feat:修复客服agent功能

agent/advisor_agent/data_query.py

@@ -24,12 +24,43 @@ from repositories.fin_holdings import FinHoldingsRepo
 from repositories.fin_product import FinProductRepo
 
 
+def enrich_customer_rows(
+    rows: list[dict[str, Any]],
+    columns: list[str],
+    name_by_id: dict[int, str],
+) -> dict[str, Any]:
+    """为查询结果补充客户姓名，并生成可直接展示的姓名摘要。"""
+    id_keys = ("customer_id", "客户ID", "客户编号", "客户_id")
+    enriched = [dict(row) for row in rows]
+    names: list[str] = []
+    for row in enriched:
+        customer_id = next((row.get(key) for key in id_keys if row.get(key) is not None), None)
+        try:
+            customer_id = int(customer_id)
+        except (TypeError, ValueError):
+            continue
+        name = name_by_id.get(customer_id)
+        if name:
+            row["客户姓名"] = name
+            names.append(f"客户{customer_id}（{name}）")
+    output_columns = list(columns)
+    if any("客户姓名" in row for row in enriched) and "客户姓名" not in output_columns:
+        insert_at = next(
+            (index + 1 for index, column in enumerate(output_columns) if column in id_keys),
+            len(output_columns),
+        )
+        output_columns.insert(insert_at, "客户姓名")
+    return {"rows": enriched, "columns": output_columns, "name_summary": "、".join(dict.fromkeys(names))}
+
+
 def _is_current_holdings_query(question: str) -> bool:
     text = "".join((question or "").split())
     return any(term in text for term in ("当前持仓", "目前持仓", "现有持仓", "持仓明细", "持仓情况"))
 
 
-async def _query_current_holdings(db, *, customer_id: int, trace_id: str) -> dict[str, Any]:
+async def _query_current_holdings(
+    db, *, customer_id: int, trace_id: str, customer_name: str | None = None
+) -> dict[str, Any]:
     holdings = await FinHoldingsRepo(db).list_by_customer(customer_id, status="持有中")
     product_repo = FinProductRepo(db)
     rows: list[dict[str, Any]] = []
@@ -60,7 +91,8 @@ async def _query_current_holdings(db, *, customer_id: int, trace_id: str) -> dic
         "truncated": False,
         "summary": f"当前持仓共 {len(rows)} 条记录。",
         "answer": (
-            f"当前持有 {len(rows)} 只基金，总市值约 {total_value:.2f} 元。"
+            (f"客户{customer_id}（{customer_name}）" if customer_name else f"客户{customer_id}")
+            + f"当前持有 {len(rows)} 只基金，总市值约 {total_value:.2f} 元。"
             + (f"包括：{'、'.join(names[:6])}。" if names else "")
         ),
         "sql": None,
@@ -108,11 +140,25 @@ async def execute_advisor_data_query(
         await ensure_customer_access(db, advisor_id=advisor_id, customer_id=customer_id)
         customer_ids = [customer_id]
 
+    name_by_id: dict[int, str] = {}
+    try:
+        relation_rows = await CustomerRelationRepo(db).list_customer_rows(
+            advisor_id=advisor_id, limit=max(len(customer_ids), 100)
+        )
+        name_by_id = {
+            int(account.id): account.real_name
+            for _relation, account, _profile in relation_rows
+            if account.real_name
+        }
+    except Exception:  # noqa: BLE001 姓名增强失败不阻断数据查询
+        pass
+
     if scope == "customer" and _is_current_holdings_query(question):
         return await _query_current_holdings(
             db,
             customer_id=customer_id,
             trace_id=trace_id,
+            customer_name=name_by_id.get(customer_id),
         )
     permission = await load_query_permission(db, advisor_id)
     if not permission.get("can_query", False):
@@ -168,6 +214,12 @@ async def execute_advisor_data_query(
     except (EmbeddingError, LLMFailError) as exc:
         raise QueryServiceError("投顾 Agent 依赖服务不可用，请检查 LLM/Embedding 服务连接") from exc
     payload = asdict(result)
+    enriched = enrich_customer_rows(payload.get("rows", []), payload.get("columns", []), name_by_id)
+    payload["rows"] = enriched["rows"]
+    payload["columns"] = enriched["columns"]
+    if enriched["name_summary"]:
+        existing_answer = payload.get("answer") or payload.get("summary") or ""
+        payload["answer"] = f"{existing_answer.rstrip('。')}。客户姓名：{enriched['name_summary']}。"
     payload["sql"] = None
     payload["customer_id"] = customer_id
     return payload

agent/advisor_agent/intent/generation_flow.py

@@ -71,6 +71,7 @@ async def generate_recommendation_draft(
     memories: list[dict] | None = None,
     llm_client=None,
     llm_timeout: float = 5.0,
+    customer_context: dict | None = None,
 ):
     draft_data = build_recommendation_draft(
         customer_id=customer_id,
@@ -87,7 +88,10 @@ async def generate_recommendation_draft(
             user_prompt=(
                 "请根据以下候选基金和客户记忆生成简洁推荐说明："
                 + json.dumps(
-                    {"candidates": candidates, "memories": memories or []},
+                    {
+                        "candidates": candidates,
+                        "customer_context": customer_context or {},
+                    },
                     ensure_ascii=False,
                 )
             ),