diff --git a/src/chat/utils/statistic.py b/src/chat/utils/statistic.py index 970746138..3f9832926 100644 --- a/src/chat/utils/statistic.py +++ b/src/chat/utils/statistic.py @@ -69,19 +69,9 @@ class OnlineTimeRecordTask(AsyncTask): else: # 如果没有记录，检查一分钟以内是否已有记录 current_time = datetime.now() - recent_record = db.online_time.find_one( + if recent_record := db.online_time.find_one( {"end_timestamp": {"$gte": current_time - timedelta(minutes=1)}} - ) - - if not recent_record: - # 若没有记录，则插入新的在线时间记录 - self.record_id = db.online_time.insert_one( - { - "start_timestamp": current_time, - "end_timestamp": current_time + timedelta(minutes=1), - } - ).inserted_id - else: + ): # 如果有记录，则更新结束时间 self.record_id = recent_record["_id"] db.online_time.update_one( @@ -92,8 +82,16 @@ class OnlineTimeRecordTask(AsyncTask): } }, ) - except Exception: - logger.exception("在线时间记录失败") + else: + # 若没有记录，则插入新的在线时间记录 + self.record_id = db.online_time.insert_one( + { + "start_timestamp": current_time, + "end_timestamp": current_time + timedelta(minutes=1), + } + ).inserted_id + except Exception as e: + logger.error(f"在线时间记录失败，错误信息：{e}") def _format_online_time(online_seconds: int) -> str: @@ -110,15 +108,13 @@ def _format_online_time(online_seconds: int) -> str: seconds = total_oneline_time.seconds % 60 if days > 0: # 如果在线时间超过1天，则格式化为"X天X小时X分钟" - total_oneline_time_str = f"{total_oneline_time.days}天{hours}小时{minutes}分钟{seconds}秒" + return f"{total_oneline_time.days}天{hours}小时{minutes}分钟{seconds}秒" elif hours > 0: # 如果在线时间超过1小时，则格式化为"X小时X分钟X秒" - total_oneline_time_str = f"{hours}小时{minutes}分钟{seconds}秒" + return f"{hours}小时{minutes}分钟{seconds}秒" else: # 其他情况格式化为"X分钟X秒" - total_oneline_time_str = f"{minutes}分钟{seconds}秒" - - return total_oneline_time_str + return f"{minutes}分钟{seconds}秒" class StatisticOutputTask(AsyncTask): @@ -311,8 +307,7 @@ class StatisticOutputTask(AsyncTask): for idx, (_, period_start) in enumerate(collect_period): if end_timestamp >= period_start: # 由于end_timestamp会超前标记时间，所以我们需要判断是否晚于当前时间，如果是，则使用当前时间作为结束时间 - if end_timestamp > now: - end_timestamp = now + end_timestamp = min(end_timestamp, now) # 如果记录时间在当前时间段内，则它一定在更早的时间段内 # 因此，我们可以直接跳过更早的时间段的判断，直接更新当前以及更早时间段的统计数据 for period_key, _period_start in collect_period[idx:]: @@ -392,12 +387,15 @@ class StatisticOutputTask(AsyncTask): last_all_time_stat = None - if "last_full_statistics_timestamp" in local_storage and "last_full_statistics" in local_storage: - # 若存有上次完整统计的时间戳，则使用该时间戳作为"所有时间"的起始时间，进行增量统计 - last_full_stat_ts: float = local_storage["last_full_statistics_timestamp"] - last_all_time_stat = local_storage["last_full_statistics"] + if "last_full_statistics" in local_storage: + # 如果存在上次完整统计数据，则使用该数据进行增量统计 + last_stat = local_storage["last_full_statistics"] # 上次完整统计数据 + + self.name_mapping = last_stat["name_mapping"] # 上次完整统计数据的名称映射 + last_all_time_stat = last_stat["stat_data"] # 上次完整统计的统计数据 + last_stat_timestamp = datetime.fromtimestamp(last_stat["timestamp"]) # 上次完整统计数据的时间戳 self.stat_period = [item for item in self.stat_period if item[0] != "all_time"] # 删除"所有时间"的统计时段 - self.stat_period.append(("all_time", now - datetime.fromtimestamp(last_full_stat_ts), "自部署以来的")) + self.stat_period.append(("all_time", now - last_stat_timestamp, "自部署以来的")) stat_start_timestamp = [(period[0], now - period[1]) for period in self.stat_period] @@ -426,9 +424,11 @@ class StatisticOutputTask(AsyncTask): stat["all_time"][key] += val # 更新上次完整统计数据的时间戳 - local_storage["last_full_statistics_timestamp"] = now.timestamp() - # 更新上次完整统计数据 - local_storage["last_full_statistics"] = stat["all_time"] + local_storage["last_full_statistics"] = { + "name_mapping": self.name_mapping, + "stat_data": stat["all_time"], + "timestamp": now.timestamp(), + } return stat @@ -455,39 +455,38 @@ class StatisticOutputTask(AsyncTask): """ 格式化按模型分类的统计数据 """ - if stats[TOTAL_REQ_CNT] > 0: - data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.4f}¥" - - output = [ - "按模型分类统计:", - " 模型名称 调用次数 输入Token 输出Token Token总量 累计花费", - ] - for model_name, count in sorted(stats[REQ_CNT_BY_MODEL].items()): - name = model_name[:29] + "..." if len(model_name) > 32 else model_name - in_tokens = stats[IN_TOK_BY_MODEL][model_name] - out_tokens = stats[OUT_TOK_BY_MODEL][model_name] - tokens = stats[TOTAL_TOK_BY_MODEL][model_name] - cost = stats[COST_BY_MODEL][model_name] - output.append(data_fmt.format(name, count, in_tokens, out_tokens, tokens, cost)) - - output.append("") - return "\n".join(output) - else: + if stats[TOTAL_REQ_CNT] <= 0: return "" + data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.4f}¥" + + output = [ + "按模型分类统计:", + " 模型名称 调用次数 输入Token 输出Token Token总量 累计花费", + ] + for model_name, count in sorted(stats[REQ_CNT_BY_MODEL].items()): + name = f"{model_name[:29]}..." if len(model_name) > 32 else model_name + in_tokens = stats[IN_TOK_BY_MODEL][model_name] + out_tokens = stats[OUT_TOK_BY_MODEL][model_name] + tokens = stats[TOTAL_TOK_BY_MODEL][model_name] + cost = stats[COST_BY_MODEL][model_name] + output.append(data_fmt.format(name, count, in_tokens, out_tokens, tokens, cost)) + + output.append("") + return "\n".join(output) def _format_chat_stat(self, stats: Dict[str, Any]) -> str: """ 格式化聊天统计数据 """ - if stats[TOTAL_MSG_CNT] > 0: - output = ["聊天消息统计:", " 联系人/群组名称 消息数量"] - for chat_id, count in sorted(stats[MSG_CNT_BY_CHAT].items()): - output.append(f"{self.name_mapping[chat_id][0][:32]:<32} {count:>10}") - - output.append("") - return "\n".join(output) - else: + if stats[TOTAL_MSG_CNT] <= 0: return "" + output = ["聊天消息统计:", " 联系人/群组名称 消息数量"] + output.extend( + f"{self.name_mapping[chat_id][0][:32]:<32} {count:>10}" + for chat_id, count in sorted(stats[MSG_CNT_BY_CHAT].items()) + ) + output.append("") + return "\n".join(output) def _generate_html_report(self, stat: dict[str, Any], now: datetime): """