feat:修复投顾agent功能

nl2sql/cache.py

@@ -49,6 +49,32 @@ def build_cache_key(
     return f"nl2sql:{digest}"
 
 
+def build_question_cache_key(
+    question: str,
+    *,
+    permission: dict[str, Any],
+    data_scope: dict[str, Any] | None = None,
+    page: int = 1,
+    page_size: int = 100,
+    sort_by: str | None = None,
+    sort_order: str = "asc",
+) -> str:
+    """生成自然语言查询结果缓存键，覆盖问题、权限和数据范围。"""
+    payload = {
+        "question": " ".join((question or "").split()),
+        "permission": _permission_payload(permission),
+        "data_scope": data_scope or {},
+        "page": page,
+        "page_size": page_size,
+        "sort_by": sort_by or "",
+        "sort_order": sort_order,
+    }
+    digest = hashlib.sha256(
+        json.dumps(payload, ensure_ascii=False, sort_keys=True, separators=(",", ":")).encode()
+    ).hexdigest()
+    return f"nl2sql:question:{digest}"
+
+
 async def cache_get(redis, key: str) -> dict[str, Any] | None:
     """读取缓存，Redis 异常或内容损坏时返回空结果。"""
     try:

nl2sql/query_rewriter.py

@@ -16,6 +16,11 @@ _SYSTEM_PROMPT = """你是基金平台 NL2SQL 的问题改写器。
 不能扩大权限范围，不能臆造查询结果；上下文不足时保留原问题。
 """
 
+_REFERENCE_TERMS = (
+    "他", "她", "它", "他们", "她们", "它们", "这个客户", "该客户", "那个客户",
+    "这个基金", "该基金", "那只基金", "这只基金", "这个结果", "上一轮", "刚才", "前面",
+)
+
 
 def _rewrite_explicit_customer_identity(question: str) -> str | None:
     normalized = re.sub(r"\s+", "", question)
@@ -68,7 +73,7 @@ async def rewrite_query(
     contextual_identity = _rewrite_customer_name_follow_up(original, context)
     if contextual_identity:
         return contextual_identity
-    if not context or llm_client is None:
+    if not context or llm_client is None or not any(term in original for term in _REFERENCE_TERMS):
         return original
 
     prompt = (

nl2sql/result.py

@@ -67,6 +67,7 @@ async def render_answer(
                 {"role": "user", "content": prompt},
             ],
             temperature=0,
+            max_tokens=256,
         )
     except Exception:  # noqa: BLE001 摘要失败回退固定文本
         return fallback

nl2sql/retrieval.py

@@ -1,6 +1,7 @@
 """NL2SQL 元数据召回与授权过滤。"""
 from __future__ import annotations
 
+import asyncio
 from collections.abc import Awaitable, Callable, Iterable
 from typing import Any
 
@@ -70,15 +71,21 @@ async def retrieve_metadata(
         "is_valid",
         "is_deprecated",
     ]
-    results: list[dict[str, Any]] = []
-    for chunk_type in ("table_meta", "field_meta"):
-        hits = await milvus_client.search(
+    async def search_chunk(chunk_type: str):
+        return await milvus_client.search(
             collection_name=NL2SQL_COLLECTION,
             data=[vector],
             limit=top_k,
             filter=f'chunk_type == "{chunk_type}" and is_valid == true',
             output_fields=output_fields,
         )
+
+    table_hits, field_hits = await asyncio.gather(
+        search_chunk("table_meta"),
+        search_chunk("field_meta"),
+    )
+    results: list[dict[str, Any]] = []
+    for hits in (table_hits, field_hits):
         for hit in _flatten_hits(hits):
             entity = hit.get("entity") or hit
             if not entity.get("is_valid", True) or entity.get("is_deprecated", False):

nl2sql/schema.py

@@ -1,12 +1,23 @@
 """从 MySQL information_schema 加载并校验 NL2SQL 权威 Schema。"""
 from __future__ import annotations
 
+import hashlib
+import json
+import logging
 from typing import Any
 
 from sqlalchemy import bindparam, text
 
 from nl2sql.metadata import normalize_column_row, normalize_table_row
 
+logger = logging.getLogger("nl2sql.schema")
+SCHEMA_CACHE_TTL = 60
+
+
+def _schema_cache_key(database: str, candidates: list[str]) -> str:
+    payload = json.dumps([database, candidates], ensure_ascii=False, separators=(",", ":"))
+    return "nl2sql:schema:" + hashlib.sha256(payload.encode()).hexdigest()
+
 
 TABLES_SQL = text(
     """
@@ -34,13 +45,25 @@ async def load_authoritative_schema(
     *,
     database: str,
     candidate_tables: set[str] | list[str],
+    redis=None,
+    cache_ttl: int = SCHEMA_CACHE_TTL,
 ) -> dict[str, list[dict[str, Any]]]:
     """从权威元数据源加载候选表，并剔除不存在的表和孤立字段。"""
     candidates = {str(name).strip() for name in candidate_tables if str(name).strip()}
     if not candidates:
         return {"tables": [], "columns": []}
 
-    params = {"database": database, "candidate_tables": sorted(candidates)}
+    candidate_list = sorted(candidates)
+    cache_key = _schema_cache_key(database, candidate_list)
+    if redis is not None:
+        try:
+            cached = await redis.get(cache_key)
+            if cached:
+                return json.loads(cached)
+        except Exception:  # noqa: BLE001 缓存异常回退权威查询
+            logger.warning("Schema 缓存读取失败", exc_info=True)
+
+    params = {"database": database, "candidate_tables": candidate_list}
     table_result = await session.execute(TABLES_SQL, params)
     column_result = await session.execute(COLUMNS_SQL, params)
 
@@ -56,4 +79,10 @@ async def load_authoritative_schema(
         normalized = normalize_column_row(dict(row))
         if normalized["table_name"] in valid_table_names and normalized["field_name"]:
             columns.append(normalized)
-    return {"tables": tables, "columns": columns}
+    schema = {"tables": tables, "columns": columns}
+    if redis is not None:
+        try:
+            await redis.set(cache_key, json.dumps(schema, ensure_ascii=False), ex=cache_ttl)
+        except Exception:  # noqa: BLE001 缓存异常不阻断查询
+            logger.warning("Schema 缓存写入失败", exc_info=True)
+    return schema

nl2sql/sql_agent.py

@@ -74,7 +74,7 @@ async def generate_sql(
         },
     ]
     try:
-        output = await llm_client.chat(messages, temperature=0)
+        output = await llm_client.chat(messages, temperature=0, max_tokens=256)
     except Exception as exc:  # noqa: BLE001 统一收敛模型异常
         raise SqlGenerationError("SQL 模型调用失败") from exc
     sql = _clean_model_output(output)