            source_label = f"🤖 <b>{provider_display} 仲裁</b>"
+            model_suffix = f" ({html.escape(self.ai_model)})" if self.ai_model else ""
+            source_label = f"🤖 <b>{provider_display} 仲裁</b>{model_suffix}"
         elif self.confidence > 0:
             source_label = "🤖 <b>AI 仲裁判定</b>"
         else:
@@ -351,6 +355,7 @@ class TelegramMessage:
         safe_downtime = html.escape(self.estimated_downtime)
 
         # AI Provider 顯示
+        # 2026-04-04 ogt: 加入 ai_model 顯示底層模型名稱
         if self.confidence > 0 and self.ai_provider:
             provider_names = {
                 "ollama": "Ollama",
@@ -362,7 +367,8 @@ class TelegramMessage:
                 "openclaw_qwen": "OpenClaw Nemo",
             }
             provider_display = provider_names.get(self.ai_provider.lower(), self.ai_provider.upper())
-            source_label = f"🤖 <b>{provider_display} 仲裁</b>"
+            model_suffix = f" ({html.escape(self.ai_model)})" if self.ai_model else ""
+            source_label = f"🤖 <b>{provider_display} 仲裁</b>{model_suffix}"
         elif self.confidence > 0:
             source_label = "🤖 <b>OpenClaw 仲裁</b>"
         else:
@@ -1268,6 +1274,8 @@ class TelegramGateway:
         anomaly_frequency: dict | None = None,
         # 2026-03-29 ogt: AI Provider 來源顯示
         ai_provider: str = "",
+        # 2026-04-04 ogt: 底層模型名稱
+        ai_model: str = "",
         # 2026-04-02 ogt: Phase 22 Nemotron 協作 (ADR-044)
         nemotron_enabled: bool = False,
         nemotron_tools: list[dict] | None = None,
@@ -1335,6 +1343,8 @@ class TelegramGateway:
             anomaly_frequency=anomaly_frequency,
             # 2026-03-29 ogt: AI Provider 來源顯示
             ai_provider=ai_provider,
+            # 2026-04-04 ogt: 底層模型名稱
+            ai_model=ai_model,
             # 2026-04-02 ogt: Phase 22 Nemotron 協作 (ADR-044)
             nemotron_enabled=nemotron_enabled,
             nemotron_tools=nemotron_tools,