feat:新增投顾agent和nl2sqlagent

agent/advisor_agent/intent/fund_analysis.py

@@ -0,0 +1,61 @@
+"""基金深度分析的数据整理层。"""
+from __future__ import annotations
+
+from decimal import Decimal
+from typing import Iterable
+
+
+def _number(value):
+    if isinstance(value, Decimal):
+        return float(value)
+    return value
+
+
+def _display_value(value):
+    if value is None:
+        return "暂无"
+    if isinstance(value, float):
+        return f"{value:g}"
+    return str(value)
+
+
+def _build_analysis_text(fund: dict, metrics: list[dict]) -> str:
+    fund_name = fund.get("fund_name") or fund.get("fund_code") or "该基金"
+    if not metrics:
+        return f"{fund_name}暂无足够业绩数据，暂无法形成完整解读。"
+
+    latest = metrics[-1]
+    period = _display_value(latest.get("period"))
+    return_rate = _display_value(latest.get("return_rate"))
+    max_drawdown = _display_value(latest.get("max_drawdown"))
+    sharpe = _display_value(latest.get("sharpe"))
+    return (
+        f"{fund_name}在{period}的历史收益率为{return_rate}%，"
+        f"最大回撤为{max_drawdown}%，夏普比率为{sharpe}。"
+        "以上仅基于历史业绩数据，不代表未来收益。"
+    )
+
+
+def build_fund_analysis(fund: dict, performance_rows: Iterable[dict]) -> dict:
+    metrics = []
+    for row in performance_rows:
+        metrics.append(
+            {
+                key: _number(value)
+                for key, value in row.items()
+            }
+        )
+    return {
+        "fund_code": fund.get("fund_code"),
+        "fund_name": fund.get("fund_name"),
+        "risk_level": fund.get("risk_level"),
+        "metrics": metrics,
+        "analysis_text": _build_analysis_text(fund, metrics),
+        "chart_data": {
+            "periods": [row.get("period") for row in metrics],
+            "return_rate": [row.get("return_rate") for row in metrics],
+            "annual_volatility": [row.get("annual_volatility") for row in metrics],
+            "max_drawdown": [row.get("max_drawdown") for row in metrics],
+            "sharpe": [row.get("sharpe") for row in metrics],
+        },
+    }