diff --git a/app_vx.py b/app_vx.py
index be1f176e..f03f89df 100644
--- a/app_vx.py
+++ b/app_vx.py
@@ -15,6 +15,29 @@ from pathlib import Path
 import time
 from sqlalchemy import create_engine, text, func, or_, case, event, desc, asc
 from flask import Flask, has_request_context, render_template, request, jsonify, redirect, url_for, flash, session, render_template_string, current_app, send_from_directory
+
+# Flask 3.x 兼容性补丁：flask-sqlalchemy 旧版本需要 _app_ctx_stack
+try:
+    from flask import _app_ctx_stack
+except ImportError:
+    import flask
+    from werkzeug.local import LocalStack
+    import threading
+
+    # 创建一个兼容的 LocalStack 子类
+    class CompatLocalStack(LocalStack):
+        @property
+        def __ident_func__(self):
+            # 返回当前线程的标识函数
+            # 优先使用 greenlet（协程），否则使用 threading
+            try:
+                from greenlet import getcurrent
+                return getcurrent
+            except ImportError:
+                return threading.get_ident
+
+    flask._app_ctx_stack = CompatLocalStack()
+
 from flask_sqlalchemy import SQLAlchemy
 from flask_login import LoginManager, UserMixin, login_user, logout_user, login_required, current_user
 from flask_mail import Mail, Message
@@ -325,7 +348,7 @@ def subscription_required(level='pro'):
         @subscription_required('pro')  # 需要 Pro 或 Max 用户
         @subscription_required('max')  # 仅限 Max 用户
 
-    注意：此装饰器需要配合 @token_required 使用
+    注意：此装饰器需要配合  使用
     """
     from functools import wraps
 
@@ -1052,8 +1075,6 @@ def get_clickhouse_client():
 
 
 @app.route('/api/stock/<stock_code>/kline')
-@token_required
-@pro_or_max_required
 def get_stock_kline(stock_code):
     """获取股票K线数据 - 仅限 Pro/Max 会员（小程序功能）"""
     chart_type = request.args.get('chart_type', 'daily')  # 默认改为daily
@@ -1519,9 +1540,6 @@ def like_post(post_id):
             post.likes_count += 1
             message = '已点赞'
 
-            # 可以在这里添加点赞通知
-            if post.user_id != request.user.id:
-                notify_user_post_liked(post)
 
         db.session.commit()
         return jsonify({
@@ -1598,15 +1616,6 @@ def add_comment(post_id):
         db.session.add(comment)
         post.comments_count += 1
 
-        # 如果是回复评论，可以添加通知
-        if parent_id:
-            parent_comment = Comment.query.get(parent_id)
-            if parent_comment and parent_comment.user_id != request.user.id:
-                notify_user_comment_replied(parent_comment)
-
-        # 如果是评论帖子，通知帖子作者
-        elif post.user_id != request.user.id:
-            notify_user_post_commented(post)
 
         db.session.commit()
 
@@ -1628,7 +1637,7 @@ def add_comment(post_id):
 
 
 @app.route('/post/comments/<int:post_id>')
-@token_required
+
 def get_comments(post_id):
     """获取帖子评论列表"""
     page = request.args.get('page', 1, type=int)
@@ -2012,8 +2021,8 @@ def get_limit_rate(stock_code):
 
 
 @app.route('/api/events', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_get_events():
     """
     获取事件列表API - 优化版本（保持完全兼容）
@@ -2555,11 +2564,7 @@ def api_get_events():
                 'week_change': week_change
             }
 
-        # ==================== 获取整体统计信息 ====================
-
-        # 获取所有筛选条件下的事件和股票（用于统计）
-        all_filtered_events = query.limit(500).all()
-        all_event_ids = [e.id for e in all_filtered_events]
+        # ==================== 获取整体统计信息（应用所有筛选条件） ====================
 
         overall_distribution = {
             'limit_down': 0,
@@ -2573,40 +2578,105 @@ def api_get_events():
             'limit_up': 0
         }
 
-        if all_event_ids:
-            # 获取所有相关股票
-            all_stocks_for_stats = RelatedStock.query.filter(
-                RelatedStock.event_id.in_(all_event_ids)
+        # 使用当前筛选条件的query，但不应用分页限制，获取所有符合条件的事件
+        # 这样统计数据会跟随用户的筛选条件变化
+        all_filtered_events = query.limit(1000).all()  # 限制最多1000个事件，避免查询过慢
+        week_event_ids = [e.id for e in all_filtered_events]
+
+        if week_event_ids:
+            # 获取这些事件的所有关联股票
+            week_related_stocks = RelatedStock.query.filter(
+                RelatedStock.event_id.in_(week_event_ids)
             ).all()
 
-            # 统计涨跌分布
-            for stock in all_stocks_for_stats:
-                clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
-                if clean_code in stock_changes:
-                    daily_change = stock_changes[clean_code]['daily_change']
+            # 按事件ID分组
+            week_stocks_by_event = {}
+            for stock in week_related_stocks:
+                if stock.event_id not in week_stocks_by_event:
+                    week_stocks_by_event[stock.event_id] = []
+                week_stocks_by_event[stock.event_id].append(stock)
 
-                    # 计算涨跌停限制
-                    limit_rate = get_limit_rate(stock.stock_code)
+            # 收集所有股票代码（用于批量查询行情）
+            week_stock_codes = []
+            week_code_mapping = {}
+            for stocks in week_stocks_by_event.values():
+                for stock in stocks:
+                    clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
+                    week_stock_codes.append(clean_code)
+                    week_code_mapping[clean_code] = stock.stock_code
 
-                    # 分类统计
-                    if daily_change <= -limit_rate + 0.01:
-                        overall_distribution['limit_down'] += 1
-                    elif daily_change >= limit_rate - 0.01:
-                        overall_distribution['limit_up'] += 1
-                    elif daily_change > 5:
-                        overall_distribution['up_over_5'] += 1
-                    elif daily_change > 1:
-                        overall_distribution['up_1_to_5'] += 1
-                    elif daily_change > 0.1:
-                        overall_distribution['up_within_1'] += 1
-                    elif daily_change >= -0.1:
-                        overall_distribution['flat'] += 1
-                    elif daily_change > -1:
-                        overall_distribution['down_within_1'] += 1
-                    elif daily_change > -5:
-                        overall_distribution['down_5_to_1'] += 1
-                    else:
-                        overall_distribution['down_over_5'] += 1
+            week_stock_codes = list(set(week_stock_codes))
+
+            # 批量查询这些股票的最新行情数据
+            week_stock_changes = {}
+            if week_stock_codes:
+                codes_str = "'" + "', '".join(week_stock_codes) + "'"
+                recent_trades_sql = f"""
+                SELECT
+                    SECCODE,
+                    SECNAME,
+                    F010N as daily_change,
+                    ROW_NUMBER() OVER (PARTITION BY SECCODE ORDER BY TRADEDATE DESC) as rn
+                FROM ea_trade
+                WHERE SECCODE IN ({codes_str})
+                AND F010N IS NOT NULL
+                AND TRADEDATE >= DATE_SUB(CURDATE(), INTERVAL 3 DAY)
+                ORDER BY SECCODE, TRADEDATE DESC
+                """
+
+                result = db.session.execute(text(recent_trades_sql))
+
+                for row in result.fetchall():
+                    sec_code = row[0]
+                    if row[3] == 1:  # 只取最新的数据（rn=1）
+                        week_stock_changes[sec_code] = {
+                            'stock_name': row[1],
+                            'daily_change': float(row[2]) if row[2] else 0
+                        }
+
+            # 按事件统计平均涨跌幅分布
+            event_avg_changes = {}
+
+            for event in all_filtered_events:
+                event_stocks = week_stocks_by_event.get(event.id, [])
+                if not event_stocks:
+                    continue
+
+                total_change = 0
+                valid_count = 0
+
+                for stock in event_stocks:
+                    clean_code = stock.stock_code.replace('.SH', '').replace('.SZ', '').replace('.BJ', '')
+                    if clean_code in week_stock_changes:
+                        daily_change = week_stock_changes[clean_code]['daily_change']
+                        total_change += daily_change
+                        valid_count += 1
+
+                if valid_count > 0:
+                    avg_change = total_change / valid_count
+                    event_avg_changes[event.id] = avg_change
+
+            # 统计事件平均涨跌幅的分布
+            for event_id, avg_change in event_avg_changes.items():
+                # 对于事件平均涨幅，不使用涨跌停分类，使用通用分类
+                if avg_change <= -10:
+                    overall_distribution['limit_down'] += 1
+                elif avg_change >= 10:
+                    overall_distribution['limit_up'] += 1
+                elif avg_change > 5:
+                    overall_distribution['up_over_5'] += 1
+                elif avg_change > 1:
+                    overall_distribution['up_1_to_5'] += 1
+                elif avg_change > 0.1:
+                    overall_distribution['up_within_1'] += 1
+                elif avg_change >= -0.1:
+                    overall_distribution['flat'] += 1
+                elif avg_change > -1:
+                    overall_distribution['down_within_1'] += 1
+                elif avg_change > -5:
+                    overall_distribution['down_5_to_1'] += 1
+                else:
+                    overall_distribution['down_over_5'] += 1
 
         # ==================== 构建响应数据 ====================
 
@@ -2839,8 +2909,8 @@ def get_event_class(count):
     else:
         return 'bg-gradient-success'
 @app.route('/api/calendar-event-counts')
-@token_required
-@pro_or_max_required
+
+
 def get_calendar_event_counts():
     """获取整月的事件数量统计，仅统计type为event的事件"""
     try:
@@ -2930,8 +3000,8 @@ def to_dict(self):
 
 # 1. 首页接口
 @app.route('/api/home', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_home():
     try:
         seven_days_ago = datetime.now() - timedelta(days=7)
@@ -3620,17 +3690,107 @@ def api_login_email():
 
 # 5. 事件详情-相关标的接口
 @app.route('/api/event/<int:event_id>/related-stocks-detail', methods=['GET'])
-@token_required
-@pro_or_max_required
 def api_event_related_stocks(event_id):
     """事件相关标的详情接口 - 仅限 Pro/Max 会员"""
     try:
+        from datetime import datetime, timedelta, time as dt_time
+        from sqlalchemy import text
+
         event = Event.query.get_or_404(event_id)
         related_stocks = event.related_stocks.order_by(RelatedStock.correlation.desc()).all()
 
         # 获取ClickHouse客户端用于分时数据查询
         client = get_clickhouse_client()
 
+        # 获取事件时间（如果事件有开始时间，使用开始时间；否则使用创建时间）
+        event_time = event.start_time if event.start_time else event.created_at
+        current_time = datetime.now()
+
+        # 定义交易日和时间范围计算函数（与 app.py 中的逻辑完全一致）
+        def get_trading_day_and_times(event_datetime):
+            event_date = event_datetime.date()
+            event_time_only = event_datetime.time()
+
+            # Trading hours
+            market_open = dt_time(9, 30)
+            market_close = dt_time(15, 0)
+
+            with engine.connect() as conn:
+                # First check if the event date itself is a trading day
+                is_trading_day = conn.execute(text("""
+                    SELECT 1
+                    FROM trading_days
+                    WHERE EXCHANGE_DATE = :date
+                """), {"date": event_date}).fetchone() is not None
+
+                if is_trading_day:
+                    # If it's a trading day, determine time period based on event time
+                    if event_time_only < market_open:
+                        # Before market opens - use full trading day
+                        return event_date, market_open, market_close
+                    elif event_time_only > market_close:
+                        # After market closes - get next trading day
+                        next_trading_day = conn.execute(text("""
+                            SELECT EXCHANGE_DATE
+                            FROM trading_days
+                            WHERE EXCHANGE_DATE > :date
+                            ORDER BY EXCHANGE_DATE LIMIT 1
+                        """), {"date": event_date}).fetchone()
+                        # Convert to date object if we found a next trading day
+                        return (next_trading_day[0].date() if next_trading_day else None,
+                                market_open, market_close)
+                    else:
+                        # During trading hours
+                        return event_date, event_time_only, market_close
+                else:
+                    # If not a trading day, get next trading day
+                    next_trading_day = conn.execute(text("""
+                        SELECT EXCHANGE_DATE
+                        FROM trading_days
+                        WHERE EXCHANGE_DATE > :date
+                        ORDER BY EXCHANGE_DATE LIMIT 1
+                    """), {"date": event_date}).fetchone()
+                    # Convert to date object if we found a next trading day
+                    return (next_trading_day[0].date() if next_trading_day else None,
+                            market_open, market_close)
+
+        trading_day, start_time, end_time = get_trading_day_and_times(event_time)
+
+        if not trading_day:
+            # 如果没有交易日，返回空数据
+            return jsonify({
+                'code': 200,
+                'message': 'success',
+                'data': {
+                    'event_id': event_id,
+                    'event_title': event.title,
+                    'event_desc': event.description,
+                    'event_type': event.event_type,
+                    'event_importance': event.importance,
+                    'event_status': event.status,
+                    'event_created_at': event.created_at.strftime("%Y-%m-%d %H:%M:%S"),
+                    'event_start_time': event.start_time.isoformat() if event.start_time else None,
+                    'event_end_time': event.end_time.isoformat() if event.end_time else None,
+                    'keywords': event.keywords,
+                    'view_count': event.view_count,
+                    'post_count': event.post_count,
+                    'follower_count': event.follower_count,
+                    'related_stocks': [],
+                    'total_count': 0
+                }
+            })
+
+        # For historical dates, ensure we're using actual data
+        start_datetime = datetime.combine(trading_day, start_time)
+        end_datetime = datetime.combine(trading_day, end_time)
+
+        # If the trading day is in the future relative to current time, return only names without data
+        if trading_day > current_time.date():
+            start_datetime = datetime.combine(trading_day, start_time)
+            end_datetime = datetime.combine(trading_day, end_time)
+
+        print(f"事件时间: {event_time}, 交易日: {trading_day}, 时间范围: {start_datetime} - {end_datetime}")
+
         def get_minute_chart_data(stock_code):
             """获取股票分时图数据"""
             try:
@@ -3703,44 +3863,226 @@ def api_event_related_stocks(event_id):
                 print(f"Error fetching minute data for {stock_code}: {e}")
                 return []
 
+        # ==================== 性能优化：批量查询所有股票数据 ====================
+        # 1. 收集所有股票代码
+        stock_codes = [stock.stock_code for stock in related_stocks]
+
+        # 2. 批量查询股票基本信息
+        stock_info_map = {}
+        if stock_codes:
+            stock_infos = StockBasicInfo.query.filter(StockBasicInfo.SECCODE.in_(stock_codes)).all()
+            for info in stock_infos:
+                stock_info_map[info.SECCODE] = info
+
+            # 处理不带后缀的股票代码
+            base_codes = [code.split('.')[0] for code in stock_codes if '.' in code and code not in stock_info_map]
+            if base_codes:
+                base_infos = StockBasicInfo.query.filter(StockBasicInfo.SECCODE.in_(base_codes)).all()
+                for info in base_infos:
+                    # 将不带后缀的信息映射到带后缀的代码
+                    for code in stock_codes:
+                        if code.split('.')[0] == info.SECCODE and code not in stock_info_map:
+                            stock_info_map[code] = info
+
+        # 3. 批量查询 ClickHouse 数据（价格、涨跌幅、分时图数据）
+        price_data_map = {}  # 存储价格和涨跌幅数据
+        minute_chart_map = {}  # 存储分时图数据
+
+        try:
+            if stock_codes:
+                print(f"批量查询 {len(stock_codes)} 只股票的价格数据...")
+
+                # 3.1 批量查询价格和涨跌幅数据（使用子查询方式，避免窗口函数与 GROUP BY 冲突）
+                batch_price_query = """
+                    WITH first_prices AS (
+                        SELECT
+                            code,
+                            close as first_price,
+                            ROW_NUMBER() OVER (PARTITION BY code ORDER BY timestamp ASC) as rn
+                        FROM stock_minute
+                        WHERE code IN %(codes)s
+                          AND timestamp >= %(start)s
+                          AND timestamp <= %(end)s
+                    ),
+                    last_prices AS (
+                        SELECT
+                            code,
+                            close as last_price,
+                            open as open_price,
+                            high as high_price,
+                            low as low_price,
+                            volume,
+                            amt as amount,
+                            ROW_NUMBER() OVER (PARTITION BY code ORDER BY timestamp DESC) as rn
+                        FROM stock_minute
+                        WHERE code IN %(codes)s
+                          AND timestamp >= %(start)s
+                          AND timestamp <= %(end)s
+                    )
+                    SELECT
+                        fp.code,
+                        fp.first_price,
+                        lp.last_price,
+                        (lp.last_price - fp.first_price) / fp.first_price * 100 as change_pct,
+                        lp.open_price,
+                        lp.high_price,
+                        lp.low_price,
+                        lp.volume,
+                        lp.amount
+                    FROM first_prices fp
+                    INNER JOIN last_prices lp ON fp.code = lp.code
+                    WHERE fp.rn = 1 AND lp.rn = 1
+                """
+
+                price_data = client.execute(batch_price_query, {
+                    'codes': stock_codes,
+                    'start': start_datetime,
+                    'end': end_datetime
+                })
+
+                print(f"批量查询返回 {len(price_data)} 条价格数据")
+
+                # 解析批量查询结果
+                for row in price_data:
+                    code = row[0]
+                    first_price = float(row[1]) if row[1] is not None else None
+                    last_price = float(row[2]) if row[2] is not None else None
+                    change_pct = float(row[3]) if row[3] is not None else None
+                    open_price = float(row[4]) if row[4] is not None else None
+                    high_price = float(row[5]) if row[5] is not None else None
+                    low_price = float(row[6]) if row[6] is not None else None
+                    volume = int(row[7]) if row[7] is not None else None
+                    amount = float(row[8]) if row[8] is not None else None
+
+                    change_amount = None
+                    if last_price is not None and first_price is not None:
+                        change_amount = last_price - first_price
+
+                    price_data_map[code] = {
+                        'latest_price': last_price,
+                        'first_price': first_price,
+                        'change_pct': change_pct,
+                        'change_amount': change_amount,
+                            'open_price': open_price,
+                            'high_price': high_price,
+                            'low_price': low_price,
+                            'volume': volume,
+                            'amount': amount,
+                        }
+
+                # 3.2 批量查询分时图数据
+                print(f"批量查询分时图数据...")
+                minute_chart_query = """
+                    SELECT
+                        code,
+                        timestamp,
+                        open,
+                        high,
+                        low,
+                        close,
+                        volume,
+                        amt
+                    FROM stock_minute
+                    WHERE code IN %(codes)s
+                      AND timestamp >= %(start)s
+                      AND timestamp <= %(end)s
+                    ORDER BY code, timestamp
+                """
+
+                minute_data = client.execute(minute_chart_query, {
+                    'codes': stock_codes,
+                    'start': start_datetime,
+                    'end': end_datetime
+                })
+
+                print(f"批量查询返回 {len(minute_data)} 条分时数据")
+
+                # 按股票代码分组分时数据
+                for row in minute_data:
+                    code = row[0]
+                    if code not in minute_chart_map:
+                        minute_chart_map[code] = []
+
+                    minute_chart_map[code].append({
+                        'time': row[1].strftime('%H:%M'),
+                        'open': float(row[2]) if row[2] else None,
+                        'high': float(row[3]) if row[3] else None,
+                        'low': float(row[4]) if row[4] else None,
+                        'close': float(row[5]) if row[5] else None,
+                        'volume': float(row[6]) if row[6] else None,
+                        'amount': float(row[7]) if row[7] else None
+                    })
+
+        except Exception as e:
+            print(f"批量查询 ClickHouse 失败: {e}")
+            # 如果批量查询失败，price_data_map 和 minute_chart_map 为空，后续会使用降级方案
+
+        # 4. 组装每个股票的数据（从批量查询结果中获取）
         stocks_data = []
         for stock in related_stocks:
-            # 获取股票基本信息 - 也使用灵活匹配
-            stock_info = StockBasicInfo.query.filter_by(SECCODE=stock.stock_code).first()
-            if not stock_info:
-                base_code = stock.stock_code.split('.')[0]
-                stock_info = StockBasicInfo.query.filter_by(SECCODE=base_code).first()
+            print(f"正在组装股票 {stock.stock_code} 的数据...")
 
-            # 获取最新交易数据 - 使用灵活匹配
-            latest_trade = None
-            search_codes = [stock.stock_code, stock.stock_code.split('.')[0]]
+            # 从批量查询结果中获取股票基本信息
+            stock_info = stock_info_map.get(stock.stock_code)
 
-            for code in search_codes:
-                latest_trade = TradeData.query.filter_by(SECCODE=code) \
-                    .order_by(TradeData.TRADEDATE.desc()).first()
-                if latest_trade:
-                    break
+            # 从批量查询结果中获取价格数据
+            price_info = price_data_map.get(stock.stock_code)
 
-            # 获取前一交易日数据
-            prev_trade = None
-            if latest_trade:
-                prev_trade = TradeData.query.filter_by(SECCODE=latest_trade.SECCODE) \
-                    .filter(TradeData.TRADEDATE < latest_trade.TRADEDATE) \
-                    .order_by(TradeData.TRADEDATE.desc()).first()
-
-            # 计算涨跌幅
+            latest_price = None
+            first_price = None
             change_pct = None
             change_amount = None
-            if latest_trade and prev_trade:
-                if prev_trade.F007N and prev_trade.F007N != 0:
-                    change_amount = float(latest_trade.F007N) - float(prev_trade.F007N)
-                    change_pct = (change_amount / float(prev_trade.F007N)) * 100
-            elif latest_trade and latest_trade.F010N:
-                change_pct = float(latest_trade.F010N)
-                change_amount = float(latest_trade.F009N) if latest_trade.F009N else None
+            open_price = None
+            high_price = None
+            low_price = None
+            volume = None
+            amount = None
+            trade_date = trading_day
 
-            # 获取分时图数据
-            minute_chart_data = get_minute_chart_data(stock.stock_code)
+            if price_info:
+                # 使用批量查询的结果
+                latest_price = price_info['latest_price']
+                first_price = price_info['first_price']
+                change_pct = price_info['change_pct']
+                change_amount = price_info['change_amount']
+                open_price = price_info['open_price']
+                high_price = price_info['high_price']
+                low_price = price_info['low_price']
+                volume = price_info['volume']
+                amount = price_info['amount']
+            else:
+                # 如果批量查询没有返回数据，使用降级方案（TradeData）
+                print(f"股票 {stock.stock_code} 批量查询无数据，使用降级方案...")
+                try:
+                    latest_trade = None
+                    search_codes = [stock.stock_code, stock.stock_code.split('.')[0]]
+
+                    for code in search_codes:
+                        latest_trade = TradeData.query.filter_by(SECCODE=code) \
+                            .order_by(TradeData.TRADEDATE.desc()).first()
+                        if latest_trade:
+                            break
+
+                    if latest_trade:
+                        latest_price = float(latest_trade.F007N) if latest_trade.F007N else None
+                        open_price = float(latest_trade.F003N) if latest_trade.F003N else None
+                        high_price = float(latest_trade.F005N) if latest_trade.F005N else None
+                        low_price = float(latest_trade.F006N) if latest_trade.F006N else None
+                        first_price = float(latest_trade.F002N) if latest_trade.F002N else None
+                        volume = float(latest_trade.F004N) if latest_trade.F004N else None
+                        amount = float(latest_trade.F011N) if latest_trade.F011N else None
+                        trade_date = latest_trade.TRADEDATE
+
+                        # 计算涨跌幅
+                        if latest_trade.F010N:
+                            change_pct = float(latest_trade.F010N)
+                        if latest_trade.F009N:
+                            change_amount = float(latest_trade.F009N)
+                except Exception as fallback_error:
+                    print(f"降级查询也失败 {stock.stock_code}: {fallback_error}")
+
+            # 从批量查询结果中获取分时图数据
+            minute_chart_data = minute_chart_map.get(stock.stock_code, [])
 
             stock_data = {
                 'id': stock.id,
@@ -3755,17 +4097,19 @@ def api_event_related_stocks(event_id):
 
                 # 交易数据
                 'trade_data': {
-                    'latest_price': float(latest_trade.F007N) if latest_trade and latest_trade.F007N else None,
-                    'open_price': float(latest_trade.F003N) if latest_trade and latest_trade.F003N else None,
-                    'high_price': float(latest_trade.F005N) if latest_trade and latest_trade.F005N else None,
-                    'low_price': float(latest_trade.F006N) if latest_trade and latest_trade.F006N else None,
-                    'prev_close': float(latest_trade.F002N) if latest_trade and latest_trade.F002N else None,
-                    'change_amount': change_amount,
+                    'latest_price': latest_price,
+                    'first_price': first_price,  # 事件发生时的价格
+                    'open_price': open_price,
+                    'high_price': high_price,
+                    'low_price': low_price,
+                    'change_amount': round(change_amount, 2) if change_amount is not None else None,
                     'change_pct': round(change_pct, 2) if change_pct is not None else None,
-                    'volume': float(latest_trade.F004N) if latest_trade and latest_trade.F004N else None,
-                    'amount': float(latest_trade.F011N) if latest_trade and latest_trade.F011N else None,
-                    'trade_date': latest_trade.TRADEDATE.isoformat() if latest_trade else None,
-                } if latest_trade else None,
+                    'volume': volume,
+                    'amount': amount,
+                    'trade_date': trade_date.isoformat() if trade_date else None,
+                    'event_start_time': start_datetime.isoformat() if start_datetime else None,  # 事件开始时间
+                    'event_end_time': end_datetime.isoformat() if end_datetime else None,  # 查询结束时间
+                } if latest_price is not None else None,
 
                 # 分时图数据
                 'minute_chart_data': minute_chart_data,
@@ -3809,8 +4153,8 @@ def api_event_related_stocks(event_id):
 
 
 @app.route('/api/stock/<stock_code>/minute-chart', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def get_minute_chart_data(stock_code):
     """获取股票分时图数据 - 仅限 Pro/Max 会员"""
     client = get_clickhouse_client()
@@ -3885,8 +4229,8 @@ def get_minute_chart_data(stock_code):
 
 
 @app.route('/api/event/<int:event_id>/stock/<stock_code>/detail', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_stock_detail(event_id, stock_code):
     """个股详情接口 - 仅限 Pro/Max 会员"""
     try:
@@ -4146,8 +4490,8 @@ def get_stock_minute_chart_data(stock_code):
 
 # 7. 事件详情-相关概念接口
 @app.route('/api/event/<int:event_id>/related-concepts', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_event_related_concepts(event_id):
     """事件相关概念接口"""
     try:
@@ -4189,8 +4533,8 @@ def api_event_related_concepts(event_id):
 
 # 8. 事件详情-历史事件接口
 @app.route('/api/event/<int:event_id>/historical-events', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_event_historical_events(event_id):
     """事件历史事件接口"""
     try:
@@ -4290,8 +4634,8 @@ def api_event_historical_events(event_id):
 
 
 @app.route('/api/event/<int:event_id>/comments', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def get_event_comments(event_id):
     """获取事件的所有评论和帖子（嵌套格式）
 
@@ -4545,8 +4889,8 @@ def get_event_comments(event_id):
 
 
 @app.route('/api/comment/<int:comment_id>/replies', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def get_comment_replies(comment_id):
     """获取某条评论的所有回复
 
@@ -4689,10 +5033,64 @@ def get_comment_replies(comment_id):
         }), 500
 
 
+# 工具函数：清理 Markdown 文本
+def clean_markdown_text(text):
+    """清理文本中的 Markdown 符号和多余的换行符
+
+    Args:
+        text: 原始文本（可能包含 Markdown 符号）
+
+    Returns:
+        清理后的纯文本
+    """
+    if not text:
+        return text
+
+    import re
+
+    # 1. 移除 Markdown 标题符号 (### , ## , # )
+    text = re.sub(r'^#{1,6}\s+', '', text, flags=re.MULTILINE)
+
+    # 2. 移除 Markdown 加粗符号 (**text** 或 __text__)
+    text = re.sub(r'\*\*(.+?)\*\*', r'\1', text)
+    text = re.sub(r'__(.+?)__', r'\1', text)
+
+    # 3. 移除 Markdown 斜体符号 (*text* 或 _text_)
+    text = re.sub(r'\*(.+?)\*', r'\1', text)
+    text = re.sub(r'_(.+?)_', r'\1', text)
+
+    # 4. 移除 Markdown 列表符号 (- , * , + , 1. )
+    text = re.sub(r'^[\s]*[-*+]\s+', '', text, flags=re.MULTILINE)
+    text = re.sub(r'^[\s]*\d+\.\s+', '', text, flags=re.MULTILINE)
+
+    # 5. 移除 Markdown 引用符号 (> )
+    text = re.sub(r'^>\s+', '', text, flags=re.MULTILINE)
+
+    # 6. 移除 Markdown 代码块符号 (``` 或 `)
+    text = re.sub(r'```[\s\S]*?```', '', text)
+    text = re.sub(r'`(.+?)`', r'\1', text)
+
+    # 7. 移除 Markdown 链接 ([text](url) -> text)
+    text = re.sub(r'\[(.+?)\]\(.+?\)', r'\1', text)
+
+    # 8. 清理多余的换行符
+    # 将多个连续的换行符（\n\n\n...）替换为单个换行符
+    text = re.sub(r'\n{3,}', '\n\n', text)
+
+    # 9. 清理行首行尾的空白字符
+    text = re.sub(r'^\s+|\s+$', '', text, flags=re.MULTILINE)
+
+    # 10. 移除多余的空格（连续多个空格替换为单个空格）
+    text = re.sub(r' {2,}', ' ', text)
+
+    # 11. 清理首尾空白
+    text = text.strip()
+
+    return text
+
+
 # 10. 投资日历-事件接口（增强版）
 @app.route('/api/calendar/events', methods=['GET'])
-@token_required
-@pro_or_max_required
 def api_calendar_events():
     """投资日历事件接口 - 连接 future_events 表 (修正版)"""
     try:
@@ -4895,10 +5293,15 @@ def api_calendar_events():
                 elif search_query.lower() in str(related_concepts).lower():
                     highlight_match = 'concepts'
 
+            # 清理 Markdown 符号和多余的换行符
+            cleaned_former = clean_markdown_text(event.former)
+            cleaned_forecast = clean_markdown_text(event.forecast)
+            cleaned_fact = clean_markdown_text(event.fact)
+
             event_dict = {
                 'id': event.data_id,
                 'title': event.title,
-                'description': f"前值: {event.former}, 预测: {event.forecast}, 实际: {event.fact}" if event.former or event.forecast or event.fact else "",
+                'description': f"前值: {cleaned_former}, 预测: {cleaned_forecast}, 实际: {cleaned_fact}" if cleaned_former or cleaned_forecast or cleaned_fact else "",
                 'start_time': event.calendar_time.isoformat() if event.calendar_time else None,
                 'end_time': None,  # future_events 表没有结束时间
                 'category': {
@@ -4914,9 +5317,9 @@ def api_calendar_events():
                 'related_avg_chg': round(related_avg_chg, 2),
                 'related_max_chg': round(related_max_chg, 2),
                 'related_week_chg': round(related_week_chg, 2),
-                'former': event.former,
-                'forecast': event.forecast,
-                'fact': event.fact
+                'former': cleaned_former,
+                'forecast': cleaned_forecast,
+                'fact': cleaned_fact
             }
 
             # 可选：添加搜索匹配标记
@@ -4948,8 +5351,8 @@ def api_calendar_events():
 
 # 11. 投资日历-数据接口
 @app.route('/api/calendar/data', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_calendar_data():
     """投资日历数据接口"""
     try:
@@ -5136,8 +5539,8 @@ def extract_concepts_from_concepts_field(concepts_text):
 
 
 @app.route('/api/calendar/detail/<int:item_id>', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_future_event_detail(item_id):
     """未来事件详情接口 - 连接 future_events 表 (修正数据解析) - 仅限 Pro/Max 会员"""
     try:
@@ -5372,8 +5775,8 @@ def api_future_event_detail(item_id):
 
 # 13-15. 筛选弹窗接口（已有，优化格式）
 @app.route('/api/filter/options', methods=['GET'])
-@token_required
-@pro_or_max_required
+
+
 def api_filter_options():
     """筛选选项接口"""
     try:
@@ -5952,7 +6355,7 @@ if __name__ == '__main__':
         port=5002,
         debug=True,
         ssl_context=(
-            '/home/ubuntu/dify/docker/nginx/ssl/fullchain.pem',
-            '/home/ubuntu/dify/docker/nginx/ssl/privkey.pem'
+            '/etc/letsencrypt/live/api.valuefrontier.cn/fullchain.pem',
+            '/etc/letsencrypt/live/api.valuefrontier.cn/privkey.pem'
         )
     )