fix: 九维分析全面升级-资金流+消息面入prompt+交叉综合+capital_flow_collector修mo_data引用

scripts/batch_reassess.py

@@ -84,14 +84,57 @@ def build_prompt(data):
     cash = 321271  # 可用现金（从DB读取）
     total = 952879  # 总资产
     
+    # 拉取资金流数据
+    _flow_note = "暂无资金流数据"
+    try:
+        import sqlite3 as _sq, json as _j
+        _db = _sq.connect("/home/hmo/MoFin/data/mofin.db")
+        _fr = _db.execute("SELECT cache_json FROM capital_flow_cache ORDER BY id DESC LIMIT 1").fetchone()
+        if _fr and _fr[0]:
+            _fc = _j.loads(_fr[0])
+            _stocks = _fc.get("stocks", {})
+            _s = _stocks.get(data['code'], {})
+            if _s and _s.get("analysis"):
+                _a = _s["analysis"]
+                _net = _a.get("net_flow", 0)
+                _main = _a.get("main_force", 0)
+                _retail = _a.get("retail_flow", 0)
+                _trend = _a.get("trend", "中性")
+                _flow_note = f"净流入{_net:.0f}万 主力{_main:.0f}万 散户{_retail:.0f}万 趋势{_trend}"
+        _db.close()
+    except:
+        pass
+    
+    # 拉取近期消息面
+    _news_note = "暂无近期消息"
+    try:
+        import sqlite3 as _sq
+        _db = _sq.connect("/home/hmo/MoFin/data/mofin.db")
+        _nr = _db.execute(
+            "SELECT summary, overall_sentiment, created_at FROM signal_news "
+            "WHERE (code=? OR sector LIKE ?) AND overall_sentiment IN ('利好','利空') "
+            "ORDER BY id DESC LIMIT 3",
+            (data['code'], f'%{data.get("name","")[:4]}%')
+        ).fetchall()
+        if _nr:
+            _news_note = " | ".join([f"{r[2][:10]} {r[1]} {r[0][:40]}" for r in _nr])
+        _db.close()
+    except:
+        pass
+    
     return f"""你是一个资深A股分析师。请对{data['code']} {data.get('name','')}做一个完整的九维矩阵分析，并输出策略参数。
 
-当前数据：
+⚠️ 重要：以下9个维度不是独立分析的，你必须交叉对比后给出综合结论。
+例如：如果消息面利好但资金流在流出，说明利好可能是出货；如果基本面强但技术面破位，说明估值可能还没到底。
+
+当前数据（以下数据均来自实时API，禁止使用模型训练数据）：
 大盘：{data.get('macro','震荡')}
 最新价：{data.get('price',0)}  涨跌：{data.get('change_pct','0')}%
 PE={data.get('pe','?')}  市值={data.get('mcap','?')}亿
 行业：{data.get('sector_context','?')}
-技术面：{data.get('tech_snapshot','')[:200]}
+技术面：{data.get('tech_snapshot','')[:300]}
+资金流：{_flow_note}
+消息面：{_news_note}
 当前信号：{data.get('timing_signal','?')}  分类：{data.get('stock_category','?')}
 原策略：{(data.get('action','') or '')[:200]}
 
@@ -99,7 +142,8 @@ PE={data.get('pe','?')}  市值={data.get('mcap','?')}亿
 
 请严格按以下格式输出：
 
-① 大盘×基本面 [一句话]
+【交叉分析】用2-3句话说明哪些维度出现矛盾/共振，最关键的信号是什么
+① 大盘×基本面 [一句话，说明矛盾关系]
 ② 大盘×消息面 [一句话]
 ③ 大盘×技术面 [一句话]
 ④ 大盘×资金流 [一句话]

scripts/capital_flow_collector.py

@@ -11,8 +11,7 @@ from datetime import datetime
 from urllib.request import urlopen, Request
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from threading import Semaphore
-from mo_data import read_portfolio, read_decisions, read_watchlist
-from mofin_db import get_conn, write_capital_flow_cache
+from mofin_db import get_conn, write_capital_flow_cache, query_holdings, query_holdings_db, query_watchlist
 
 DATA_DIR = "/home/hmo/web-dashboard/data"
 CACHE_PATH = f"{DATA_DIR}/capital_flow_cache.json"
@@ -134,13 +133,15 @@ def analyze_flow(flow_data):
 
 def main():
     codes = set()
-    # 读取持仓+自选
+    # 读取持仓+自选（从DB直接读，替代已删除的mo_data）
     try:
-        dec = mo_data.read_decisions()
-        for d in dec.get("decisions", []):
-            c = d.get("code", "")
-            if c:
-                codes.add(c)
+        import sqlite3
+        _db = sqlite3.connect("/home/hmo/MoFin/data/mofin.db")
+        for row in _db.execute("SELECT DISTINCT code FROM holdings WHERE is_active=1").fetchall():
+            if row[0]: codes.add(row[0])
+        for row in _db.execute("SELECT DISTINCT code FROM holding_strategies WHERE status='active' AND decision_type='自选策略'").fetchall():
+            if row[0]: codes.add(row[0])
+        _db.close()
     except:
         pass
 

scripts/per_stock_reassess.py

@@ -394,12 +394,53 @@ def main():
                     except:
                         pass
                     
+                    # 拉取资金流数据
+                    _flow_note = "暂无资金流数据"
+                    try:
+                        _fdb = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db")
+                        _fr = _fdb.execute("SELECT cache_json FROM capital_flow_cache ORDER BY id DESC LIMIT 1").fetchone()
+                        if _fr and _fr[0]:
+                            _fc = __import__('json').loads(_fr[0])
+                            _s = _fc.get("stocks", {}).get(code, {})
+                            if _s and _s.get("analysis"):
+                                _a = _s["analysis"]
+                                _flow_note = f"净流入{_a.get('net_flow',0):.0f}万 主力{_a.get('main_force',0):.0f}万 趋势{_a.get('trend','中性')}"
+                        _fdb.close()
+                    except:
+                        pass
+                    
+                    # 拉取近期消息面
+                    _news_note = "暂无近期消息"
+                    try:
+                        _ndb = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db")
+                        _nr2 = _ndb.execute(
+                            "SELECT summary, overall_sentiment, created_at FROM signal_news "
+                            "WHERE (code=? OR sector LIKE ?) AND overall_sentiment IN ('利好','利空') "
+                            "ORDER BY id DESC LIMIT 3",
+                            (code, f'%{entry.get("name","")[:4]}%')
+                        ).fetchall()
+                        if _nr2:
+                            _news_note = " | ".join([f"{r[2][:10]} {r[1]} {r[0][:40]}" for r in _nr2])
+                        _ndb.close()
+                    except:
+                        pass
+                    
                     _prompt = f"""你是一个资深股票分析师。请对股票{code}做一个完整的9维矩阵分析。
-当前数据：大盘={_macro_desc or "震荡"} | PE/市值={_pe_val} {_pb_val} | 价格={price} 区间={entry.get("entry_low",0)}~{entry.get("entry_high",0)} 止损={entry.get("stop_loss",0)} 止盈={entry.get("take_profit",0)} RR={result.get("rr_ratio",entry.get("rr_ratio",0))} | 信号={result.get("timing_signal") or entry.get("timing_signal","")} | 行业={(result.get("sector_context") or entry.get("sector_context",""))[:50]}
+
+⚠️ 重要：9个维度必须交叉对比，找出矛盾/共振点，给出综合判断。
+
+当前数据（实时API，禁止使用模型训练数据）：
+大盘={_macro_desc or "震荡"} | PE/市值={_pe_val} {_pb_val} | 价格={price} 区间={entry.get("entry_low",0)}~{entry.get("entry_high",0)} 止损={entry.get("stop_loss",0)} 止盈={entry.get("take_profit",0)} RR={result.get("rr_ratio",entry.get("rr_ratio",0))} | 信号={result.get("timing_signal") or entry.get("timing_signal","")} | 行业={(result.get("sector_context") or entry.get("sector_context",""))[:50]}
 策略={(result.get("action") or entry.get("action",""))[:200]}
 技术={(result.get("tech_snapshot") or entry.get("tech_snapshot",""))[:200]}
+资金流={_flow_note}
+消息面={_news_note}
 
-格式：①大盘×基本面 ②大盘×消息面 ③大盘×技术面 ④大盘×资金流 ⑤行业×基本面 ⑥行业×消息面 ⑦行业×技术面 ⑧个股×基本面 ⑨个股×消息面
+格式：
+【交叉分析】哪些维度矛盾/共振，关键信号
+① 大盘×基本面 ② 大盘×消息面 ③ 大盘×技术面 ④ 大盘×资金流
+⑤ 行业×基本面 ⑥ 行业×消息面 ⑦ 行业×技术面
+⑧ 个股×基本面 ⑨ 个股×消息面
 
 最后必须输出：
 【综合结论】(买入/关注/观望/卖出)