From 89ca1651d9318d68095ed3a7d0a30a9a1f27b9da Mon Sep 17 00:00:00 2001 From: minecraft1024a Date: Wed, 12 Nov 2025 21:26:21 +0800 Subject: [PATCH] 1 --- src/chat/utils/report_generator.py | 63 ++++++++++++++--- src/chat/utils/statistic.py | 109 ++++++++++++++++++++++++----- src/chat/utils/statistic_keys.py | 21 +++++- 3 files changed, 164 insertions(+), 29 deletions(-) diff --git a/src/chat/utils/report_generator.py b/src/chat/utils/report_generator.py index 59467efaa..5be2fd19a 100644 --- a/src/chat/utils/report_generator.py +++ b/src/chat/utils/report_generator.py @@ -65,16 +65,30 @@ class HTMLReportGenerator: f"" f"{model_name}" f"{count}" - f"{stat_data[IN_TOK_BY_MODEL].get(model_name, 0)}" - f"{stat_data[OUT_TOK_BY_MODEL].get(model_name, 0)}" + f"{stat_data[AVG_TOK_BY_MODEL].get(model_name, 0)}" f"{stat_data[TOTAL_TOK_BY_MODEL].get(model_name, 0)}" + f"{stat_data[TPS_BY_MODEL].get(model_name, 0):.2f}" + f"{stat_data[COST_PER_KTOK_BY_MODEL].get(model_name, 0):.4f} ¥" f"{stat_data[COST_BY_MODEL].get(model_name, 0):.4f} ¥" f"{stat_data[AVG_TIME_COST_BY_MODEL].get(model_name, 0):.3f} 秒" - f"{stat_data[STD_TIME_COST_BY_MODEL].get(model_name, 0):.3f} 秒" f"" for model_name, count in sorted(stat_data[REQ_CNT_BY_MODEL].items()) ] ) + # 按供应商分类统计 + provider_rows = "\n".join( + [ + f"" + f"{provider_name}" + f"{count}" + f"{stat_data[TOTAL_TOK_BY_PROVIDER].get(provider_name, 0)}" + f"{stat_data[TPS_BY_PROVIDER].get(provider_name, 0):.2f}" + f"{stat_data[COST_PER_KTOK_BY_PROVIDER].get(provider_name, 0):.4f} ¥" + f"{stat_data[COST_BY_PROVIDER].get(provider_name, 0):.4f} ¥" + f"" + for provider_name, count in sorted(stat_data[REQ_CNT_BY_PROVIDER].items()) + ] + ) # 按请求类型分类统计 type_rows = "\n".join( [ @@ -114,23 +128,55 @@ class HTMLReportGenerator: for chat_id, count in sorted(stat_data[MSG_CNT_BY_CHAT].items()) ] ) + summary_cards = f""" +
+
+

总花费

+

{stat_data.get(TOTAL_COST, 0):.4f} ¥

+
+
+

总请求数

+

{stat_data.get(TOTAL_REQ_CNT, 0)}

+
+
+

总Token数

+

{sum(stat_data.get(TOTAL_TOK_BY_MODEL, {}).values())}

+
+
+

总消息数

+

{stat_data.get(TOTAL_MSG_CNT, 0)}

+
+
+

总在线时间

+

{format_online_time(int(stat_data.get(ONLINE_TIME, 0)))}

+
+
+ """ + + # 增加饼图和条形图 + # static_charts = self._generate_static_charts_div(stat_data, div_id) # 该功能尚未实现 + static_charts = "" return f"""

统计时段: {start_time.strftime("%Y-%m-%d %H:%M:%S")} ~ {now.strftime("%Y-%m-%d %H:%M:%S")}

-

总在线时间: {format_online_time(int(stat_data.get(ONLINE_TIME, 0)))}

-

总消息数: {stat_data.get(TOTAL_MSG_CNT, 0)}

-

总请求数: {stat_data.get(TOTAL_REQ_CNT, 0)}

-

总花费: {stat_data.get(TOTAL_COST, 0):.4f} ¥

+ {summary_cards} + {static_charts}

按模型分类统计

- + {model_rows}
模型名称调用次数输入Token输出TokenToken总量累计花费平均耗时(秒)标准差(秒)
模型名称调用次数平均Token数Token总量TPS每K Token成本累计花费平均耗时(秒)
+

按供应商分类统计

+ + + {provider_rows} +
供应商名称调用次数Token总量TPS每K Token成本累计花费
+

按模块分类统计

@@ -156,7 +202,6 @@ class HTMLReportGenerator:
""" - def _generate_chart_tab(self, chart_data: dict) -> str: """生成图表选项卡的HTML内容。""" return f""" diff --git a/src/chat/utils/statistic.py b/src/chat/utils/statistic.py index 8043450d9..08d2ed8be 100644 --- a/src/chat/utils/statistic.py +++ b/src/chat/utils/statistic.py @@ -246,6 +246,7 @@ class StatisticOutputTask(AsyncTask): REQ_CNT_BY_USER: defaultdict(int), REQ_CNT_BY_MODEL: defaultdict(int), REQ_CNT_BY_MODULE: defaultdict(int), + REQ_CNT_BY_PROVIDER: defaultdict(int), # New IN_TOK_BY_TYPE: defaultdict(int), IN_TOK_BY_USER: defaultdict(int), IN_TOK_BY_MODEL: defaultdict(int), @@ -258,15 +259,18 @@ class StatisticOutputTask(AsyncTask): TOTAL_TOK_BY_USER: defaultdict(int), TOTAL_TOK_BY_MODEL: defaultdict(int), TOTAL_TOK_BY_MODULE: defaultdict(int), + TOTAL_TOK_BY_PROVIDER: defaultdict(int), # New TOTAL_COST: 0.0, COST_BY_TYPE: defaultdict(float), COST_BY_USER: defaultdict(float), COST_BY_MODEL: defaultdict(float), COST_BY_MODULE: defaultdict(float), + COST_BY_PROVIDER: defaultdict(float), # New TIME_COST_BY_TYPE: defaultdict(list), TIME_COST_BY_USER: defaultdict(list), TIME_COST_BY_MODEL: defaultdict(list), TIME_COST_BY_MODULE: defaultdict(list), + TIME_COST_BY_PROVIDER: defaultdict(list), # New AVG_TIME_COST_BY_TYPE: defaultdict(float), AVG_TIME_COST_BY_USER: defaultdict(float), AVG_TIME_COST_BY_MODEL: defaultdict(float), @@ -275,6 +279,17 @@ class StatisticOutputTask(AsyncTask): STD_TIME_COST_BY_USER: defaultdict(float), STD_TIME_COST_BY_MODEL: defaultdict(float), STD_TIME_COST_BY_MODULE: defaultdict(float), + # New calculated fields + TPS_BY_MODEL: defaultdict(float), + COST_PER_KTOK_BY_MODEL: defaultdict(float), + AVG_TOK_BY_MODEL: defaultdict(float), + TPS_BY_PROVIDER: defaultdict(float), + COST_PER_KTOK_BY_PROVIDER: defaultdict(float), + # Chart data + PIE_CHART_COST_BY_PROVIDER: {}, + PIE_CHART_REQ_BY_PROVIDER: {}, + BAR_CHART_COST_BY_MODEL: {}, + BAR_CHART_REQ_BY_MODEL: {}, } for period_key, _ in collect_period } @@ -309,6 +324,7 @@ class StatisticOutputTask(AsyncTask): request_type = record.get("request_type") or "unknown" user_id = record.get("user_id") or "unknown" model_name = record.get("model_name") or "unknown" + provider_name = record.get("model_api_provider") or "unknown" # 提取模块名：如果请求类型包含"."，取第一个"."之前的部分 module_name = request_type.split(".")[0] if "." in request_type else request_type @@ -317,6 +333,7 @@ class StatisticOutputTask(AsyncTask): stats[period_key][REQ_CNT_BY_USER][user_id] += 1 stats[period_key][REQ_CNT_BY_MODEL][model_name] += 1 stats[period_key][REQ_CNT_BY_MODULE][module_name] += 1 + stats[period_key][REQ_CNT_BY_PROVIDER][provider_name] += 1 prompt_tokens = record.get("prompt_tokens") or 0 completion_tokens = record.get("completion_tokens") or 0 @@ -336,6 +353,7 @@ class StatisticOutputTask(AsyncTask): stats[period_key][TOTAL_TOK_BY_USER][user_id] += total_tokens stats[period_key][TOTAL_TOK_BY_MODEL][model_name] += total_tokens stats[period_key][TOTAL_TOK_BY_MODULE][module_name] += total_tokens + stats[period_key][TOTAL_TOK_BY_PROVIDER][provider_name] += total_tokens cost = record.get("cost") or 0.0 stats[period_key][TOTAL_COST] += cost @@ -343,6 +361,7 @@ class StatisticOutputTask(AsyncTask): stats[period_key][COST_BY_USER][user_id] += cost stats[period_key][COST_BY_MODEL][model_name] += cost stats[period_key][COST_BY_MODULE][module_name] += cost + stats[period_key][COST_BY_PROVIDER][provider_name] += cost # 收集time_cost数据 time_cost = record.get("time_cost") or 0.0 @@ -351,32 +370,84 @@ class StatisticOutputTask(AsyncTask): stats[period_key][TIME_COST_BY_USER][user_id].append(time_cost) stats[period_key][TIME_COST_BY_MODEL][model_name].append(time_cost) stats[period_key][TIME_COST_BY_MODULE][module_name].append(time_cost) + stats[period_key][TIME_COST_BY_PROVIDER][provider_name].append(time_cost) break - # 计算平均耗时和标准差 - for period_key in stats: - for category in [REQ_CNT_BY_TYPE, REQ_CNT_BY_USER, REQ_CNT_BY_MODEL, REQ_CNT_BY_MODULE]: - time_cost_key = f"time_costs_by_{category.split('_')[-1]}" - avg_key = f"avg_time_costs_by_{category.split('_')[-1]}" - std_key = f"std_time_costs_by_{category.split('_')[-1]}" + # -- 计算派生指标 -- + for period_key, period_stats in stats.items(): + # 计算模型相关指标 + for model_name, req_count in period_stats[REQ_CNT_BY_MODEL].items(): + total_tok = period_stats[TOTAL_TOK_BY_MODEL].get(model_name, 0) + total_cost = period_stats[COST_BY_MODEL].get(model_name, 0.0) + time_costs = period_stats[TIME_COST_BY_MODEL].get(model_name, []) + total_time_cost = sum(time_costs) - for item_name in stats[period_key][category]: - time_costs = stats[period_key][time_cost_key].get(item_name, []) + # TPS + if total_time_cost > 0: + period_stats[TPS_BY_MODEL][model_name] = round(total_tok / total_time_cost, 2) + # Cost per 1K Tokens + if total_tok > 0: + period_stats[COST_PER_KTOK_BY_MODEL][model_name] = round((total_cost / total_tok) * 1000, 4) + # Avg Tokens per Request + period_stats[AVG_TOK_BY_MODEL][model_name] = round(total_tok / req_count) if req_count > 0 else 0 + + # 计算供应商相关指标 + for provider_name, req_count in period_stats[REQ_CNT_BY_PROVIDER].items(): + total_tok = period_stats[TOTAL_TOK_BY_PROVIDER].get(provider_name, 0) + total_cost = period_stats[COST_BY_PROVIDER].get(provider_name, 0.0) + time_costs = period_stats[TIME_COST_BY_PROVIDER].get(provider_name, []) + total_time_cost = sum(time_costs) + + # TPS + if total_time_cost > 0: + period_stats[TPS_BY_PROVIDER][provider_name] = round(total_tok / total_time_cost, 2) + # Cost per 1K Tokens + if total_tok > 0: + period_stats[COST_PER_KTOK_BY_PROVIDER][provider_name] = round((total_cost / total_tok) * 1000, 4) + + # 计算平均耗时和标准差 + for category_key, items in [ + (REQ_CNT_BY_TYPE, "type"), + (REQ_CNT_BY_USER, "user"), + (REQ_CNT_BY_MODEL, "model"), + (REQ_CNT_BY_MODULE, "module"), + ]: + time_cost_key = f"time_costs_by_{items}" + avg_key = f"avg_time_costs_by_{items}" + std_key = f"std_time_costs_by_{items}" + + for item_name in period_stats[category_key]: + time_costs = period_stats[time_cost_key].get(item_name, []) if time_costs: - # 计算平均耗时 - avg_time_cost = sum(time_costs) / len(time_costs) - stats[period_key][avg_key][item_name] = round(avg_time_cost, 3) - - # 计算标准差 + avg_time = sum(time_costs) / len(time_costs) + period_stats[avg_key][item_name] = round(avg_time, 3) if len(time_costs) > 1: - variance = sum((x - avg_time_cost) ** 2 for x in time_costs) / len(time_costs) - std_time_cost = variance**0.5 - stats[period_key][std_key][item_name] = round(std_time_cost, 3) + variance = sum((x - avg_time) ** 2 for x in time_costs) / len(time_costs) + period_stats[std_key][item_name] = round(variance**0.5, 3) else: - stats[period_key][std_key][item_name] = 0.0 + period_stats[std_key][item_name] = 0.0 else: - stats[period_key][avg_key][item_name] = 0.0 - stats[period_key][std_key][item_name] = 0.0 + period_stats[avg_key][item_name] = 0.0 + period_stats[std_key][item_name] = 0.0 + + # 准备图表数据 + # 按供应商花费饼图 + provider_costs = period_stats[COST_BY_PROVIDER] + if provider_costs: + sorted_providers = sorted(provider_costs.items(), key=lambda item: item[1], reverse=True) + period_stats[PIE_CHART_COST_BY_PROVIDER] = { + "labels": [item[0] for item in sorted_providers], + "data": [round(item[1], 4) for item in sorted_providers], + } + + # 按模型花费条形图 + model_costs = period_stats[COST_BY_MODEL] + if model_costs: + sorted_models = sorted(model_costs.items(), key=lambda item: item[1], reverse=True) + period_stats[BAR_CHART_COST_BY_MODEL] = { + "labels": [item[0] for item in sorted_models], + "data": [round(item[1], 4) for item in sorted_models], + } return stats @staticmethod diff --git a/src/chat/utils/statistic_keys.py b/src/chat/utils/statistic_keys.py index 41e96b1be..f7c91780c 100644 --- a/src/chat/utils/statistic_keys.py +++ b/src/chat/utils/statistic_keys.py @@ -40,4 +40,23 @@ AVG_TIME_COST_BY_MODULE = "avg_time_costs_by_module" STD_TIME_COST_BY_TYPE = "std_time_costs_by_type" STD_TIME_COST_BY_USER = "std_time_costs_by_user" STD_TIME_COST_BY_MODEL = "std_time_costs_by_model" -STD_TIME_COST_BY_MODULE = "std_time_costs_by_module" \ No newline at end of file +STD_TIME_COST_BY_MODULE = "std_time_costs_by_module" + +# 新增模型性能指标 +TPS_BY_MODEL = "tps_by_model" # Tokens Per Second +COST_PER_KTOK_BY_MODEL = "cost_per_ktok_by_model" +AVG_TOK_BY_MODEL = "avg_tok_by_model" + +# 新增按供应商统计 +REQ_CNT_BY_PROVIDER = "requests_by_provider" +COST_BY_PROVIDER = "costs_by_provider" +TOTAL_TOK_BY_PROVIDER = "tokens_by_provider" +TPS_BY_PROVIDER = "tps_by_provider" +COST_PER_KTOK_BY_PROVIDER = "cost_per_ktok_by_provider" +TIME_COST_BY_PROVIDER = "time_cost_by_provider" + +# 新增饼图和条形图数据 +PIE_CHART_COST_BY_PROVIDER = "pie_chart_cost_by_provider" +PIE_CHART_REQ_BY_PROVIDER = "pie_chart_req_by_provider" +BAR_CHART_COST_BY_MODEL = "bar_chart_cost_by_model" +BAR_CHART_REQ_BY_MODEL = "bar_chart_req_by_model" \ No newline at end of file