feat:新增投顾agent和nl2sqlagent

nl2sql/result.py

@@ -0,0 +1,52 @@
+"""NL2SQL 结果摘要和基础图表配置。"""
+from __future__ import annotations
+
+import json
+from typing import Any
+
+
+def build_chart_config(columns: list[str], rows: list[dict[str, Any]]) -> dict[str, Any] | None:
+    """识别简单的分类数值结果，返回安全的柱状图配置。"""
+    if not rows or len(columns) < 2:
+        return None
+    numeric_column = next(
+        (
+            column
+            for column in columns
+            if all(isinstance(row.get(column), (int, float)) and not isinstance(row.get(column), bool) for row in rows)
+        ),
+        None,
+    )
+    category_column = next((column for column in columns if column != numeric_column), None)
+    if numeric_column is None or category_column is None:
+        return None
+    return {"type": "bar", "category": category_column, "value": numeric_column}
+
+
+async def summarize_result(
+    question: str,
+    columns: list[str],
+    rows: list[dict[str, Any]],
+    *,
+    llm_client,
+    max_prompt_rows: int = 20,
+) -> str:
+    """使用脱敏后的受控结果生成摘要，模型失败时返回固定话术。"""
+    fallback = f"查询完成，共返回 {len(rows)} 条记录。"
+    prompt = (
+        "请用简洁中文总结查询结果，只基于提供的数据，不要猜测。\n"
+        f"问题：{question}\n"
+        f"列名：{json.dumps(columns, ensure_ascii=False)}\n"
+        f"结果：{json.dumps(rows[:max_prompt_rows], ensure_ascii=False, default=str)}"
+    )
+    try:
+        answer = await llm_client.chat(
+            [
+                {"role": "system", "content": "你是数据查询结果摘要助手。"},
+                {"role": "user", "content": prompt},
+            ],
+            temperature=0,
+        )
+    except Exception:  # noqa: BLE001 摘要失败回退固定文本
+        return fallback
+    return answer.strip() or fallback