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"""投顾 Agent 的 NL2SQL 数据查询适配层。"""
from __future__ import annotations
from dataclasses import asdict
from typing import Any
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from uuid import uuid4
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from agent.advisor_agent.auth import ensure_customer_access
from agent.data_query.agent import DataQueryAgent
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from common.common_const import CUSTOMER_REL_STATUS_SIGNED, CUSTOMER_REL_STATUS_UNSIGNED
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from config import database
from config.settings import settings
from nl2sql.contracts import DataQueryRequest, DataQueryResult
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from nl2sql.embedding import EmbeddingError
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from nl2sql.retrieval import retrieve_metadata
from nl2sql.runtime_config import runtime_config
from nl2sql.schema import load_authoritative_schema
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from repositories.customer_relation import CustomerRelationRepo
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from service.nl2sql.permission_service import load_query_permission
from service.nl2sql.query_service import QueryServiceError
from tool.llm import llm as default_llm
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from utils.exceptions import LLMFailError
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from repositories.fin_holdings import FinHoldingsRepo
from repositories.fin_product import FinProductRepo
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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))}
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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"))
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async def _query_current_holdings(
db, *, customer_id: int, trace_id: str, customer_name: str | None = None
) -> dict[str, Any]:
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holdings = await FinHoldingsRepo(db).list_by_customer(customer_id, status="持有中")
product_repo = FinProductRepo(db)
rows: list[dict[str, Any]] = []
total_value = 0
for holding in holdings:
product = await product_repo.get(holding.product_id)
rows.append(
{
"产品代码": product.product_code if product else None,
"产品名称": product.product_name if product else None,
"风险等级": product.risk_level if product else None,
"持有份额": f"{holding.shares:.4f}",
"成本金额": f"{holding.cost_amount:.2f}",
"当前市值": f"{holding.current_value:.2f}",
"盈亏": f"{holding.profit_loss:.2f}",
"收益率": f"{holding.profit_ratio:.4f}",
"状态": holding.status,
}
)
total_value += holding.current_value
names = [row["产品名称"] for row in rows if row["产品名称"]]
return {
"query_id": f"holdings-{uuid4().hex}",
"trace_id": trace_id,
"columns": list(rows[0].keys()) if rows else ["产品代码", "产品名称", "风险等级", "持有份额", "成本金额", "当前市值", "盈亏", "收益率", "状态"],
"rows": rows,
"row_count": len(rows),
"truncated": False,
"summary": f"当前持仓共 {len(rows)} 条记录。",
"answer": (
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(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。"
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+ (f"包括:{'、'.join(names[:6])}。" if names else "")
),
"sql": None,
}
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async def execute_advisor_data_query(
db,
*,
advisor_id: int,
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customer_id: int | None,
scope: str = "customer",
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question: str,
trace_id: str,
session_id: str | None = None,
conversation_context: str = "",
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data_scope: dict[str, Any] | None = None,
max_rows: int | None = None,
page: int = 1,
page_size: int = 100,
sort_by: str | None = None,
sort_order: str = "asc",
milvus=None,
redis=None,
llm_client=None,
query_agent=None,
) -> dict[str, Any]:
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"""在当前投顾或选中客户范围内执行只读自然语言查询。
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``data_scope`` 即使由调用方传入也不会被信任,服务端始终覆盖为当前
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客户关系范围,避免投顾借助 NL2SQL 查询其他客户数据。
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"""
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if scope == "advisor":
relations = await CustomerRelationRepo(db).list_by_advisor(advisor_id)
customer_ids = [
relation.customer_id
for relation in relations
if relation.status in {CUSTOMER_REL_STATUS_UNSIGNED, CUSTOMER_REL_STATUS_SIGNED}
]
if not customer_ids:
raise QueryServiceError("当前投顾名下没有可查询客户")
else:
if customer_id is None:
raise QueryServiceError("单客户查询需要明确客户范围")
await ensure_customer_access(db, advisor_id=advisor_id, customer_id=customer_id)
customer_ids = [customer_id]
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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
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if scope == "customer" and _is_current_holdings_query(question):
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return await _query_current_holdings(
db,
customer_id=customer_id,
trace_id=trace_id,
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customer_name=name_by_id.get(customer_id),
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)
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permission = await load_query_permission(db, advisor_id)
if not permission.get("can_query", False):
raise QueryServiceError("当前投顾没有 NL2SQL 查询权限")
milvus = milvus or database.milvus.client()
redis = redis or database.redis.client()
llm_client = llm_client or default_llm
request = DataQueryRequest(
question=question,
user_id=advisor_id,
trace_id=trace_id,
session_id=session_id,
caller_agent="advisor_agent",
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data_scope={"customer_ids": customer_ids},
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max_rows=min(max_rows or runtime_config.max_rows, runtime_config.max_rows),
include_sql=False,
page=page,
page_size=page_size,
sort_by=sort_by,
sort_order=sort_order,
)
async def permission_loader(_user_id: int):
return permission
async def metadata_retriever(query: str):
return await retrieve_metadata(
query,
milvus,
top_k=runtime_config.retrieval_top_k,
)
async def schema_loader(table_names: set[str], _permission: dict):
return await load_authoritative_schema(
db,
database=settings.mysql.database,
candidate_tables=table_names,
)
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try:
result: DataQueryResult = await (query_agent or DataQueryAgent()).query(
request,
session=db,
permission_loader=permission_loader,
metadata_retriever=metadata_retriever,
schema_loader=schema_loader,
llm_client=llm_client,
summary_llm=llm_client,
masks=permission.get("masks"),
conversation_context=conversation_context,
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)
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
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payload = asdict(result)
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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']}。"
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payload["sql"] = None
payload["customer_id"] = customer_id
return payload