新功能：个性化推荐算法

server/app/features/personalized_reco/observability/utils.py

@@ -0,0 +1,61 @@
+from __future__ import annotations
+
+from typing import Optional
+
+from app.features.personalized_reco.observability.types import EmptyReason, MissingFields
+
+
+def compute_missing_fields(user_profile: object) -> MissingFields:
+    """
+    判定用户画像缺失字段（对齐算法规则 V1.2 口径）。
+
+    规则：
+    - need：user_profile.need 为空对象 {} 或不存在
+    - context：user_profile.context 为空对象 {} 或不存在
+    - emotion：user_profile.emotion_score 为 None 或不存在
+    """
+
+    need = getattr(user_profile, "need", None)
+    context = getattr(user_profile, "context", None)
+    emotion_score = getattr(user_profile, "emotion_score", None)
+
+    need_missing = not bool(need)
+    context_missing = not bool(context)
+    emotion_missing = emotion_score is None
+
+    return MissingFields(need=need_missing, context=context_missing, emotion=emotion_missing)
+
+
+def compute_empty_reason(
+    *,
+    served_k: int,
+    candidate_pool_size_raw: int,
+    candidate_pool_size_after_hard_filter: int,
+    candidate_pool_size_after_freqcap: int,
+) -> Optional[EmptyReason]:
+    """
+    判定 empty_reason（served_k=0 必填）。
+
+    规则（对齐 plan）：
+    - served_k>0 -> None
+    - raw==0 -> pool_empty
+    - raw>0 且 after_hard_filter==0 -> hard_filter_all
+    - after_freqcap==0 -> freqcap_all
+    - 其他 -> unknown
+    """
+
+    if int(served_k) > 0:
+        return None
+
+    raw = int(candidate_pool_size_raw)
+    after_hard = int(candidate_pool_size_after_hard_filter)
+    after_freqcap = int(candidate_pool_size_after_freqcap)
+
+    if raw == 0:
+        return "pool_empty"
+    if raw > 0 and after_hard == 0:
+        return "hard_filter_all"
+    if after_freqcap == 0:
+        return "freqcap_all"
+    return "unknown"
+