fix: 连续上榜改为严格N日每天上榜，缺一日都不行

backend/routes/core_stocks.py

@@ -90,73 +90,52 @@ async def active_core_stocks(days: int = Query(10, ge=1, le=30, description="交
         conn.close()
 
 
-@router.get("/consecutive", summary="连续上榜的核心股")
-async def consecutive_core_stocks(min_days: int = Query(3, ge=2, le=10, description="最小连续天数")):
-    from datetime import date as date_cls
+@router.get("/consecutive", summary="最近N日每天上榜的核心股")
+async def consecutive_core_stocks(days: int = Query(3, ge=2, le=10, description="交易日天数")):
     conn = get_connection()
     try:
-        # 最近30个有数据的交易日
         rows = conn.execute(
-            "SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT 30"
+            "SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT ?",
+            (days,)
         ).fetchall()
-        all_dates = [r["trade_date"] for r in reversed(rows)]
+        recent_dates = [r["trade_date"] for r in reversed(rows)]
 
-        if not all_dates:
-            return JSONResponse({"stocks": []}, headers=_NO_CACHE_HEADERS)
+        if len(recent_dates) < days:
+            return JSONResponse({"days": days, "stocks": []}, headers=_NO_CACHE_HEADERS)
 
-        # 查询所有上榜记录
-        placeholders = ",".join("?" * len(all_dates))
+        placeholders = ",".join("?" * len(recent_dates))
         rows = conn.execute(
             f"""SELECT trade_date, stock_code, stock_name, f3, cover_count
                 FROM daily_core_stocks
-                WHERE trade_date IN ({placeholders})
-                ORDER BY stock_code, trade_date""",
-            all_dates,
+                WHERE trade_date IN ({placeholders})""",
+            recent_dates,
         ).fetchall()
 
-        # 按股票分组，记录上榜日期
         stock_dates: dict[str, dict] = {}
         for r in rows:
             code = r["stock_code"]
             s = stock_dates.setdefault(code, {
                 "stockCode": code,
                 "stockName": r["stock_name"],
-                "dates": [],
+                "dates": set(),
                 "dailyGains": {},
             })
-            s["dates"].append(r["trade_date"])
+            s["dates"].add(r["trade_date"])
             s["dailyGains"][r["trade_date"]] = r["f3"]
 
-        # 计算连续上榜天数（从最新交易日往回数）
         results = []
         for code, s in stock_dates.items():
-            dates_list = sorted(s["dates"])
-            consecutive = 0
-            last_n = []
-            for i in range(len(dates_list) - 1, -1, -1):
-                if i == len(dates_list) - 1:
-                    consecutive = 1
-                    last_n.append(dates_list[i])
-                else:
-                    prev_idx = all_dates.index(dates_list[i + 1]) if dates_list[i + 1] in all_dates else -1
-                    curr_idx = all_dates.index(dates_list[i]) if dates_list[i] in all_dates else -1
-                    if prev_idx - curr_idx <= 2:
-                        consecutive += 1
-                        last_n.append(dates_list[i])
-                    else:
-                        break
-
-            if consecutive >= min_days:
+            if len(s["dates"]) >= days:
                 results.append({
                     "stockCode": code,
                     "stockName": s["stockName"],
-                    "consecutiveDays": consecutive,
-                    "recentDates": last_n,
-                    "dailyGains": {d: s["dailyGains"].get(d) for d in last_n},
+                    "consecutiveDays": len(s["dates"]),
+                    "recentDates": sorted(s["dates"]),
+                    "dailyGains": s["dailyGains"],
                 })
 
         results.sort(key=lambda x: -x["consecutiveDays"])
-        return JSONResponse({"stocks": results}, headers=_NO_CACHE_HEADERS)
+        return JSONResponse({"days": days, "recentDates": recent_dates, "stocks": results}, headers=_NO_CACHE_HEADERS)
     finally:
         conn.close()
 

backend/services/ai_service.py

@@ -33,7 +33,7 @@ SYSTEM_PROMPT = """你是一位专业的A股市场分析师，擅长从数据中
 - get_market_dashboard: 获取市场整体数据（指数/涨跌统计/市场温度/连板梯队/行业强度/板块资金流/两融/海外指数与国内期货/事件情报）
 - get_theme_history: 获取指定日期的题材涨幅排行
 - get_active_core_stocks: 获取核心股追踪数据（10日涨幅矩阵+所属题材）
-- get_consecutive_core_stocks: 获取连续上榜的核心股列表（近3日及以上连续上榜），用于识别持续活跃的热点股
+- get_consecutive_core_stocks: 获取最近N个交易日每天都上榜的核心股（缺一日都不行），用于识别持续活跃的热点股
 - get_stock_quote: 获取个股实时行情
 - get_fund_flow: 获取个股资金流向
 - get_news: 获取财经快讯（新浪7x24，用于重要消息面）
@@ -81,7 +81,7 @@ DAILY_ANALYSIS_PROMPT = """请对 {trade_date}（A股交易日） 的A股市场
 1. get_market_dashboard() —— 指数、涨跌统计、市场温度、连板梯队 limitLadder、板块资金流 sectorFundFlow、两融、海外指数与国内期货 globalMarkets
 2. get_theme_history(date="{trade_date}") —— 今日题材涨幅榜
 3. get_active_core_stocks() —— 核心股 10 日涨幅矩阵与所属题材
-4. get_consecutive_core_stocks(min_days=3) —— 连续3日及以上上榜的核心股
+4. get_consecutive_core_stocks(days=3) —— 最近3个交易日每天都上榜的核心股（缺一日都不行）
 5. get_news(limit=30) —— 今日财经快讯
 只有在需要核实某只具体个股时，才额外调用 get_stock_quote / get_fund_flow，合计不超过 2 次。
 

backend/services/ai_tools.py

@@ -46,11 +46,11 @@ TOOLS = [
         "type": "function",
         "function": {
             "name": "get_consecutive_core_stocks",
-            "description": "获取连续上榜的核心股列表（近3日及以上连续上榜），用于识别持续活跃的热点股",
+            "description": "获取最近N个交易日每天都上榜的核心股（缺一日都不行），用于识别持续活跃的热点股",
             "parameters": {
                 "type": "object",
                 "properties": {
-                    "min_days": {"type": "integer", "description": "最小连续天数，默认3"}
+                    "days": {"type": "integer", "description": "交易日天数，默认3"}
                 },
                 "required": []
             }
@@ -113,7 +113,7 @@ async def execute_tool(tool_name: str, arguments: dict) -> str:
         elif tool_name == "get_active_core_stocks":
             return await _get_active_core_stocks()
         elif tool_name == "get_consecutive_core_stocks":
-            return await _get_consecutive_core_stocks(arguments.get("min_days", 3))
+            return await _get_consecutive_core_stocks(arguments.get("days", 3))
         elif tool_name == "get_stock_quote":
             return await _get_stock_quote(arguments.get("code", ""))
         elif tool_name == "get_fund_flow":
@@ -235,28 +235,28 @@ async def _get_active_core_stocks() -> str:
         conn.close()
 
 
-async def _get_consecutive_core_stocks(min_days: int = 3) -> str:
-    """获取连续上榜的核心股列表"""
+async def _get_consecutive_core_stocks(days: int = 3) -> str:
+    """获取最近N个交易日**每个交易日都上榜**的核心股，缺一日都不行"""
     from database import get_connection
     conn = get_connection()
     try:
-        # 最近30个有数据的交易日
+        # 最近N个有数据的交易日
         rows = conn.execute(
-            "SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT 30"
+            "SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT ?",
+            (days,)
         ).fetchall()
-        all_dates = [r["trade_date"] for r in reversed(rows)]
+        recent_dates = [r["trade_date"] for r in reversed(rows)]
 
-        if not all_dates:
-            return json.dumps({"dates": [], "stocks": []}, ensure_ascii=False)
+        if len(recent_dates) < days:
+            return json.dumps({"days": days, "stocks": []}, ensure_ascii=False)
 
-        # 查询所有上榜记录
-        placeholders = ",".join("?" * len(all_dates))
+        # 查询这些日期的上榜记录
+        placeholders = ",".join("?" * len(recent_dates))
         rows = conn.execute(
             f"""SELECT trade_date, stock_code, stock_name, f3, cover_count
                 FROM daily_core_stocks
-                WHERE trade_date IN ({placeholders})
-                ORDER BY stock_code, trade_date""",
-            all_dates,
+                WHERE trade_date IN ({placeholders})""",
+            recent_dates,
         ).fetchall()
 
         # 按股票分组，记录上榜日期
@@ -266,48 +266,30 @@ async def _get_consecutive_core_stocks(min_days: int = 3) -> str:
             s = stock_dates.setdefault(code, {
                 "stockCode": code,
                 "stockName": r["stock_name"],
-                "dates": [],
+                "dates": set(),
                 "dailyGains": {},
             })
-            s["dates"].append(r["trade_date"])
+            s["dates"].add(r["trade_date"])
             s["dailyGains"][r["trade_date"]] = r["f3"]
 
-        # 计算连续上榜天数（从最新交易日往回数）
+        # 只保留N个交易日全部上榜的股票
         results = []
         for code, s in stock_dates.items():
-            dates_list = sorted(s["dates"])
-            # 从最新的日期往回数连续天数
-            consecutive = 0
-            last_n = []
-            for i in range(len(dates_list) - 1, -1, -1):
-                if i == len(dates_list) - 1:
-                    consecutive = 1
-                    last_n.append(dates_list[i])
-                else:
-                    # 检查是否连续（允许间隔1天非交易日）
-                    prev_idx = all_dates.index(dates_list[i + 1]) if dates_list[i + 1] in all_dates else -1
-                    curr_idx = all_dates.index(dates_list[i]) if dates_list[i] in all_dates else -1
-                    if prev_idx - curr_idx <= 2:  # 允许间隔1天
-                        consecutive += 1
-                        last_n.append(dates_list[i])
-                    else:
-                        break
-
-            if consecutive >= min_days:
+            if len(s["dates"]) >= days:
                 results.append({
                     "stockCode": code,
                     "stockName": s["stockName"],
-                    "consecutiveDays": consecutive,
-                    "recentDates": last_n,
-                    "dailyGains": {d: s["dailyGains"].get(d) for d in last_n},
+                    "consecutiveDays": len(s["dates"]),
+                    "recentDates": sorted(s["dates"]),
+                    "dailyGains": s["dailyGains"],
                 })
 
-        # 按连续天数降序排列
         results.sort(key=lambda x: -x["consecutiveDays"])
 
         return json.dumps({
-            "minDays": min_days,
-            "stocks": results[:30],
+            "days": days,
+            "recentDates": recent_dates,
+            "stocks": results,
         }, ensure_ascii=False)
     finally:
         conn.close()