feat(prompt): 技术指标注入LLM prompt——collect_data增加ta/mtf/factor,build_prompt增加_tech_str

- collect_data(): 从ta.full_analysis获取支撑阻力/MA/形态,从mtf获取多周期趋势/RSI,从stock_indicators获取mcap_q/pe_q/bias60
- build_prompt(): 在技术面段注入_tech_str(MA/dist_ma20/RSI/多周期趋势/基本面分位)
- LLM现在能看到11个策略所需的全部输入数据

deploy/profile-scripts/batch_reassess.py

@@ -122,6 +122,63 @@ def collect_data(code):
                 data["strategy_def"] = None
         except Exception:
             data["strategy_def"] = None
+        # ── 技术指标收集（策略输入数据）──
+        try:
+            import technical_analysis as _ta
+            _tech = _ta.full_analysis(code)
+            if _tech:
+                _sr = _tech.get("support_resistance", {})
+                data["ta_strong_support"] = _sr.get("strong_support", 0)
+                data["ta_weak_support"] = _sr.get("weak_support", 0)
+                data["ta_pivot"] = _sr.get("pivot", 0)
+                data["ta_weak_resist"] = _sr.get("weak_resist", 0)
+                data["ta_strong_resist"] = _sr.get("strong_resist", 0)
+                _cs = _tech.get("candlestick", {})
+                data["ta_candle"] = _cs.get("pattern", "") + "/" + _cs.get("sentiment", "")
+                _vol = _tech.get("volume", {})
+                data["ta_volume"] = _vol.get("description", "")
+                import re as _re
+                _snap = data.get("tech_snapshot", "")
+                _ma = _re.search(r'MA5=([\d.]+).*?MA10=([\d.]+).*?MA20=([\d.]+).*?MA60=([\d.]+)', _snap)
+                if _ma:
+                    data["ta_ma5"] = float(_ma.group(1))
+                    data["ta_ma10"] = float(_ma.group(2))
+                    data["ta_ma20"] = float(_ma.group(3))
+                    data["ta_ma60"] = float(_ma.group(4))
+                    if data["ta_ma20"] > 0:
+                        data["ta_dist_ma20"] = round((data["price"] - data["ta_ma20"]) / data["ta_ma20"] * 100, 2)
+        except Exception:
+            pass
+        try:
+            import multi_timeframe as _mtf
+            _mtf_r = _mtf.full_multi_tf_analysis(code)
+            if _mtf_r:
+                _adj = _mtf_r.get("strategy_adjustment", {})
+                data["mtf_trend_alignment"] = _adj.get("trend_alignment", "未知")
+                data["mtf_daily_trend"] = _mtf_r.get("daily", {}).get("trend", {}).get("description", "")
+                data["mtf_weekly_trend"] = _mtf_r.get("weekly", {}).get("trend", {}).get("description", "")
+                data["mtf_monthly_trend"] = _mtf_r.get("monthly", {}).get("trend", {}).get("description", "")
+                _rsi = _mtf_r.get("daily", {}).get("rsi")
+                if _rsi is not None:
+                    data["ta_rsi"] = round(_rsi, 1)
+        except Exception:
+            pass
+        try:
+            _db2 = sqlite3.connect(DB, timeout=30)
+            _fi = _db2.execute("SELECT mcap_q, pe_q, bias60, bias20, rsi, r5f, dist_lo20 FROM stock_indicators WHERE code=? ORDER BY date DESC LIMIT 1", (code,)).fetchone()
+            if _fi:
+                data["factor_mcap_q"] = _fi[0] if _fi[0] is not None else None
+                data["factor_pe_q"] = _fi[1] if _fi[1] is not None else None
+                data["factor_bias60"] = _fi[2] if _fi[2] is not None else None
+                data["factor_bias20"] = _fi[3] if _fi[3] is not None else None
+                if data.get("ta_rsi") is None and _fi[4] is not None:
+                    data["ta_rsi"] = round(_fi[4], 1)
+                data["factor_ret5d"] = _fi[5] if _fi[5] is not None else None
+                data["factor_dist_lo20"] = _fi[6] if _fi[6] is not None else None
+            _db2.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"}
         try:
@@ -390,6 +447,34 @@ def build_prompt(data):
                              f"（是否建仓/什么价位建仓/仓位多大），禁止假设我有浮盈、"
                              f"禁止出现「已持仓者」视角的建议。")
 
+    _tech_parts = []
+    if data.get("ta_strong_support"):
+        _tech_parts.append(f"强支撑={data['ta_strong_support']} 弱支撑={data['ta_weak_support']} 枢轴={data['ta_pivot']} 弱压={data['ta_weak_resist']} 强压={data['ta_strong_resist']}")
+    if data.get("ta_ma20"):
+        _ma_info = f"MA5={data.get('ta_ma5','?')} MA10={data.get('ta_ma10','?')} MA20={data.get('ta_ma20','?')} MA60={data.get('ta_ma60','?')}"
+        if data.get("ta_dist_ma20") is not None:
+            _ma_info += f" 距MA20={data['ta_dist_ma20']}%"
+        _tech_parts.append(_ma_info)
+    if data.get("ta_rsi"):
+        _tech_parts.append(f"RSI={data['ta_rsi']}")
+    if data.get("ta_candle"):
+        _tech_parts.append(f"K线形态={data['ta_candle']}")
+    if data.get("mtf_trend_alignment"):
+        _tech_parts.append(f"多周期趋势={data['mtf_trend_alignment']}")
+    if data.get("mtf_daily_trend"):
+        _tech_parts.append(f"日线={data['mtf_daily_trend']}")
+    if data.get("mtf_weekly_trend"):
+        _tech_parts.append(f"周线={data['mtf_weekly_trend']}")
+    if data.get("mtf_monthly_trend"):
+        _tech_parts.append(f"月线={data['mtf_monthly_trend']}")
+    _factor_parts = []
+    for _fk, _fl in [("factor_mcap_q", "市值分位"), ("factor_pe_q", "PE分位"), ("factor_bias60", "bias60"), ("factor_bias20", "bias20"), ("factor_ret5d", "5日涨幅"), ("factor_dist_lo20", "距20日低点")]:
+        if data.get(_fk) is not None:
+            _factor_parts.append(f"{_fl}={data[_fk]}")
+    if _factor_parts:
+        _tech_parts.append("基本面分位: " + " ".join(_factor_parts))
+    _tech_str = " | ".join(_tech_parts) if _tech_parts else "技术指标数据待刷新"
+
     # ── 换仓上下文（2026-07-24 老爸：现金不足时给出具体换股建议）──
     _rotation_context = ""
     if not data.get('held'):
@@ -550,6 +635,7 @@ 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）
 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}
 资金流：{_flow_note}（近5日累计）
 消息面：{_news_note}（最近3条，自动标注抓取时间）
 当前信号：{data.get('timing_signal','?')}  分类：{data.get('stock_category','?')}