feat：提供focus统计，查看你的no_reply吧！！

src/chat/utils/statistic.py

@@ -14,6 +14,16 @@ from src.manager.local_store_manager import local_storage
 
 logger = get_logger("maibot_statistic")
 
+# HFC统计相关的键
+HFC_TOTAL_CYCLES = "hfc_total_cycles"
+HFC_CYCLES_BY_CHAT = "hfc_cycles_by_chat"
+HFC_CYCLES_BY_ACTION = "hfc_cycles_by_action"
+HFC_CYCLES_BY_VERSION = "hfc_cycles_by_version"
+HFC_AVG_TIME_BY_CHAT = "hfc_avg_time_by_chat"
+HFC_AVG_TIME_BY_ACTION = "hfc_avg_time_by_action"
+HFC_AVG_TIME_BY_VERSION = "hfc_avg_time_by_version"
+HFC_ACTIONS_BY_CHAT = "hfc_actions_by_chat"  # 群聊×动作交叉统计
+
 # 统计数据的键
 TOTAL_REQ_CNT = "total_requests"
 TOTAL_COST = "total_cost"
@@ -457,6 +467,147 @@ class StatisticOutputTask(AsyncTask):
                     break
         return stats
 
+    def _collect_hfc_data_for_period(self, collect_period: List[Tuple[str, datetime]]) -> Dict[str, Any]:
+        """
+        收集指定时间段的HFC统计数据
+
+        :param collect_period: 统计时间段
+        """
+        if not collect_period:
+            return {}
+
+        # 为每个时间段初始化空的统计数据
+        stats = {
+            period_key: {
+                HFC_TOTAL_CYCLES: 0,
+                HFC_CYCLES_BY_CHAT: defaultdict(int),
+                HFC_CYCLES_BY_ACTION: defaultdict(int),
+                HFC_CYCLES_BY_VERSION: defaultdict(int),
+                HFC_AVG_TIME_BY_CHAT: defaultdict(lambda: {"decision": 0, "action": 0, "total": 0}),
+                HFC_AVG_TIME_BY_ACTION: defaultdict(lambda: {"decision": 0, "action": 0, "total": 0}),
+                HFC_AVG_TIME_BY_VERSION: defaultdict(lambda: {"decision": 0, "action": 0, "total": 0}),
+                HFC_ACTIONS_BY_CHAT: defaultdict(lambda: defaultdict(int)),  # 群聊×动作交叉统计
+
+            }
+            for period_key, _ in collect_period
+        }
+
+        try:
+            import json
+            from pathlib import Path
+            
+            hfc_stats_file = Path("data/hfc/time.json")
+            if not hfc_stats_file.exists():
+                logger.info("HFC统计文件不存在，跳过HFC统计")
+                return stats
+
+            # 读取HFC统计数据
+            with open(hfc_stats_file, 'r', encoding='utf-8') as f:
+                hfc_data = json.load(f)
+
+            # 处理每个chat_id和版本的统计数据
+            for stats_key, chat_stats in hfc_data.items():
+                chat_id = chat_stats.get("chat_id", "unknown")
+                version = chat_stats.get("version", "unknown")
+                last_updated_str = chat_stats.get("last_updated")
+                
+                if not last_updated_str:
+                    continue
+                
+                # 解析最后更新时间
+                try:
+                    last_updated = datetime.fromisoformat(last_updated_str.replace('Z', '+00:00'))
+                    if last_updated.tzinfo:
+                        last_updated = last_updated.replace(tzinfo=None)
+                except:
+                    continue
+
+                # 对于"全部时间"，所有数据都包含
+                # 对于其他时间段，只包含在时间范围内更新的数据
+                applicable_periods = []
+                for period_key, period_start in collect_period:
+                    if period_key == "all_time" or last_updated >= period_start:
+                        applicable_periods.append(period_key)
+
+                if not applicable_periods:
+                    continue
+
+                # 处理整体统计
+                overall = chat_stats.get("overall", {})
+                total_records = overall.get("total_records", 0)
+                avg_step_times = overall.get("avg_step_times", {})
+                
+                # 计算决策时间和动作时间
+                action_time = avg_step_times.get("执行动作", 0)
+                total_time = overall.get("avg_total_time", 0)
+                decision_time = max(0, total_time - action_time)
+
+                for period_key in applicable_periods:
+                    stats[period_key][HFC_TOTAL_CYCLES] += total_records
+                    stats[period_key][HFC_CYCLES_BY_CHAT][chat_id] += total_records
+                    stats[period_key][HFC_CYCLES_BY_VERSION][version] += total_records
+
+                # 处理按动作类型的统计
+                by_action = chat_stats.get("by_action", {})
+                for action_type, action_data in by_action.items():
+                    count = action_data.get("count", 0)
+                    action_step_times = action_data.get("avg_step_times", {})
+                    action_total_time = action_data.get("avg_total_time", 0)
+                    
+                    # 计算该动作类型的决策时间和动作时间
+                    action_exec_time = action_step_times.get("执行动作", 0)
+                    action_decision_time = max(0, action_total_time - action_exec_time)
+
+                    for period_key in applicable_periods:
+                        stats[period_key][HFC_CYCLES_BY_ACTION][action_type] += count
+                        
+                        # 群聊×动作交叉统计
+                        stats[period_key][HFC_ACTIONS_BY_CHAT][chat_id][action_type] += count
+                        
+                        # 累加时间统计（用于后续计算加权平均）
+                        # 这里我们需要重新设计数据结构来存储累计值
+                        if chat_id not in stats[period_key][HFC_AVG_TIME_BY_CHAT]:
+                            stats[period_key][HFC_AVG_TIME_BY_CHAT][chat_id] = {"decision": 0, "action": 0, "total": 0, "count": 0}
+                        if action_type not in stats[period_key][HFC_AVG_TIME_BY_ACTION]:
+                            stats[period_key][HFC_AVG_TIME_BY_ACTION][action_type] = {"decision": 0, "action": 0, "total": 0, "count": 0}
+                        if version not in stats[period_key][HFC_AVG_TIME_BY_VERSION]:
+                            stats[period_key][HFC_AVG_TIME_BY_VERSION][version] = {"decision": 0, "action": 0, "total": 0, "count": 0}
+
+                        # 累加加权值（时间*数量）
+                        stats[period_key][HFC_AVG_TIME_BY_CHAT][chat_id]["decision"] += decision_time * total_records
+                        stats[period_key][HFC_AVG_TIME_BY_CHAT][chat_id]["action"] += action_time * total_records
+                        stats[period_key][HFC_AVG_TIME_BY_CHAT][chat_id]["total"] += total_time * total_records
+                        stats[period_key][HFC_AVG_TIME_BY_CHAT][chat_id]["count"] += total_records
+
+                        stats[period_key][HFC_AVG_TIME_BY_ACTION][action_type]["decision"] += action_decision_time * count
+                        stats[period_key][HFC_AVG_TIME_BY_ACTION][action_type]["action"] += action_exec_time * count
+                        stats[period_key][HFC_AVG_TIME_BY_ACTION][action_type]["total"] += action_total_time * count
+                        stats[period_key][HFC_AVG_TIME_BY_ACTION][action_type]["count"] += count
+
+                        stats[period_key][HFC_AVG_TIME_BY_VERSION][version]["decision"] += decision_time * total_records
+                        stats[period_key][HFC_AVG_TIME_BY_VERSION][version]["action"] += action_time * total_records
+                        stats[period_key][HFC_AVG_TIME_BY_VERSION][version]["total"] += total_time * total_records
+                        stats[period_key][HFC_AVG_TIME_BY_VERSION][version]["count"] += total_records
+
+        except Exception as e:
+            logger.error(f"收集HFC统计数据失败: {e}")
+
+        # 计算加权平均时间
+        for period_key in stats:
+            for stat_type in [HFC_AVG_TIME_BY_CHAT, HFC_AVG_TIME_BY_ACTION, HFC_AVG_TIME_BY_VERSION]:
+                for key, time_data in stats[period_key][stat_type].items():
+                    if time_data.get("count", 0) > 0:
+                        count = time_data["count"]
+                        stats[period_key][stat_type][key] = {
+                            "decision": time_data["decision"] / count,
+                            "action": time_data["action"] / count,
+                            "total": time_data["total"] / count
+                        }
+                    else:
+                        stats[period_key][stat_type][key] = {"decision": 0, "action": 0, "total": 0}
+        
+        return stats
+
     def _collect_all_statistics(self, now: datetime) -> Dict[str, Dict[str, Any]]:
         """
         收集各时间段的统计数据
@@ -483,20 +634,58 @@ class StatisticOutputTask(AsyncTask):
         online_time_stat = self._collect_online_time_for_period(stat_start_timestamp, now)
         message_count_stat = self._collect_message_count_for_period(stat_start_timestamp)
 
+        # HFC统计数据收集
+        hfc_stat = self._collect_hfc_data_for_period(stat_start_timestamp)
+
         # 统计数据合并
-        # 合并三类统计数据
+        # 合并四类统计数据
         for period_key, _ in stat_start_timestamp:
             stat[period_key].update(model_req_stat[period_key])
             stat[period_key].update(online_time_stat[period_key])
             stat[period_key].update(message_count_stat[period_key])
+            stat[period_key].update(hfc_stat[period_key])
 
         if last_all_time_stat:
             # 若存在上次完整统计数据，则将其与当前统计数据合并
             for key, val in last_all_time_stat.items():
+                # 跳过已删除的SUCCESS_RATE相关key
+                if key in ["hfc_success_rate_by_chat", "hfc_success_rate_by_action", "hfc_success_rate_by_version"]:
+                    continue
+                
+                # 确保当前统计数据中存在该key
+                if key not in stat["all_time"]:
+                    continue
+                
                 if isinstance(val, dict):
                     # 是字典类型，则进行合并
                     for sub_key, sub_val in val.items():
+                        # 检查是否是HFC的嵌套字典时间数据
+                        if key in [HFC_AVG_TIME_BY_CHAT, HFC_AVG_TIME_BY_ACTION, HFC_AVG_TIME_BY_VERSION] and isinstance(sub_val, dict):
+                            # 对于HFC时间数据，需要特殊处理
+                            if sub_key not in stat["all_time"][key]:
+                                stat["all_time"][key][sub_key] = {"decision": 0, "action": 0, "total": 0}
+                            
+                            # 合并嵌套的时间数据
+                            for time_type, time_val in sub_val.items():
+                                if time_type in stat["all_time"][key][sub_key]:
+                                    stat["all_time"][key][sub_key][time_type] += time_val
+                        elif key == HFC_ACTIONS_BY_CHAT and isinstance(sub_val, dict):
+                            # 对于群聊×动作交叉统计的二层嵌套字典，需要特殊处理
+                            if sub_key not in stat["all_time"][key]:
+                                stat["all_time"][key][sub_key] = {}
+                            
+                            # 合并二层嵌套的动作数据
+                            for action_type, action_count in sub_val.items():
+                                if action_type in stat["all_time"][key][sub_key]:
+                                    stat["all_time"][key][sub_key][action_type] += action_count
+                                else:
+                                    stat["all_time"][key][sub_key][action_type] = action_count
+                        else:
+                            # 普通的数值或字典合并
+                            if sub_key in stat["all_time"][key]:
                                 stat["all_time"][key][sub_key] += sub_val
+                            else:
+                                stat["all_time"][key][sub_key] = sub_val
                 else:
                     # 直接合并
                     stat["all_time"][key] += val
@@ -580,6 +769,8 @@ class StatisticOutputTask(AsyncTask):
         ]
         # 添加图表选项卡
         tab_list.append('<button class="tab-link" onclick="showTab(event, \'charts\')">数据图表</button>')
+        # 添加HFC统计选项卡
+        tab_list.append('<button class="tab-link" onclick="showTab(event, \'hfc_stats\')">HFC统计</button>')
 
         def _format_stat_data(stat_data: dict[str, Any], div_id: str, start_time: datetime) -> str:
             """
@@ -706,6 +897,9 @@ class StatisticOutputTask(AsyncTask):
         chart_data = self._generate_chart_data(stat)
         tab_content_list.append(self._generate_chart_tab(chart_data))
         
+        # 添加HFC统计内容
+        tab_content_list.append(self._generate_hfc_stats_tab(stat))
+
         joined_tab_list = "\n".join(tab_list)
         joined_tab_content = "\n".join(tab_content_list)
 
@@ -953,6 +1147,208 @@ class StatisticOutputTask(AsyncTask):
             "message_by_chat": message_by_chat,
         }
 
+    def _generate_hfc_stats_tab(self, stat: dict[str, Any]) -> str:
+        """生成HFC统计选项卡HTML内容"""
+        
+        def _get_chat_display_name(chat_id):
+            """获取聊天显示名称"""
+            if chat_id in self.name_mapping:
+                return self.name_mapping[chat_id][0]
+            else:
+                return chat_id
+        
+        def _generate_overview_section(data, title):
+            """生成总览部分"""
+            total_cycles = data.get(HFC_TOTAL_CYCLES, 0)
+            if total_cycles == 0:
+                return f"<h3>{title}</h3><p>暂无HFC数据</p>"
+            
+            def _generate_chat_action_table(actions_by_chat):
+                """生成群聊×动作选择率表格"""
+                if not actions_by_chat:
+                    return "<h4>按群聊的动作选择率</h4><p>暂无数据</p>"
+                
+                # 获取所有动作类型
+                all_actions = set()
+                for chat_actions in actions_by_chat.values():
+                    all_actions.update(chat_actions.keys())
+                
+                if not all_actions:
+                    return "<h4>按群聊的动作选择率</h4><p>暂无数据</p>"
+                
+                all_actions = sorted(all_actions)
+                
+                # 生成表头
+                action_headers = ""
+                for action in all_actions:
+                    action_display = action
+                    if action == "no_reply":
+                        action_display = "不回复"
+                    action_headers += f"<th>{action_display}</th>"
+                
+                # 生成表格行
+                table_rows = ""
+                for chat_id in sorted(actions_by_chat.keys()):
+                    chat_actions = actions_by_chat[chat_id]
+                    chat_total = sum(chat_actions.values())
+                    
+                    if chat_total == 0:
+                        continue
+                        
+                    chat_display_name = _get_chat_display_name(chat_id)
+                    table_rows += f"<tr><td>{chat_display_name}</td>"
+                    
+                    # 为每个动作生成百分比
+                    for action in all_actions:
+                        count = chat_actions.get(action, 0)
+                        percentage = (count / chat_total * 100) if chat_total > 0 else 0
+                        table_rows += f"<td>{count} ({percentage:.1f}%)</td>"
+                    
+                    table_rows += f"<td>{chat_total}</td></tr>"
+                
+                return f"""
+                <h4>按群聊的动作选择率</h4>
+                <table>
+                    <thead>
+                        <tr><th>群聊名称</th>{action_headers}<th>总计</th></tr>
+                    </thead>
+                    <tbody>
+                        {table_rows}
+                    </tbody>
+                </table>
+                <p class="info-item"><strong>说明：</strong>显示每个群聊中不同动作类型的选择次数及占比。</p>
+                """
+            
+            cycles_by_chat = data.get(HFC_CYCLES_BY_CHAT, {})
+            cycles_by_action = data.get(HFC_CYCLES_BY_ACTION, {})
+            cycles_by_version = data.get(HFC_CYCLES_BY_VERSION, {})
+            avg_time_by_chat = data.get(HFC_AVG_TIME_BY_CHAT, {})
+            avg_time_by_action = data.get(HFC_AVG_TIME_BY_ACTION, {})
+            avg_time_by_version = data.get(HFC_AVG_TIME_BY_VERSION, {})
+            actions_by_chat = data.get(HFC_ACTIONS_BY_CHAT, {})
+            
+            # 按群聊统计表格
+            chat_rows = ""
+            for chat_id in sorted(cycles_by_chat.keys()):
+                cycles = cycles_by_chat[chat_id]
+                time_data = avg_time_by_chat.get(chat_id, {"decision": 0, "action": 0, "total": 0})
+                decision_time = time_data.get("decision", 0)
+                action_time = time_data.get("action", 0)
+                total_time = time_data.get("total", 0)
+                chat_display_name = _get_chat_display_name(chat_id)
+                chat_rows += f"""
+                <tr>
+                    <td>{chat_display_name}</td>
+                    <td>{cycles}</td>
+                    <td>{decision_time:.2f}s</td>
+                    <td>{action_time:.2f}s</td>
+                    <td>{total_time:.2f}s</td>
+                </tr>"""
+            
+            # 按动作类型统计表格 - 添加说明
+            action_rows = ""
+            for action_type in sorted(cycles_by_action.keys()):
+                cycles = cycles_by_action[action_type]
+                time_data = avg_time_by_action.get(action_type, {"decision": 0, "action": 0, "total": 0})
+                decision_time = time_data.get("decision", 0)
+                action_time = time_data.get("action", 0)
+                total_time = time_data.get("total", 0)
+                # 为no_reply添加说明
+                action_display = action_type
+                if action_type == "no_reply":
+                    action_display = f"{action_type} (不回复决策)"
+                action_rows += f"""
+                <tr>
+                    <td>{action_display}</td>
+                    <td>{cycles}</td>
+                    <td>{decision_time:.2f}s</td>
+                    <td>{action_time:.2f}s</td>
+                    <td>{total_time:.2f}s</td>
+                </tr>"""
+            
+            # 按版本统计表格
+            version_rows = ""
+            for version in sorted(cycles_by_version.keys()):
+                cycles = cycles_by_version[version]
+                time_data = avg_time_by_version.get(version, {"decision": 0, "action": 0, "total": 0})
+                decision_time = time_data.get("decision", 0)
+                action_time = time_data.get("action", 0)
+                total_time = time_data.get("total", 0)
+                version_rows += f"""
+                <tr>
+                    <td>{version}</td>
+                    <td>{cycles}</td>
+                    <td>{decision_time:.2f}s</td>
+                    <td>{action_time:.2f}s</td>
+                    <td>{total_time:.2f}s</td>
+                </tr>"""
+            
+            return f"""
+            <h3>{title} (总循环数: {total_cycles})</h3>
+            
+            <h4>按群聊统计</h4>
+            <table>
+                <thead>
+                    <tr><th>群聊名称</th><th>循环次数</th><th>决策时间</th><th>动作时间</th><th>总时间</th></tr>
+                </thead>
+                <tbody>
+                    {chat_rows}
+                </tbody>
+            </table>
+            
+            <h4>按动作类型统计</h4>
+            <table>
+                <thead>
+                    <tr><th>动作类型</th><th>循环次数</th><th>决策时间</th><th>动作时间</th><th>总时间</th></tr>
+                </thead>
+                <tbody>
+                    {action_rows}
+                </tbody>
+            </table>
+            <p class="info-item"><strong>时间说明：</strong>决策时间包括观察、处理、规划等步骤；动作时间是执行具体动作的时间。</p>
+            
+            <h4>按版本统计</h4>
+            <table>
+                <thead>
+                    <tr><th>版本</th><th>循环次数</th><th>决策时间</th><th>动作时间</th><th>总时间</th></tr>
+                </thead>
+                <tbody>
+                    {version_rows}
+                </tbody>
+            </table>
+            
+            {_generate_chat_action_table(actions_by_chat)}
+            """
+        
+        # 生成指定时间段的统计
+        sections = []
+        
+        # 定义要显示的时间段及其描述（所有时间在最上方）
+        time_periods = [
+            ("all_time", "全部时间"),
+            ("last_24_hours", "最近24小时"),
+            ("last_7_days", "最近7天")
+        ]
+        
+        for period_key, period_desc in time_periods:
+            period_data = stat.get(period_key, {})
+            if period_data.get(HFC_TOTAL_CYCLES, 0) > 0:  # 只显示有数据的时间段
+                sections.append(_generate_overview_section(period_data, period_desc))
+        
+        if not sections:
+            sections.append("<h3>暂无HFC数据</h3><p>系统中还没有HFC循环记录</p>")
+        
+        sections_html = "<br/>".join(sections)
+        
+        return f"""
+        <div id="hfc_stats" class="tab-content">
+            <h2>HFC (Heart Flow Chat) 统计</h2>
+            <p class="info-item"><strong>说明：</strong>此页面显示HFC模块的性能统计信息，包括各群聊、动作类型和版本的详细数据。</p>
+            
+            {sections_html}
+        </div>
+        """
+
     def _generate_chart_tab(self, chart_data: dict) -> str:
         """生成图表选项卡HTML内容"""
 
@@ -1290,6 +1686,9 @@ class AsyncStatisticOutputTask(AsyncTask):
     def _collect_message_count_for_period(self, collect_period: List[Tuple[str, datetime]]) -> Dict[str, Any]:
         return StatisticOutputTask._collect_message_count_for_period(self, collect_period)
     
+    def _collect_hfc_data_for_period(self, collect_period: List[Tuple[str, datetime]]) -> Dict[str, Any]:
+        return StatisticOutputTask._collect_hfc_data_for_period(self, collect_period)
+
     @staticmethod
     def _format_total_stat(stats: Dict[str, Any]) -> str:
         return StatisticOutputTask._format_total_stat(stats)
@@ -1309,3 +1708,6 @@ class AsyncStatisticOutputTask(AsyncTask):
         
     def _generate_chart_tab(self, chart_data: dict) -> str:
         return StatisticOutputTask._generate_chart_tab(self, chart_data)
+    
+    def _generate_hfc_stats_tab(self, stat: dict[str, Any]) -> str:
+        return StatisticOutputTask._generate_hfc_stats_tab(self, stat)