feat:新增投顾agent和nl2sqlagent

agent/advisor_agent/intent/recommend.py

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+"""基金推荐候选过滤与排序。"""
+from __future__ import annotations
+
+from collections import defaultdict
+from typing import Iterable
+
+from common.common_const import MEMORY_INFO_TYPE_OPINION
+from common.suitability import check_suitability
+
+
+def _opinion_bonuses(memories: Iterable[dict]) -> dict[str, float]:
+    bonuses: dict[str, float] = defaultdict(float)
+    for memory in memories:
+        if memory.get("info_type") != MEMORY_INFO_TYPE_OPINION:
+            continue
+        product_code = memory.get("product_code")
+        if product_code:
+            bonuses[str(product_code)] += float(memory.get("score", 0.0) or 0.0)
+    return bonuses
+
+
+def recommend_candidates(
+    customer_risk: str,
+    candidates: Iterable[dict],
+    *,
+    memories: Iterable[dict] = (),
+) -> list[dict]:
+    """硬过滤不适当产品，再按业绩和主观观点排序。"""
+    bonuses = _opinion_bonuses(memories)
+    result = []
+    for candidate in candidates:
+        suitability = check_suitability(customer_risk, candidate.get("risk_level", ""))
+        if not suitability.ok:
+            continue
+        item = dict(candidate)
+        base_score = float(item.get("performance_score", 0.0) or 0.0)
+        item["recommendation_score"] = base_score + bonuses.get(
+            str(item.get("product_code")), 0.0
+        )
+        result.append(item)
+    return sorted(
+        result,
+        key=lambda item: item["recommendation_score"],
+        reverse=True,
+    )