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better：优化记忆提取能力

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SengokuCola
2025-11-11 23:57:47 +08:00
parent 82a87f4926
commit 2d6eba7da1
3 changed files with 185 additions and 122 deletions
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4
src/chat/frequency_control/frequency_control.py
View File

@@ -112,10 +112,10 @@ class FrequencyControl:
if len(response) < 20:
if "过于频繁" in response:
logger.info(f"频率调整: 过于频繁，调整值到{final_value_by_api}")
self.talk_frequency_adjust = max(0.1, min(3.0, self.talk_frequency_adjust * 0.8))
self.talk_frequency_adjust = max(0.1, min(1.5, self.talk_frequency_adjust * 0.8))
elif "过少" in response:
logger.info(f"频率调整: 过少，调整值到{final_value_by_api}")
self.talk_frequency_adjust = max(0.1, min(3.0, self.talk_frequency_adjust * 1.2))
self.talk_frequency_adjust = max(0.1, min(1.5, self.talk_frequency_adjust * 1.2))
self.last_frequency_adjust_time = time.time()
else:
logger.info(f"频率调整：response不符合要求，取消本次调整")

75
src/chat/utils/statistic.py
View File

@@ -690,9 +690,6 @@ class StatisticOutputTask(AsyncTask):
online_hours = stats[ONLINE_TIME] / 3600.0 if stats[ONLINE_TIME] > 0 else 0.0
cost_per_hour = stats[TOTAL_COST] / online_hours if online_hours > 0 else 0.0
# 计算token/消息数量指标（每100条）
tokens_per_100_messages = (total_tokens / stats[TOTAL_MSG_CNT] * 100) if stats[TOTAL_MSG_CNT] > 0 else 0.0
# 计算token/时间指标（token/小时）
tokens_per_hour = (total_tokens / online_hours) if online_hours > 0 else 0.0
@@ -700,8 +697,9 @@ class StatisticOutputTask(AsyncTask):
total_replies = stats.get(TOTAL_REPLY_CNT, 0)
cost_per_100_replies = (stats[TOTAL_COST] / total_replies * 100) if total_replies > 0 else 0.0
# 计算token/回复数量指标（每100条）
tokens_per_100_replies = (total_tokens / total_replies * 100) if total_replies > 0 else 0.0
# 计算花费/消息数量（排除自己回复）指标（每100条）
total_messages_excluding_replies = stats[TOTAL_MSG_CNT] - total_replies
cost_per_100_messages_excluding_replies = (stats[TOTAL_COST] / total_messages_excluding_replies * 100) if total_messages_excluding_replies > 0 else 0.0
output = [
f"总在线时间: {_format_online_time(stats[ONLINE_TIME])}",
@@ -711,10 +709,9 @@ class StatisticOutputTask(AsyncTask):
f"总Token数: {_format_large_number(total_tokens)}",
f"总花费: {stats[TOTAL_COST]:.2f}¥",
f"花费/消息数量: {cost_per_100_messages:.4f}¥/100条" if stats[TOTAL_MSG_CNT] > 0 else "花费/消息数量: N/A",
f"花费/回复数量: {cost_per_100_replies:.4f}¥/100条" if total_replies > 0 else "花费/回复数量: N/A",
f"花费/接受消息数量: {cost_per_100_messages_excluding_replies:.4f}¥/100条" if total_messages_excluding_replies > 0 else "花费/消息数量(排除回复): N/A",
f"花费/回复消息数量: {cost_per_100_replies:.4f}¥/100条" if total_replies > 0 else "花费/回复数量: N/A",
f"花费/时间: {cost_per_hour:.2f}¥/小时" if online_hours > 0 else "花费/时间: N/A",
f"Token/消息数量: {_format_large_number(tokens_per_100_messages)}/100条" if stats[TOTAL_MSG_CNT] > 0 else "Token/消息数量: N/A",
f"Token/回复数量: {_format_large_number(tokens_per_100_replies)}/100条" if total_replies > 0 else "Token/回复数量: N/A",
f"Token/时间: {_format_large_number(tokens_per_hour)}/小时" if online_hours > 0 else "Token/时间: N/A",
"",
]
@@ -933,25 +930,21 @@ class StatisticOutputTask(AsyncTask):
<div class=\"kpi-value\">{(stat_data[TOTAL_COST] / stat_data[TOTAL_MSG_CNT] * 100 if stat_data[TOTAL_MSG_CNT] > 0 else 0.0):.4f} ¥/100条</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">花费/时间</div>
<div class=\"kpi-value\">{(stat_data[TOTAL_COST] / (stat_data[ONLINE_TIME] / 3600.0) if stat_data[ONLINE_TIME] > 0 else 0.0):.2f} ¥/小时</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">Token/消息数量</div>
<div class=\"kpi-value\">{_format_large_number(sum(stat_data[TOTAL_TOK_BY_MODEL].values()) / stat_data[TOTAL_MSG_CNT] * 100 if stat_data[TOTAL_MSG_CNT] > 0 and stat_data[TOTAL_TOK_BY_MODEL] else 0.0, html=True)}/100条</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">Token/回复数量</div>
<div class=\"kpi-value\">{_format_large_number(sum(stat_data[TOTAL_TOK_BY_MODEL].values()) / stat_data.get(TOTAL_REPLY_CNT, 0) * 100 if stat_data.get(TOTAL_REPLY_CNT, 0) > 0 and stat_data[TOTAL_TOK_BY_MODEL] else 0.0, html=True)}/100条</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">Token/时间</div>
<div class=\"kpi-value\">{_format_large_number(sum(stat_data[TOTAL_TOK_BY_MODEL].values()) / (stat_data[ONLINE_TIME] / 3600.0) if stat_data[ONLINE_TIME] > 0 and stat_data[TOTAL_TOK_BY_MODEL] else 0.0, html=True)}/小时</div>
<div class=\"kpi-title\">花费/消息数量(排除回复)</div>
<div class=\"kpi-value\">{(stat_data[TOTAL_COST] / (stat_data[TOTAL_MSG_CNT] - stat_data.get(TOTAL_REPLY_CNT, 0)) * 100 if (stat_data[TOTAL_MSG_CNT] - stat_data.get(TOTAL_REPLY_CNT, 0)) > 0 else 0.0):.4f} ¥/100条</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">花费/回复数量</div>
<div class=\"kpi-value\">{(stat_data[TOTAL_COST] / stat_data.get(TOTAL_REPLY_CNT, 0) * 100 if stat_data.get(TOTAL_REPLY_CNT, 0) > 0 else 0.0):.4f} ¥/100条</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">花费/时间</div>
<div class=\"kpi-value\">{(stat_data[TOTAL_COST] / (stat_data[ONLINE_TIME] / 3600.0) if stat_data[ONLINE_TIME] > 0 else 0.0):.2f} ¥/小时</div>
</div>
<div class=\"kpi-card\">
<div class=\"kpi-title\">Token/时间</div>
<div class=\"kpi-value\">{_format_large_number(sum(stat_data[TOTAL_TOK_BY_MODEL].values()) / (stat_data[ONLINE_TIME] / 3600.0) if stat_data[ONLINE_TIME] > 0 and stat_data[TOTAL_TOK_BY_MODEL] else 0.0, html=True)}/小时</div>
</div>
</div>
<h2>按模型分类统计</h2>
@@ -1805,10 +1798,8 @@ class StatisticOutputTask(AsyncTask):
# 初始化数据结构
cost_per_100_messages = [0.0] * len(time_points) # 花费/消息数量（每100条）
cost_per_hour = [0.0] * len(time_points) # 花费/时间（每小时）
tokens_per_100_messages = [0.0] * len(time_points) # Token/消息数量（每100条）
tokens_per_hour = [0.0] * len(time_points) # Token/时间（每小时）
cost_per_100_replies = [0.0] * len(time_points) # 花费/回复数量（每100条）
tokens_per_100_replies = [0.0] * len(time_points) # Token/回复数量（每100条）
# 每个时间点的累计数据
total_costs = [0.0] * len(time_points)
@@ -1882,10 +1873,6 @@ class StatisticOutputTask(AsyncTask):
if total_online_hours[idx] > 0:
cost_per_hour[idx] = (total_costs[idx] / total_online_hours[idx])
# Token/消息数量（每100条）
if total_messages[idx] > 0:
tokens_per_100_messages[idx] = (total_tokens[idx] / total_messages[idx] * 100)
# Token/时间（每小时）
if total_online_hours[idx] > 0:
tokens_per_hour[idx] = (total_tokens[idx] / total_online_hours[idx])
@@ -1893,10 +1880,6 @@ class StatisticOutputTask(AsyncTask):
# 花费/回复数量（每100条）
if total_replies[idx] > 0:
cost_per_100_replies[idx] = (total_costs[idx] / total_replies[idx] * 100)
# Token/回复数量（每100条）
if total_replies[idx] > 0:
tokens_per_100_replies[idx] = (total_tokens[idx] / total_replies[idx] * 100)
# 生成时间标签
if interval_hours == 1:
@@ -1908,10 +1891,8 @@ class StatisticOutputTask(AsyncTask):
"time_labels": time_labels,
"cost_per_100_messages": cost_per_100_messages,
"cost_per_hour": cost_per_hour,
"tokens_per_100_messages": tokens_per_100_messages,
"tokens_per_hour": tokens_per_hour,
"cost_per_100_replies": cost_per_100_replies,
"tokens_per_100_replies": tokens_per_100_replies,
}
def _generate_metrics_tab(self, metrics_data: dict) -> str:
@@ -1919,10 +1900,8 @@ class StatisticOutputTask(AsyncTask):
colors = {
"cost_per_100_messages": "#8b5cf6",
"cost_per_hour": "#9f8efb",
"tokens_per_100_messages": "#b5a6ff",
"tokens_per_hour": "#c7bbff",
"cost_per_100_replies": "#d9ceff",
"tokens_per_100_replies": "#a78bfa",
}
return f"""
@@ -1944,17 +1923,11 @@ class StatisticOutputTask(AsyncTask):
<div style="margin-bottom: 40px;">
<canvas id="costPerHourChart" width="800" height="400"></canvas>
</div>
<div style="margin-bottom: 40px;">
<canvas id="tokensPer100MessagesChart" width="800" height="400"></canvas>
</div>
<div style="margin-bottom: 40px;">
<canvas id="tokensPerHourChart" width="800" height="400"></canvas>
</div>
<div style="margin-bottom: 40px;">
<canvas id="costPer100RepliesChart" width="800" height="400"></canvas>
</div>
<div>
<canvas id="tokensPer100RepliesChart" width="800" height="400"></canvas>
<canvas id="costPer100RepliesChart" width="800" height="400"></canvas>
</div>
</div>
@@ -2001,13 +1974,6 @@ class StatisticOutputTask(AsyncTask):
dataKey: 'cost_per_hour',
color: '{colors["cost_per_hour"]}'
}},
tokensPer100Messages: {{
id: 'tokensPer100MessagesChart',
title: 'Token/消息数量',
yAxisLabel: 'Token (/100条)',
dataKey: 'tokens_per_100_messages',
color: '{colors["tokens_per_100_messages"]}'
}},
tokensPerHour: {{
id: 'tokensPerHourChart',
title: 'Token/时间',
@@ -2021,13 +1987,6 @@ class StatisticOutputTask(AsyncTask):
yAxisLabel: '花费 (¥/100条)',
dataKey: 'cost_per_100_replies',
color: '{colors["cost_per_100_replies"]}'
}},
tokensPer100Replies: {{
id: 'tokensPer100RepliesChart',
title: 'Token/回复数量',
yAxisLabel: 'Token (/100条)',
dataKey: 'tokens_per_100_replies',
color: '{colors["tokens_per_100_replies"]}'
}}
}};
@@ -2054,10 +2013,8 @@ class StatisticOutputTask(AsyncTask):
// 重新创建图表
createMetricsChart('costPer100Messages', data, timeScale);
createMetricsChart('costPerHour', data, timeScale);
createMetricsChart('tokensPer100Messages', data, timeScale);
createMetricsChart('tokensPerHour', data, timeScale);
createMetricsChart('costPer100Replies', data, timeScale);
createMetricsChart('tokensPer100Replies', data, timeScale);
}}
function createMetricsChart(chartType, data, timeScale) {{