From d1a222d9e9cc9e0371964334956b77d9c6d1a2cc Mon Sep 17 00:00:00 2001
From: zzlgreat <zzlgreat@gmail.com>
Date: Tue, 2 Dec 2025 12:22:49 +0800
Subject: [PATCH] update pay ui

---
 __pycache__/app_vx.cpython-310.pyc | Bin 132393 -> 153340 bytes
 app_vx.py                          | 500 +++++++++++++++++++----------
 2 files changed, 331 insertions(+), 169 deletions(-)

diff --git a/__pycache__/app_vx.cpython-310.pyc b/__pycache__/app_vx.cpython-310.pyc
index 59b31b8a914168b2d3c26b6b4be9a118d29fbd18..a772109ee2d7c6e92cb3ec8068c592a8f3d63b68 100644
GIT binary patch
delta 62052
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diff --git a/app_vx.py b/app_vx.py
index 1e51f6c6..9685449b 100644
--- a/app_vx.py
+++ b/app_vx.py
@@ -5381,6 +5381,114 @@ def get_comment_replies(comment_id):
         }), 500
 
 
+# 工具函数：解析JSON字段
+def parse_json_field(field_value):
+    """解析JSON字段"""
+    if not field_value:
+        return []
+    try:
+        if isinstance(field_value, str):
+            if field_value.startswith('['):
+                return json.loads(field_value)
+            else:
+                return field_value.split(',')
+        else:
+            return field_value
+    except:
+        return []
+
+
+# 工具函数：获取 future_events 表字段值，支持新旧字段回退
+def get_future_event_field(row, new_field, old_field):
+    """
+    获取 future_events 表字段值，支持新旧字段回退
+    如果新字段存在且不为空，使用新字段；否则使用旧字段
+    """
+    new_value = getattr(row, new_field, None) if hasattr(row, new_field) else None
+    old_value = getattr(row, old_field, None) if hasattr(row, old_field) else None
+
+    # 如果新字段有值（不为空字符串），使用新字段
+    if new_value is not None and str(new_value).strip():
+        return new_value
+    return old_value
+
+
+# 工具函数：解析新的 best_matches 数据结构（含研报引用信息）
+def parse_best_matches(best_matches_value):
+    """
+    解析新的 best_matches 数据结构（含研报引用信息）
+
+    新结构示例:
+    [
+        {
+            "stock_code": "300451.SZ",
+            "company_name": "创业慧康",
+            "original_description": "核心标的，医疗信息化...",
+            "best_report_title": "报告标题",
+            "best_report_author": "作者",
+            "best_report_sentences": "相关内容",
+            "best_report_match_score": "好",
+            "best_report_match_ratio": 0.9285714285714286,
+            "best_report_declare_date": "2023-04-25T00:00:00",
+            "total_reports": 9,
+            "high_score_reports": 6
+        },
+        ...
+    ]
+
+    返回统一格式的股票列表，兼容旧格式
+    """
+    if not best_matches_value:
+        return []
+
+    try:
+        # 解析 JSON
+        if isinstance(best_matches_value, str):
+            data = json.loads(best_matches_value)
+        else:
+            data = best_matches_value
+
+        if not isinstance(data, list):
+            return []
+
+        result = []
+        for item in data:
+            if isinstance(item, dict):
+                # 新结构：包含研报信息的字典
+                stock_info = {
+                    'code': item.get('stock_code', ''),
+                    'name': item.get('company_name', ''),
+                    'description': item.get('original_description', ''),
+                    'score': item.get('best_report_match_ratio', 0),
+                    # 研报引用信息
+                    'report': {
+                        'title': item.get('best_report_title', ''),
+                        'author': item.get('best_report_author', ''),
+                        'sentences': item.get('best_report_sentences', ''),
+                        'match_score': item.get('best_report_match_score', ''),
+                        'match_ratio': item.get('best_report_match_ratio', 0),
+                        'declare_date': item.get('best_report_declare_date', ''),
+                        'total_reports': item.get('total_reports', 0),
+                        'high_score_reports': item.get('high_score_reports', 0)
+                    } if item.get('best_report_title') else None
+                }
+                result.append(stock_info)
+            elif isinstance(item, (list, tuple)) and len(item) >= 2:
+                # 旧结构：[code, name, description, score]
+                result.append({
+                    'code': item[0],
+                    'name': item[1],
+                    'description': item[2] if len(item) > 2 else '',
+                    'score': item[3] if len(item) > 3 else 0,
+                    'report': None
+                })
+
+        return result
+    except Exception as e:
+        print(f"parse_best_matches error: {e}")
+        return []
+
+
 # 工具函数：处理转义字符，保留 Markdown 格式
 def unescape_markdown_text(text):
     """
@@ -5470,6 +5578,7 @@ def api_calendar_events():
         offset = (page - 1) * per_page
 
         # 构建基础查询 - 使用 future_events 表
+        # 添加新字段 second_modified_text, `second_modified_text.1`, best_matches 支持新旧回退
         query = """
                 SELECT data_id, \
                        calendar_time, \
@@ -5481,7 +5590,10 @@ def api_calendar_events():
                        fact, \
                        related_stocks, \
                        concepts, \
-                       inferred_tag
+                       inferred_tag, \
+                       second_modified_text, \
+                       `second_modified_text.1` as second_modified_text_1, \
+                       best_matches
                 FROM future_events
                 WHERE 1 = 1 \
                 """
@@ -5552,90 +5664,114 @@ def api_calendar_events():
 
         events_data = []
         for event in events:
-            # 解析相关股票
+            # 使用新字段回退机制获取 former 和 forecast
+            # second_modified_text -> former
+            former_value = get_future_event_field(event, 'second_modified_text', 'former')
+            # second_modified_text.1 -> forecast
+            forecast_new = getattr(event, 'second_modified_text_1', None)
+            forecast_value = forecast_new if (forecast_new and str(forecast_new).strip()) else getattr(event, 'forecast', None)
+
+            # 解析相关股票 - 优先使用 best_matches，回退到 related_stocks
             related_stocks_list = []
             related_avg_chg = 0
             related_max_chg = 0
             related_week_chg = 0
 
-            # 处理相关股票数据
-            if event.related_stocks:
+            # 优先使用 best_matches（新结构，含研报引用）
+            best_matches = getattr(event, 'best_matches', None)
+            if best_matches and str(best_matches).strip():
+                # 使用新的 parse_best_matches 函数解析
+                parsed_stocks = parse_best_matches(best_matches)
+            else:
+                # 回退到旧的 related_stocks 处理
+                parsed_stocks = []
+                if event.related_stocks:
+                    try:
+                        import ast
+                        if isinstance(event.related_stocks, str):
+                            try:
+                                stock_data = json.loads(event.related_stocks)
+                            except:
+                                stock_data = ast.literal_eval(event.related_stocks)
+                        else:
+                            stock_data = event.related_stocks
+
+                        if stock_data:
+                            for stock_info in stock_data:
+                                if isinstance(stock_info, list) and len(stock_info) >= 2:
+                                    parsed_stocks.append({
+                                        'code': stock_info[0],
+                                        'name': stock_info[1],
+                                        'description': stock_info[2] if len(stock_info) > 2 else '',
+                                        'score': stock_info[3] if len(stock_info) > 3 else 0,
+                                        'report': None
+                                    })
+                    except Exception as e:
+                        print(f"Error parsing related_stocks for event {event.data_id}: {e}")
+
+            # 处理解析后的股票数据，获取交易信息
+            if parsed_stocks:
                 try:
-                    import json
-                    import ast
+                    daily_changes = []
+                    week_changes = []
 
-                    # 使用与detail接口相同的解析逻辑
-                    if isinstance(event.related_stocks, str):
-                        try:
-                            stock_data = json.loads(event.related_stocks)
-                        except:
-                            stock_data = ast.literal_eval(event.related_stocks)
-                    else:
-                        stock_data = event.related_stocks
+                    for stock_info in parsed_stocks:
+                        stock_code = stock_info.get('code', '')
+                        stock_name = stock_info.get('name', '')
+                        description = stock_info.get('description', '')
+                        score = stock_info.get('score', 0)
+                        report = stock_info.get('report', None)
 
-                    if stock_data:
-                        daily_changes = []
-                        week_changes = []
+                        if stock_code:
+                            # 规范化股票代码，移除后缀
+                            clean_code = stock_code.replace('.SZ', '').replace('.SH', '').replace('.BJ', '')
 
-                        # 处理正确的数据格式 [股票代码, 股票名称, 描述, 分数]
-                        for stock_info in stock_data:
-                            if isinstance(stock_info, list) and len(stock_info) >= 2:
-                                stock_code = stock_info[0]  # 股票代码
-                                stock_name = stock_info[1]  # 股票名称
-                                description = stock_info[2] if len(stock_info) > 2 else ''
-                                score = stock_info[3] if len(stock_info) > 3 else 0
-                            else:
-                                continue
+                            # 使用模糊匹配查询真实的交易数据
+                            trade_query = """
+                                          SELECT F007N as close_price, F010N as change_pct, TRADEDATE
+                                          FROM ea_trade
+                                          WHERE SECCODE LIKE :stock_code_pattern
+                                          ORDER BY TRADEDATE DESC LIMIT 7 \
+                                          """
+                            trade_result = db.session.execute(text(trade_query),
+                                                              {'stock_code_pattern': f'{clean_code}%'})
+                            trade_data = trade_result.fetchall()
 
-                            if stock_code:
-                                # 规范化股票代码，移除后缀
-                                clean_code = stock_code.replace('.SZ', '').replace('.SH', '').replace('.BJ', '')
+                            daily_chg = 0
+                            week_chg = 0
 
-                                # 使用模糊匹配查询真实的交易数据
-                                trade_query = """
-                                              SELECT F007N as close_price, F010N as change_pct, TRADEDATE
-                                              FROM ea_trade
-                                              WHERE SECCODE LIKE :stock_code_pattern
-                                              ORDER BY TRADEDATE DESC LIMIT 7 \
-                                              """
-                                trade_result = db.session.execute(text(trade_query),
-                                                                  {'stock_code_pattern': f'{clean_code}%'})
-                                trade_data = trade_result.fetchall()
+                            if trade_data:
+                                # 日涨跌幅（当日）
+                                daily_chg = float(trade_data[0].change_pct or 0)
 
-                                daily_chg = 0
-                                week_chg = 0
+                                # 周涨跌幅（5个交易日）
+                                if len(trade_data) >= 5:
+                                    current_price = float(trade_data[0].close_price or 0)
+                                    week_ago_price = float(trade_data[4].close_price or 0)
+                                    if week_ago_price > 0:
+                                        week_chg = ((current_price - week_ago_price) / week_ago_price) * 100
 
-                                if trade_data:
-                                    # 日涨跌幅（当日）
-                                    daily_chg = float(trade_data[0].change_pct or 0)
+                            # 收集涨跌幅数据
+                            daily_changes.append(daily_chg)
+                            week_changes.append(week_chg)
 
-                                    # 周涨跌幅（5个交易日）
-                                    if len(trade_data) >= 5:
-                                        current_price = float(trade_data[0].close_price or 0)
-                                        week_ago_price = float(trade_data[4].close_price or 0)
-                                        if week_ago_price > 0:
-                                            week_chg = ((current_price - week_ago_price) / week_ago_price) * 100
+                            related_stocks_list.append({
+                                'code': stock_code,
+                                'name': stock_name,
+                                'description': description,
+                                'score': score,
+                                'daily_chg': daily_chg,
+                                'week_chg': week_chg,
+                                'report': report  # 添加研报引用信息
+                            })
 
-                                # 收集涨跌幅数据
-                                daily_changes.append(daily_chg)
-                                week_changes.append(week_chg)
+                    # 计算平均收益率
+                    if daily_changes:
+                        related_avg_chg = round(sum(daily_changes) / len(daily_changes), 4)
+                        related_max_chg = round(max(daily_changes), 4)
 
-                                related_stocks_list.append({
-                                    'code': stock_code,
-                                    'name': stock_name,
-                                    'description': description,
-                                    'score': score,
-                                    'daily_chg': daily_chg,
-                                    'week_chg': week_chg
-                                })
-
-                        # 计算平均收益率
-                        if daily_changes:
-                            related_avg_chg = round(sum(daily_changes) / len(daily_changes), 4)
-                            related_max_chg = round(max(daily_changes), 4)
-
-                        if week_changes:
-                            related_week_chg = round(sum(week_changes) / len(week_changes), 4)
+                    if week_changes:
+                        related_week_chg = round(sum(week_changes) / len(week_changes), 4)
 
                 except Exception as e:
                     print(f"Error processing related stocks for event {event.data_id}: {e}")
@@ -5660,8 +5796,9 @@ def api_calendar_events():
                     highlight_match = 'concepts'
 
             # 将转义的换行符转换为真正的换行符，保留 Markdown 格式
-            cleaned_former = unescape_markdown_text(event.former)
-            cleaned_forecast = unescape_markdown_text(event.forecast)
+            # 使用新字段回退后的值（former_value, forecast_value）
+            cleaned_former = unescape_markdown_text(former_value)
+            cleaned_forecast = unescape_markdown_text(forecast_value)
             cleaned_fact = unescape_markdown_text(event.fact)
 
             event_dict = {
@@ -5907,6 +6044,7 @@ 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:
         # 从 future_events 表查询事件详情
+        # 添加新字段 second_modified_text, `second_modified_text.1`, best_matches 支持新旧回退
         query = """
                 SELECT data_id, \
                        calendar_time, \
@@ -5917,7 +6055,10 @@ def api_future_event_detail(item_id):
                        forecast, \
                        fact, \
                        related_stocks, \
-                       concepts
+                       concepts, \
+                       second_modified_text, \
+                       `second_modified_text.1` as second_modified_text_1, \
+                       best_matches
                 FROM future_events
                 WHERE data_id = :item_id \
                 """
@@ -5932,6 +6073,13 @@ def api_future_event_detail(item_id):
                 'data': None
             }), 404
 
+        # 使用新字段回退机制获取 former 和 forecast
+        # second_modified_text -> former
+        former_value = get_future_event_field(event, 'second_modified_text', 'former')
+        # second_modified_text.1 -> forecast
+        forecast_new = getattr(event, 'second_modified_text_1', None)
+        forecast_value = forecast_new if (forecast_new and str(forecast_new).strip()) else getattr(event, 'forecast', None)
+
         extracted_concepts = extract_concepts_from_concepts_field(event.concepts)
 
         # 解析相关股票
@@ -5975,136 +6123,150 @@ def api_future_event_detail(item_id):
             '环保': '公共产业板块', '综合': '公共产业板块'
         }
 
-        # 处理相关股票
+        # 处理相关股票 - 优先使用 best_matches，回退到 related_stocks
         related_avg_chg = 0
         related_max_chg = 0
         related_week_chg = 0
 
-        if event.related_stocks:
+        # 优先使用 best_matches（新结构，含研报引用）
+        best_matches = getattr(event, 'best_matches', None)
+        if best_matches and str(best_matches).strip():
+            # 使用新的 parse_best_matches 函数解析
+            parsed_stocks = parse_best_matches(best_matches)
+        else:
+            # 回退到旧的 related_stocks 处理
+            parsed_stocks = []
+            if event.related_stocks:
+                try:
+                    import ast
+                    if isinstance(event.related_stocks, str):
+                        try:
+                            stock_data = json.loads(event.related_stocks)
+                        except:
+                            stock_data = ast.literal_eval(event.related_stocks)
+                    else:
+                        stock_data = event.related_stocks
+
+                    if stock_data:
+                        for stock_info in stock_data:
+                            if isinstance(stock_info, list) and len(stock_info) >= 2:
+                                parsed_stocks.append({
+                                    'code': stock_info[0],
+                                    'name': stock_info[1],
+                                    'description': stock_info[2] if len(stock_info) > 2 else '',
+                                    'score': stock_info[3] if len(stock_info) > 3 else 0,
+                                    'report': None
+                                })
+                except Exception as e:
+                    print(f"Error parsing related_stocks for event {event.data_id}: {e}")
+
+        # 处理解析后的股票数据
+        if parsed_stocks:
             try:
-                import json
-                import ast
+                daily_changes = []
+                week_changes = []
 
-                # **修正：正确解析related_stocks数据结构**
-                if isinstance(event.related_stocks, str):
-                    try:
-                        # 先尝试JSON解析
-                        stock_data = json.loads(event.related_stocks)
-                    except:
-                        # 如果JSON解析失败，尝试ast.literal_eval解析
-                        stock_data = ast.literal_eval(event.related_stocks)
-                else:
-                    stock_data = event.related_stocks
+                for stock_info in parsed_stocks:
+                    stock_code = stock_info.get('code', '')
+                    stock_name = stock_info.get('name', '')
+                    description = stock_info.get('description', '')
+                    score = stock_info.get('score', 0)
+                    report = stock_info.get('report', None)
 
-                print(f"Parsed stock_data: {stock_data}")  # 调试输出
+                    if stock_code:
+                        # 规范化股票代码，移除后缀
+                        clean_code = stock_code.replace('.SZ', '').replace('.SH', '').replace('.BJ', '')
 
-                if stock_data:
-                    daily_changes = []
-                    week_changes = []
+                        print(f"Processing stock: {clean_code} - {stock_name}")  # 调试输出
 
-                    # **修正：处理正确的数据格式 [股票代码, 股票名称, 描述, 分数]**
-                    for stock_info in stock_data:
-                        if isinstance(stock_info, list) and len(stock_info) >= 2:
-                            stock_code = stock_info[0]  # 第一个元素是股票代码
-                            stock_name = stock_info[1]  # 第二个元素是股票名称
-                            description = stock_info[2] if len(stock_info) > 2 else ''
-                            score = stock_info[3] if len(stock_info) > 3 else 0
-                        else:
-                            continue  # 跳过格式不正确的数据
+                        # 使用模糊匹配LIKE查询申万一级行业F004V
+                        sector_query = """
+                                       SELECT F004V as sw_primary_sector
+                                       FROM ea_sector
+                                       WHERE SECCODE LIKE :stock_code_pattern
+                                         AND F002V = '申银万国行业分类' LIMIT 1 \
+                                       """
+                        sector_result = db.session.execute(text(sector_query),
+                                                           {'stock_code_pattern': f'{clean_code}%'})
+                        sector_row = sector_result.fetchone()
 
-                        if stock_code:
-                            # 规范化股票代码，移除后缀
-                            clean_code = stock_code.replace('.SZ', '').replace('.SH', '').replace('.BJ', '')
+                        # 根据申万一级行业（F004V）映射到主板块
+                        sw_primary_sector = sector_row.sw_primary_sector if sector_row else None
+                        primary_sector = sector_map.get(sw_primary_sector, '其他') if sw_primary_sector else '其他'
 
-                            print(f"Processing stock: {clean_code} - {stock_name}")  # 调试输出
+                        print(
+                            f"Stock: {clean_code}, SW Primary: {sw_primary_sector}, Primary Sector: {primary_sector}")
 
-                            # 使用模糊匹配LIKE查询申万一级行业F004V
-                            sector_query = """
-                                           SELECT F004V as sw_primary_sector
-                                           FROM ea_sector
-                                           WHERE SECCODE LIKE :stock_code_pattern
-                                             AND F002V = '申银万国行业分类' LIMIT 1 \
-                                           """
-                            sector_result = db.session.execute(text(sector_query),
-                                                               {'stock_code_pattern': f'{clean_code}%'})
-                            sector_row = sector_result.fetchone()
+                        # 通过SQL查询获取真实的日涨跌幅和周涨跌幅
+                        trade_query = """
+                                      SELECT F007N as close_price, F010N as change_pct, TRADEDATE
+                                      FROM ea_trade
+                                      WHERE SECCODE LIKE :stock_code_pattern
+                                      ORDER BY TRADEDATE DESC LIMIT 7 \
+                                      """
+                        trade_result = db.session.execute(text(trade_query),
+                                                          {'stock_code_pattern': f'{clean_code}%'})
+                        trade_data = trade_result.fetchall()
 
-                            # 根据申万一级行业（F004V）映射到主板块
-                            sw_primary_sector = sector_row.sw_primary_sector if sector_row else None
-                            primary_sector = sector_map.get(sw_primary_sector, '其他') if sw_primary_sector else '其他'
+                        daily_chg = 0
+                        week_chg = 0
 
-                            print(
-                                f"Stock: {clean_code}, SW Primary: {sw_primary_sector}, Primary Sector: {primary_sector}")
+                        if trade_data:
+                            # 日涨跌幅（当日）
+                            daily_chg = float(trade_data[0].change_pct or 0)
 
-                            # 通过SQL查询获取真实的日涨跌幅和周涨跌幅
-                            trade_query = """
-                                          SELECT F007N as close_price, F010N as change_pct, TRADEDATE
-                                          FROM ea_trade
-                                          WHERE SECCODE LIKE :stock_code_pattern
-                                          ORDER BY TRADEDATE DESC LIMIT 7 \
-                                          """
-                            trade_result = db.session.execute(text(trade_query),
-                                                              {'stock_code_pattern': f'{clean_code}%'})
-                            trade_data = trade_result.fetchall()
+                            # 周涨跌幅（5个交易日）
+                            if len(trade_data) >= 5:
+                                current_price = float(trade_data[0].close_price or 0)
+                                week_ago_price = float(trade_data[4].close_price or 0)
+                                if week_ago_price > 0:
+                                    week_chg = ((current_price - week_ago_price) / week_ago_price) * 100
 
-                            daily_chg = 0
-                            week_chg = 0
+                        print(
+                            f"Trade data found: {len(trade_data) if trade_data else 0} records, daily_chg: {daily_chg}")
 
-                            if trade_data:
-                                # 日涨跌幅（当日）
-                                daily_chg = float(trade_data[0].change_pct or 0)
+                        # 统计各分类数量
+                        sector_stats['全部股票'] += 1
+                        sector_stats[primary_sector] += 1
 
-                                # 周涨跌幅（5个交易日）
-                                if len(trade_data) >= 5:
-                                    current_price = float(trade_data[0].close_price or 0)
-                                    week_ago_price = float(trade_data[4].close_price or 0)
-                                    if week_ago_price > 0:
-                                        week_chg = ((current_price - week_ago_price) / week_ago_price) * 100
+                        # 收集涨跌幅数据
+                        daily_changes.append(daily_chg)
+                        week_changes.append(week_chg)
 
-                            print(
-                                f"Trade data found: {len(trade_data) if trade_data else 0} records, daily_chg: {daily_chg}")
+                        related_stocks_list.append({
+                            'code': stock_code,  # 原始股票代码
+                            'name': stock_name,  # 股票名称
+                            'description': description,  # 关联描述
+                            'score': score,  # 关联分数
+                            'sw_primary_sector': sw_primary_sector,  # 申万一级行业（F004V）
+                            'primary_sector': primary_sector,  # 主板块分类
+                            'daily_change': daily_chg,  # 真实的日涨跌幅
+                            'week_change': week_chg,  # 真实的周涨跌幅
+                            'report': report  # 研报引用信息（新字段）
+                        })
 
-                            # 统计各分类数量
-                            sector_stats['全部股票'] += 1
-                            sector_stats[primary_sector] += 1
+                # 计算平均收益率
+                if daily_changes:
+                    related_avg_chg = sum(daily_changes) / len(daily_changes)
+                    related_max_chg = max(daily_changes)
 
-                            # 收集涨跌幅数据
-                            daily_changes.append(daily_chg)
-                            week_changes.append(week_chg)
-
-                            related_stocks_list.append({
-                                'code': stock_code,  # 原始股票代码
-                                'name': stock_name,  # 股票名称
-                                'description': description,  # 关联描述
-                                'score': score,  # 关联分数
-                                'sw_primary_sector': sw_primary_sector,  # 申万一级行业（F004V）
-                                'primary_sector': primary_sector,  # 主板块分类
-                                'daily_change': daily_chg,  # 真实的日涨跌幅
-                                'week_change': week_chg  # 真实的周涨跌幅
-                            })
-
-                    # 计算平均收益率
-                    if daily_changes:
-                        related_avg_chg = sum(daily_changes) / len(daily_changes)
-                        related_max_chg = max(daily_changes)
-
-                    if week_changes:
-                        related_week_chg = sum(week_changes) / len(week_changes)
+                if week_changes:
+                    related_week_chg = sum(week_changes) / len(week_changes)
 
             except Exception as e:
                 print(f"Error processing related stocks: {e}")
                 import traceback
                 traceback.print_exc()
 
-        # 构建返回数据
+        # 构建返回数据，使用新字段回退后的值
         detail_data = {
             'id': event.data_id,
             'title': event.title,
             'type': event.type,
             'star': event.star,
             'calendar_time': event.calendar_time.isoformat() if event.calendar_time else None,
-            'former': event.former,
-            'forecast': event.forecast,
+            'former': former_value,  # 使用回退后的值（优先 second_modified_text）
+            'forecast': forecast_value,  # 使用回退后的值（优先 second_modified_text.1）
             'fact': event.fact,
             'concepts': event.concepts,
             'extracted_concepts': extracted_concepts,