From 8c7b9a28d9673b077e14c7f71cd289bb95f71eac Mon Sep 17 00:00:00 2001
From: xxm <xxm@mofin.local>
Date: Thu, 20 Aug 2026 16:00:33 +0800
Subject: [PATCH] =?UTF-8?q?fix(prompt):=20=E4=BF=AE=E5=A4=8D=E6=95=B0?=
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- collect_data(): 从sector_snapshots读取行业涨跌/排名
- build_prompt(): 注入行业强度数据(行业涨跌%+排名)
- 移除current_regime_strategies死数据(旧策略名不匹配strategy_defs)
- 港股缺资金流(数据采集层限制,非代码问题)
---
 deploy/profile-scripts/batch_reassess.py | 18 +++++++++++++++++-
 1 file changed, 17 insertions(+), 1 deletion(-)

diff --git a/deploy/profile-scripts/batch_reassess.py b/deploy/profile-scripts/batch_reassess.py
index bbc0d0ef..ae8924c5 100644
--- a/deploy/profile-scripts/batch_reassess.py
+++ b/deploy/profile-scripts/batch_reassess.py
@@ -178,6 +178,22 @@ def collect_data(code):
             _db2.close()
         except Exception:
             pass
+        
+        # 行业强度（sector_snapshots: market_watch.py 写入的板块涨跌排名）
+        try:
+            _db3 = sqlite3.connect(DB, timeout=30)
+            _sector = data.get("sector_context", "")
+            if _sector:
+                _ss = _db3.execute(
+                    "SELECT change_pct, rank_in_market FROM sector_snapshots "
+                    "WHERE sector_name LIKE ? ORDER BY date DESC LIMIT 1",
+                    (f"%{_sector}%",)).fetchone()
+                if _ss:
+                    data["sector_change_pct"] = _ss[0] if _ss[0] is not None else None
+                    data["sector_rank"] = _ss[1] if _ss[1] is not None else None
+            _db3.close()
+        except Exception:
+            pass
 
         # 情势体检：温区 + 高风险消息 + 执行红线
         _sit = {"regime_a": "unknown", "regime_7d_ago": "unknown", "high_risk": "", "breach_stop": "否", "reach_tp": "否", "out_zone": "否", "over_hold": "否"}
@@ -632,7 +648,7 @@ accumulation(主力建仓) / b_td1_v3(超跌原池优选) / v_mr(弱市深超跌
 大盘：{data.get('macro','震荡')}{_macro_label}
 最新价：{data.get('price',0)}  涨跌：{data.get('change_pct','0')}%{_price_label}
 PE={data.get('pe','?')}（最新财报）  市值={data.get('mcap','?')}亿
-行业：{data.get('sector_context','?')}（近一个交易日）
+行业：{data.get('sector_context','?')}（近一个交易日）{_sector_extra}
 技术面：{data.get('tech_snapshot','')[:300]}（MA=5/10/20/60日 支撑阻力=近20日 量价=当日+近5日趋势）
 {_tech_str}
 {_tech_str}