statistics输出优化
llm_statistics输出优化(增加token分模型计算,格式优化)
This commit is contained in:
@@ -50,7 +50,11 @@ class LLMStatistics:
|
||||
"total_cost": 0.0,
|
||||
"costs_by_user": defaultdict(float),
|
||||
"costs_by_type": defaultdict(float),
|
||||
"costs_by_model": defaultdict(float)
|
||||
"costs_by_model": defaultdict(float),
|
||||
#新增token统计字段
|
||||
"tokens_by_type": defaultdict(int),
|
||||
"tokens_by_user": defaultdict(int),
|
||||
"tokens_by_model": defaultdict(int),
|
||||
}
|
||||
|
||||
cursor = db.llm_usage.find({
|
||||
@@ -71,7 +75,11 @@ class LLMStatistics:
|
||||
|
||||
prompt_tokens = doc.get("prompt_tokens", 0)
|
||||
completion_tokens = doc.get("completion_tokens", 0)
|
||||
stats["total_tokens"] += prompt_tokens + completion_tokens
|
||||
total_tokens = prompt_tokens + completion_tokens # 根据数据库字段调整
|
||||
stats["tokens_by_type"][request_type] += total_tokens
|
||||
stats["tokens_by_user"][user_id] += total_tokens
|
||||
stats["tokens_by_model"][model_name] += total_tokens
|
||||
stats["total_tokens"] += total_tokens
|
||||
|
||||
cost = doc.get("cost", 0.0)
|
||||
stats["total_cost"] += cost
|
||||
@@ -98,30 +106,60 @@ class LLMStatistics:
|
||||
}
|
||||
|
||||
def _format_stats_section(self, stats: Dict[str, Any], title: str) -> str:
|
||||
"""格式化统计部分的输出
|
||||
|
||||
Args:
|
||||
stats: 统计数据
|
||||
title: 部分标题
|
||||
"""
|
||||
"""格式化统计部分的输出"""
|
||||
output = []
|
||||
output.append(f"\n{title}")
|
||||
output.append("=" * len(title))
|
||||
|
||||
output.append("\n"+"-" * 84)
|
||||
output.append(f"{title}")
|
||||
output.append("-" * 84)
|
||||
|
||||
output.append(f"总请求数: {stats['total_requests']}")
|
||||
if stats['total_requests'] > 0:
|
||||
output.append(f"总Token数: {stats['total_tokens']}")
|
||||
output.append(f"总花费: ¥{stats['total_cost']:.4f}")
|
||||
output.append(f"总花费: {stats['total_cost']:.4f}¥\n")
|
||||
|
||||
output.append("\n按模型统计:")
|
||||
data_fmt = "{:<32} {:>10} {:>14} {:>13.4f} ¥"
|
||||
|
||||
# 按模型统计
|
||||
output.append("按模型统计:")
|
||||
output.append(("模型名称 调用次数 Token总量 累计花费"))
|
||||
for model_name, count in sorted(stats["requests_by_model"].items()):
|
||||
tokens = stats["tokens_by_model"][model_name]
|
||||
cost = stats["costs_by_model"][model_name]
|
||||
output.append(f"- {model_name}: {count}次 (花费: ¥{cost:.4f})")
|
||||
output.append(data_fmt.format(
|
||||
model_name[:32] + ".." if len(model_name) > 32 else model_name,
|
||||
count,
|
||||
tokens,
|
||||
cost
|
||||
))
|
||||
output.append("")
|
||||
|
||||
output.append("\n按请求类型统计:")
|
||||
# 按请求类型统计
|
||||
output.append("按请求类型统计:")
|
||||
output.append(("模型名称 调用次数 Token总量 累计花费"))
|
||||
for req_type, count in sorted(stats["requests_by_type"].items()):
|
||||
tokens = stats["tokens_by_type"][req_type]
|
||||
cost = stats["costs_by_type"][req_type]
|
||||
output.append(f"- {req_type}: {count}次 (花费: ¥{cost:.4f})")
|
||||
output.append(data_fmt.format(
|
||||
req_type[:22] + ".." if len(req_type) > 24 else req_type,
|
||||
count,
|
||||
tokens,
|
||||
cost
|
||||
))
|
||||
output.append("")
|
||||
|
||||
# 修正用户统计列宽
|
||||
output.append("按用户统计:")
|
||||
output.append(("模型名称 调用次数 Token总量 累计花费"))
|
||||
for user_id, count in sorted(stats["requests_by_user"].items()):
|
||||
tokens = stats["tokens_by_user"][user_id]
|
||||
cost = stats["costs_by_user"][user_id]
|
||||
output.append(data_fmt.format(
|
||||
user_id[:22], # 不再添加省略号,保持原始ID
|
||||
count,
|
||||
tokens,
|
||||
cost
|
||||
))
|
||||
|
||||
return "\n".join(output)
|
||||
|
||||
@@ -131,7 +169,7 @@ class LLMStatistics:
|
||||
|
||||
output = []
|
||||
output.append(f"LLM请求统计报告 (生成时间: {current_time})")
|
||||
output.append("=" * 50)
|
||||
|
||||
|
||||
# 添加各个时间段的统计
|
||||
sections = [
|
||||
|
||||
Reference in New Issue
Block a user