feat(盯盘): 推荐操作精选层——72h新鲜度+RR降序+现金预算贪心装入(上限5只)

老爸: 太多推荐=没有推荐。机制:
- 候选: tag非空 且 reassessed_at 72h内（陈旧信号不算推荐）
- 排序: rr_ratio 降序
- 预算: 从 portfolio_summary 读现金/总资产, 每只建议仓位
  (position_advice解析%或默认8%) 贪心累加, 耗尽即止, 最多5只
- 落选者降回持仓/自选自然组
- /api/watch 返回 cash/budget_pct/rec_used_pct, 前端显示预算条
- 推荐行仓位列显示'建议X%'

server.py

@@ -191,6 +191,57 @@ def get_watch():
 
         results.append(d)
 
+    # ── 推荐操作精选层（2026-07-21 老爸：太多推荐=没有推荐）──
+    # 候选 = tag 非空 且 72h 内有新鲜重评；按 RR 降序；贪心装入现金预算；最多 5 只。
+    # 落选者降回其自然分组（持仓/自选）。
+    import re as _re
+    from datetime import datetime as _dt, timedelta as _td
+    conn2 = sqlite3.connect("/home/hmo/MoFin/data/mofin.db")
+    try:
+        _pr = conn2.execute("SELECT cash, total_assets FROM portfolio_summary WHERE id=1").fetchone()
+        _cash = float(_pr[0] or 0)
+        _total = float(_pr[1] or 0)
+    finally:
+        conn2.close()
+    _budget_pct = (_cash / _total * 100) if _total > 0 else 0
+    _fresh_cutoff = _dt.now() - _td(hours=72)
+
+    def _is_fresh(d):
+        ra = d.get('reassessed_at') or ''
+        if not ra:
+            return False
+        try:
+            return _dt.fromisoformat(str(ra)[:19]) >= _fresh_cutoff
+        except Exception:
+            return False
+
+    def _sugg_pct(d):
+        # 从 position_advice 解析百分比（如 "8%（理由...)"），失败默认 8%
+        m = _re.search(r'(\d+(?:\.\d+)?)\s*%', d.get('position_advice') or '')
+        if m:
+            try:
+                v = float(m.group(1))
+                if 0 < v <= 30:
+                    return v
+            except Exception:
+                pass
+        return 8.0
+
+    _cands = [d for d in results if d['sort_group'] == 0 and _is_fresh(d)]
+    _cands.sort(key=lambda x: x.get('rr_ratio') or 0, reverse=True)
+    _selected, _cum = [], 0.0
+    for d in _cands:
+        pct = _sugg_pct(d)
+        if len(_selected) < 5 and _cum + pct <= _budget_pct + 1e-9:
+            d['suggested_position_pct'] = pct
+            _cum += pct
+            _selected.append(d)
+    _sel_codes = {d['code'] for d in _selected}
+    for d in results:
+        if d['sort_group'] == 0 and d['code'] not in _sel_codes:
+            # 落选：降回自然分组
+            d['sort_group'] = 1 if d['decision_type'] == '持仓策略' else 2
+
     # 排序：group → signal_rank → group-internal (持仓按position_pct desc, 自选按rr desc)
     def skey(x):
         g = x['sort_group']
@@ -207,7 +258,10 @@ def get_watch():
         d.pop('_pos', None)
         d.pop('_rr', None)
 
-    return json.dumps({"stocks": results, "count": len(results)}, ensure_ascii=False)
+    return json.dumps({"stocks": results, "count": len(results),
+                       "cash": _cash, "total_assets": _total,
+                       "budget_pct": round(_budget_pct, 2),
+                       "rec_used_pct": round(_cum, 2)}, ensure_ascii=False)
 
 
 @app.route("/api/strategy_history/<code>")