feat(api): Phase 13.3 智能路由 (#85-87)

- IntentClassifier: 意圖分類 (告警/部署/查詢/維運/審查)
- ComplexityScorer: 複雜度評分 (1-5 分)
- AIRouter: 動態模型選擇 (整合 Intent + Complexity)
- 測試: 完整單元測試覆蓋

Phase 13.3 設計: project_phase13_3_smart_router.md

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

apps/api/src/services/intent_classifier.py

@@ -0,0 +1,149 @@
+"""
+Intent Classifier - Phase 13.3 #85
+===================================
+快速意圖分類，用於智能路由
+
+目標: < 100ms 延遲
+策略: 關鍵字優先 → 小模型備援
+
+Phase 13.3 (2026-03-26): 初始實作
+"""
+
+import re
+from enum import Enum
+
+import structlog
+
+from src.core.config import settings
+
+logger = structlog.get_logger(__name__)
+
+
+class IntentType(Enum):
+    """意圖類型"""
+
+    ALERT_TRIAGE = "alert_triage"  # 告警分流/處理
+    DEPLOYMENT = "deployment"  # 部署操作 (kubectl, rollout)
+    QUERY = "query"  # 資訊查詢 (狀態, 日誌)
+    MAINTENANCE = "maintenance"  # 維運操作 (重啟, 擴容)
+    CODE_REVIEW = "code_review"  # 程式碼審查
+    UNKNOWN = "unknown"
+
+
+# 關鍵字映射 (優先匹配，0ms)
+INTENT_KEYWORDS: dict[IntentType, list[str]] = {
+    IntentType.ALERT_TRIAGE: [
+        "alert", "告警", "警報", "異常", "error", "critical", "warning",
+        "高負載", "high cpu", "memory", "oom", "crash", "down",
+    ],
+    IntentType.DEPLOYMENT: [
+        "deploy", "部署", "rollout", "kubectl apply", "helm", "release",
+        "版本", "upgrade", "更新", "上線",
+    ],
+    IntentType.QUERY: [
+        "查詢", "狀態", "status", "describe", "get", "list", "日誌", "log",
+        "哪個", "什麼", "how many", "多少",
+    ],
+    IntentType.MAINTENANCE: [
+        "restart", "重啟", "scale", "擴容", "縮容", "rollback", "回滾",
+        "維護", "maintenance", "patch", "修補",
+    ],
+    IntentType.CODE_REVIEW: [
+        "review", "審查", "pr", "pull request", "commit", "diff",
+        "程式碼", "code", "merge",
+    ],
+}
+
+
+class IntentClassifier:
+    """
+    意圖分類器
+
+    使用兩階段分類策略:
+    1. 關鍵字快速匹配 (0ms)
+    2. 小模型 LLM 分類 (< 100ms) - 備援
+    """
+
+    # 小模型，低延遲
+    MODEL = "qwen2.5:1b"
+
+    def __init__(self):
+        self._keyword_cache: dict[str, IntentType] = {}
+
+    async def classify(self, text: str) -> IntentType:
+        """
+        分類意圖
+
+        Args:
+            text: 用戶輸入或告警內容
+
+        Returns:
+            IntentType: 分類結果
+        """
+        text_lower = text.lower()
+
+        # 階段 1: 關鍵字快速匹配 (0ms)
+        intent = self._keyword_match(text_lower)
+        if intent != IntentType.UNKNOWN:
+            logger.debug(
+                "intent_classified_by_keyword",
+                intent=intent.value,
+                text_preview=text[:50],
+            )
+            return intent
+
+        # 階段 2: LLM 分類 (< 100ms)
+        # 目前先用關鍵字，LLM 整合待 Qwen 1B 部署
+        logger.debug(
+            "intent_fallback_to_unknown",
+            text_preview=text[:50],
+        )
+        return IntentType.UNKNOWN
+
+    def _keyword_match(self, text: str) -> IntentType:
+        """關鍵字匹配"""
+        # 檢查快取
+        cache_key = text[:100]
+        if cache_key in self._keyword_cache:
+            return self._keyword_cache[cache_key]
+
+        # 計算每個意圖的匹配分數
+        scores: dict[IntentType, int] = {}
+
+        for intent, keywords in INTENT_KEYWORDS.items():
+            score = 0
+            for keyword in keywords:
+                if keyword in text:
+                    score += 1
+                    # 完整匹配加分
+                    if re.search(rf"\b{re.escape(keyword)}\b", text):
+                        score += 1
+            if score > 0:
+                scores[intent] = score
+
+        if not scores:
+            return IntentType.UNKNOWN
+
+        # 選擇最高分
+        best_intent = max(scores, key=lambda k: scores[k])
+
+        # 快取結果
+        self._keyword_cache[cache_key] = best_intent
+
+        return best_intent
+
+    def classify_sync(self, text: str) -> IntentType:
+        """同步版本 (僅關鍵字匹配)"""
+        return self._keyword_match(text.lower())
+
+
+# 單例
+_classifier: IntentClassifier | None = None
+
+
+def get_intent_classifier() -> IntentClassifier:
+    """取得 IntentClassifier 單例"""
+    global _classifier
+    if _classifier is None:
+        _classifier = IntentClassifier()
+    return _classifier