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better：美化logger

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SengokuCola
2025-08-24 15:26:24 +08:00
parent e860b7033a
commit d10e08f15d
9 changed files with 89 additions and 109 deletions
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128
src/chat/utils/statistic.py
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@@ -612,7 +612,7 @@ class StatisticOutputTask(AsyncTask):
f"总在线时间: {_format_online_time(stats[ONLINE_TIME])}",
f"总消息数: {stats[TOTAL_MSG_CNT]}",
f"总请求数: {stats[TOTAL_REQ_CNT]}",
f"总花费: {stats[TOTAL_COST]:.4f}¥",
f"总花费: {stats[TOTAL_COST]:.2f}¥",
"",
]
@@ -625,7 +625,7 @@ class StatisticOutputTask(AsyncTask):
"""
if stats[TOTAL_REQ_CNT] <= 0:
return ""
data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.4f}¥ {:>10} {:>10}"
data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.2f}¥ {:>10.1f} {:>10.1f}"
output = [
"按模型分类统计:",
@@ -723,9 +723,9 @@ class StatisticOutputTask(AsyncTask):
f"<td>{stat_data[IN_TOK_BY_MODEL][model_name]}</td>"
f"<td>{stat_data[OUT_TOK_BY_MODEL][model_name]}</td>"
f"<td>{stat_data[TOTAL_TOK_BY_MODEL][model_name]}</td>"
f"<td>{stat_data[COST_BY_MODEL][model_name]:.4f} ¥</td>"
f"<td>{stat_data[AVG_TIME_COST_BY_MODEL][model_name]:.3f} 秒</td>"
f"<td>{stat_data[STD_TIME_COST_BY_MODEL][model_name]:.3f} 秒</td>"
f"<td>{stat_data[COST_BY_MODEL][model_name]:.2f} ¥</td>"
f"<td>{stat_data[AVG_TIME_COST_BY_MODEL][model_name]:.1f} 秒</td>"
f"<td>{stat_data[STD_TIME_COST_BY_MODEL][model_name]:.1f} 秒</td>"
f"</tr>"
for model_name, count in sorted(stat_data[REQ_CNT_BY_MODEL].items())
]
@@ -739,9 +739,9 @@ class StatisticOutputTask(AsyncTask):
f"<td>{stat_data[IN_TOK_BY_TYPE][req_type]}</td>"
f"<td>{stat_data[OUT_TOK_BY_TYPE][req_type]}</td>"
f"<td>{stat_data[TOTAL_TOK_BY_TYPE][req_type]}</td>"
f"<td>{stat_data[COST_BY_TYPE][req_type]:.4f} ¥</td>"
f"<td>{stat_data[AVG_TIME_COST_BY_TYPE][req_type]:.3f} 秒</td>"
f"<td>{stat_data[STD_TIME_COST_BY_TYPE][req_type]:.3f} 秒</td>"
f"<td>{stat_data[COST_BY_TYPE][req_type]:.2f} ¥</td>"
f"<td>{stat_data[AVG_TIME_COST_BY_TYPE][req_type]:.1f} 秒</td>"
f"<td>{stat_data[STD_TIME_COST_BY_TYPE][req_type]:.1f} 秒</td>"
f"</tr>"
for req_type, count in sorted(stat_data[REQ_CNT_BY_TYPE].items())
]
@@ -755,9 +755,9 @@ class StatisticOutputTask(AsyncTask):
f"<td>{stat_data[IN_TOK_BY_MODULE][module_name]}</td>"
f"<td>{stat_data[OUT_TOK_BY_MODULE][module_name]}</td>"
f"<td>{stat_data[TOTAL_TOK_BY_MODULE][module_name]}</td>"
f"<td>{stat_data[COST_BY_MODULE][module_name]:.4f} ¥</td>"
f"<td>{stat_data[AVG_TIME_COST_BY_MODULE][module_name]:.3f} 秒</td>"
f"<td>{stat_data[STD_TIME_COST_BY_MODULE][module_name]:.3f} 秒</td>"
f"<td>{stat_data[COST_BY_MODULE][module_name]:.2f} ¥</td>"
f"<td>{stat_data[AVG_TIME_COST_BY_MODULE][module_name]:.1f} 秒</td>"
f"<td>{stat_data[STD_TIME_COST_BY_MODULE][module_name]:.1f} 秒</td>"
f"</tr>"
for module_name, count in sorted(stat_data[REQ_CNT_BY_MODULE].items())
]
@@ -780,79 +780,47 @@ class StatisticOutputTask(AsyncTask):
<p class=\"info-item\"><strong>总在线时间: </strong>{_format_online_time(stat_data[ONLINE_TIME])}</p>
<p class=\"info-item\"><strong>总消息数: </strong>{stat_data[TOTAL_MSG_CNT]}</p>
<p class=\"info-item\"><strong>总请求数: </strong>{stat_data[TOTAL_REQ_CNT]}</p>
<p class=\"info-item\"><strong>总花费: </strong>{stat_data[TOTAL_COST]:.4f} ¥</p>
<p class=\"info-item\"><strong>总花费: </strong>{stat_data[TOTAL_COST]:.2f} ¥</p>
<div style="display: flex; flex-wrap: wrap; gap: 20px; margin: 20px 0;">
<div style="flex: 1; min-width: 300px;">
<h2>按模型分类统计</h2>
<table>
<thead><tr><th>模型名称</th><th>调用次数</th><th>输入Token</th><th>输出Token</th><th>Token总量</th><th>累计花费</th><th>平均耗时(秒)</th><th>标准差(秒)</th></tr></thead>
<tbody>
{model_rows}
</tbody>
</table>
</div>
<div style="flex: 1; min-width: 300px;">
<h3>模型调用次数分布</h3>
<canvas id="modelPieChart_{div_id}" width="300" height="300"></canvas>
</div>
</div>
<h2>按模型分类统计</h2>
<table>
<thead><tr><th>模型名称</th><th>调用次数</th><th>输入Token</th><th>输出Token</th><th>Token总量</th><th>累计花费</th><th>平均耗时(秒)</th><th>标准差(秒)</th></tr></thead>
<tbody>
{model_rows}
</tbody>
</table>
<div style="display: flex; flex-wrap: wrap; gap: 20px; margin: 20px 0;">
<div style="flex: 1; min-width: 300px;">
<h2>按模块分类统计</h2>
<table>
<thead>
<tr><th>模块名称</th><th>调用次数</th><th>输入Token</th><th>输出Token</th><th>Token总量</th><th>累计花费</th><th>平均耗时(秒)</th><th>标准差(秒)</th></tr>
</thead>
<tbody>
{module_rows}
</tbody>
</table>
</div>
<div style="flex: 1; min-width: 300px;">
<h3>模块调用次数分布</h3>
<canvas id="modulePieChart_{div_id}" width="300" height="300"></canvas>
</div>
</div>
<h2>按模块分类统计</h2>
<table>
<thead>
<tr><th>模块名称</th><th>调用次数</th><th>输入Token</th><th>输出Token</th><th>Token总量</th><th>累计花费</th><th>平均耗时(秒)</th><th>标准差(秒)</th></tr>
</thead>
<tbody>
{module_rows}
</tbody>
</table>
<div style="display: flex; flex-wrap: wrap; gap: 20px; margin: 20px 0;">
<div style="flex: 1; min-width: 300px;">
<h2>按请求类型分类统计</h2>
<table>
<thead>
<tr><th>请求类型</th><th>调用次数</th><th>输入Token</th><th>输出Token</th><th>Token总量</th><th>累计花费</th><th>平均耗时(秒)</th><th>标准差(秒)</th></tr>
</thead>
<tbody>
{type_rows}
</tbody>
</table>
</div>
<div style="flex: 1; min-width: 300px;">
<h3>请求类型分布</h3>
<canvas id="typePieChart_{div_id}" width="300" height="300"></canvas>
</div>
</div>
<h2>按请求类型分类统计</h2>
<table>
<thead>
<tr><th>请求类型</th><th>调用次数</th><th>输入Token</th><th>输出Token</th><th>Token总量</th><th>累计花费</th><th>平均耗时(秒)</th><th>标准差(秒)</th></tr>
</thead>
<tbody>
{type_rows}
</tbody>
</table>
<div style="display: flex; flex-wrap: wrap; gap: 20px; margin: 20px 0;">
<div style="flex: 1; min-width: 300px;">
<h2>聊天消息统计</h2>
<table>
<thead>
<tr><th>联系人/群组名称</th><th>消息数量</th></tr>
</thead>
<tbody>
{chat_rows}
</tbody>
</table>
</div>
<div style="flex: 1; min-width: 300px;">
<h3>消息分布</h3>
<canvas id="chatPieChart_{div_id}" width="300" height="300"></canvas>
</div>
</div>
<h2>聊天消息统计</h2>
<table>
<thead>
<tr><th>联系人/群组名称</th><th>消息数量</th></tr>
</thead>
<tbody>
{chat_rows}
</tbody>
</table>
<script>
// 为当前统计卡片创建饼图
createPieCharts_{div_id}();
@@ -991,7 +959,7 @@ class StatisticOutputTask(AsyncTask):
}}
}});
}}
</script>
</div>
"""