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fix(usage): 统一使用记录与仪表盘的缓存命中率计算口径

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- 新增归一化总输入上下文计算逻辑，按 provider 区分 OpenAI/Gemini 与 Claude 的 cache token 语义
- 将管理端使用聚合、用户使用记录、仪表盘缓存统计、缓存亲和性分析统一为 token 级缓存命中率
- 修正 total_input_context 字段，避免 cache_read 在部分 provider 上被重复计入分母
- 同步更新相关 Rust 单元测试与网关集成测试断言
- 调整前端 dashboard mock 中 cache_hit_rate 的单位为百分比
This commit is contained in:
AAEE86
2026-04-12 00:57:40 +08:00
parent 7c5bb7f383
commit 335e440cc5
9 changed files with 218 additions and 74 deletions
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131
crates/aether-admin/src/observability/usage.rs
View File

@@ -1,5 +1,7 @@
use crate::observability::stats::{aggregate_usage_stats, parse_bounded_u32, round_to};
use aether_billing::normalize_input_tokens_for_billing;
use aether_billing::{
normalize_input_tokens_for_billing, normalize_total_input_context_for_cache_hit_rate,
};
use aether_data::repository::users::StoredUserSummary;
use aether_data_contracts::repository::{
provider_catalog::{StoredProviderCatalogEndpoint, StoredProviderCatalogProvider},
@@ -318,9 +320,20 @@ pub fn admin_usage_cache_creation_tokens(item: &StoredRequestUsageAudit) -> u64
}
pub fn admin_usage_total_input_context(item: &StoredRequestUsageAudit) -> u64 {
item.input_tokens
.saturating_add(admin_usage_cache_creation_tokens(item))
.saturating_add(item.cache_read_input_tokens)
let api_format = item
.endpoint_api_format
.as_deref()
.or(item.api_format.as_deref());
let input_tokens = i64::try_from(item.input_tokens).unwrap_or(i64::MAX);
let cache_creation_tokens =
i64::try_from(admin_usage_cache_creation_tokens(item)).unwrap_or(i64::MAX);
let cache_read_tokens = i64::try_from(item.cache_read_input_tokens).unwrap_or(i64::MAX);
normalize_total_input_context_for_cache_hit_rate(
api_format,
input_tokens,
cache_creation_tokens,
cache_read_tokens,
) as u64
}
pub fn admin_usage_effective_input_tokens(item: &StoredRequestUsageAudit) -> u64 {
@@ -358,13 +371,15 @@ pub fn admin_usage_aggregation_by_model_json(
limit: usize,
) -> Value {
#[allow(clippy::type_complexity)]
let mut grouped: BTreeMap<String, (u64, u64, u64, u64, u64, u64, u64, u64, u64, f64, f64)> =
BTreeMap::new();
let mut grouped: BTreeMap<
String,
(u64, u64, u64, u64, u64, u64, u64, u64, u64, u64, f64, f64),
> = BTreeMap::new();
for item in usage {
let key = item.model.clone();
let entry = grouped
.entry(key)
.or_insert((0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, 0.0));
.or_insert((0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, 0.0));
entry.0 = entry.0.saturating_add(1);
entry.1 = entry.1.saturating_add(item.total_tokens);
entry.2 = entry.2.saturating_add(item.input_tokens);
@@ -374,16 +389,19 @@ pub fn admin_usage_aggregation_by_model_json(
.saturating_add(admin_usage_effective_input_tokens(item));
entry.5 = entry
.5
.saturating_add(admin_usage_cache_creation_tokens(item));
.saturating_add(admin_usage_total_input_context(item));
entry.6 = entry
.6
.saturating_add(item.cache_creation_ephemeral_5m_input_tokens);
.saturating_add(admin_usage_cache_creation_tokens(item));
entry.7 = entry
.7
.saturating_add(item.cache_creation_ephemeral_5m_input_tokens);
entry.8 = entry
.8
.saturating_add(item.cache_creation_ephemeral_1h_input_tokens);
entry.8 = entry.8.saturating_add(item.cache_read_input_tokens);
entry.9 += item.total_cost_usd;
entry.10 += item.actual_total_cost_usd;
entry.9 = entry.9.saturating_add(item.cache_read_input_tokens);
entry.10 += item.total_cost_usd;
entry.11 += item.actual_total_cost_usd;
}
let mut items: Vec<Value> = grouped
@@ -394,9 +412,10 @@ pub fn admin_usage_aggregation_by_model_json(
(
request_count,
total_tokens,
input_tokens,
_input_tokens,
output_tokens,
effective_input_tokens,
total_input_context,
cache_creation_tokens,
cache_creation_ephemeral_5m_tokens,
cache_creation_ephemeral_1h_tokens,
@@ -410,9 +429,7 @@ pub fn admin_usage_aggregation_by_model_json(
"request_count": request_count,
"total_tokens": total_tokens,
"effective_input_tokens": effective_input_tokens,
"total_input_context": input_tokens
.saturating_add(cache_creation_tokens)
.saturating_add(cache_read_tokens),
"total_input_context": total_input_context,
"output_tokens": output_tokens,
"total_cost": round_to(total_cost, 6),
"actual_cost": round_to(actual_cost, 6),
@@ -421,9 +438,7 @@ pub fn admin_usage_aggregation_by_model_json(
"cache_creation_ephemeral_1h_tokens": cache_creation_ephemeral_1h_tokens,
"cache_read_tokens": cache_read_tokens,
"cache_hit_rate": admin_usage_token_cache_hit_rate(
input_tokens
.saturating_add(cache_creation_tokens)
.saturating_add(cache_read_tokens),
total_input_context,
cache_read_tokens,
),
})
@@ -464,6 +479,7 @@ pub fn admin_usage_aggregation_by_provider_json(
u64,
u64,
u64,
u64,
f64,
f64,
u64,
@@ -488,6 +504,7 @@ pub fn admin_usage_aggregation_by_provider_json(
0,
0,
0,
0,
0.0,
0.0,
0,
@@ -505,21 +522,24 @@ pub fn admin_usage_aggregation_by_provider_json(
.saturating_add(admin_usage_effective_input_tokens(item));
entry.6 = entry
.6
.saturating_add(admin_usage_cache_creation_tokens(item));
.saturating_add(admin_usage_total_input_context(item));
entry.7 = entry
.7
.saturating_add(item.cache_creation_ephemeral_5m_input_tokens);
.saturating_add(admin_usage_cache_creation_tokens(item));
entry.8 = entry
.8
.saturating_add(item.cache_creation_ephemeral_5m_input_tokens);
entry.9 = entry
.9
.saturating_add(item.cache_creation_ephemeral_1h_input_tokens);
entry.9 = entry.9.saturating_add(item.cache_read_input_tokens);
entry.10 += item.total_cost_usd;
entry.11 += item.actual_total_cost_usd;
entry.12 = entry
.12
.saturating_add(item.response_time_ms.unwrap_or_default());
entry.10 = entry.10.saturating_add(item.cache_read_input_tokens);
entry.11 += item.total_cost_usd;
entry.12 += item.actual_total_cost_usd;
entry.13 = entry
.13
.saturating_add(item.response_time_ms.unwrap_or_default());
entry.14 = entry
.14
.saturating_add(if admin_usage_is_success(item) { 1 } else { 0 });
}
@@ -532,9 +552,10 @@ pub fn admin_usage_aggregation_by_provider_json(
provider_name,
request_count,
total_tokens,
input_tokens,
_input_tokens,
output_tokens,
effective_input_tokens,
total_input_context,
cache_creation_tokens,
cache_creation_ephemeral_5m_tokens,
cache_creation_ephemeral_1h_tokens,
@@ -562,9 +583,7 @@ pub fn admin_usage_aggregation_by_provider_json(
"request_count": request_count,
"total_tokens": total_tokens,
"effective_input_tokens": effective_input_tokens,
"total_input_context": input_tokens
.saturating_add(cache_creation_tokens)
.saturating_add(cache_read_tokens),
"total_input_context": total_input_context,
"output_tokens": output_tokens,
"total_cost": round_to(total_cost, 6),
"actual_cost": round_to(actual_cost, 6),
@@ -576,9 +595,7 @@ pub fn admin_usage_aggregation_by_provider_json(
"cache_creation_ephemeral_1h_tokens": cache_creation_ephemeral_1h_tokens,
"cache_read_tokens": cache_read_tokens,
"cache_hit_rate": admin_usage_token_cache_hit_rate(
input_tokens
.saturating_add(cache_creation_tokens)
.saturating_add(cache_read_tokens),
total_input_context,
cache_read_tokens,
),
})
@@ -608,7 +625,21 @@ pub fn admin_usage_aggregation_by_api_format_json(
#[allow(clippy::type_complexity)]
let mut grouped: BTreeMap<
String,
(u64, u64, u64, u64, u64, u64, u64, u64, u64, f64, f64, u64),
(
u64,
u64,
u64,
u64,
u64,
u64,
u64,
u64,
u64,
u64,
f64,
f64,
u64,
),
> = BTreeMap::new();
for item in usage {
let key = item
@@ -617,7 +648,7 @@ pub fn admin_usage_aggregation_by_api_format_json(
.unwrap_or_else(|| "unknown".to_string());
let entry = grouped
.entry(key)
.or_insert((0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, 0.0, 0));
.or_insert((0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, 0.0, 0));
entry.0 = entry.0.saturating_add(1);
entry.1 = entry.1.saturating_add(item.total_tokens);
entry.2 = entry.2.saturating_add(item.input_tokens);
@@ -627,18 +658,21 @@ pub fn admin_usage_aggregation_by_api_format_json(
.saturating_add(admin_usage_effective_input_tokens(item));
entry.5 = entry
.5
.saturating_add(admin_usage_cache_creation_tokens(item));
.saturating_add(admin_usage_total_input_context(item));
entry.6 = entry
.6
.saturating_add(item.cache_creation_ephemeral_5m_input_tokens);
.saturating_add(admin_usage_cache_creation_tokens(item));
entry.7 = entry
.7
.saturating_add(item.cache_creation_ephemeral_5m_input_tokens);
entry.8 = entry
.8
.saturating_add(item.cache_creation_ephemeral_1h_input_tokens);
entry.8 = entry.8.saturating_add(item.cache_read_input_tokens);
entry.9 += item.total_cost_usd;
entry.10 += item.actual_total_cost_usd;
entry.11 = entry
.11
entry.9 = entry.9.saturating_add(item.cache_read_input_tokens);
entry.10 += item.total_cost_usd;
entry.11 += item.actual_total_cost_usd;
entry.12 = entry
.12
.saturating_add(item.response_time_ms.unwrap_or_default());
}
@@ -650,9 +684,10 @@ pub fn admin_usage_aggregation_by_api_format_json(
(
request_count,
total_tokens,
input_tokens,
_input_tokens,
output_tokens,
effective_input_tokens,
total_input_context,
cache_creation_tokens,
cache_creation_ephemeral_5m_tokens,
cache_creation_ephemeral_1h_tokens,
@@ -672,9 +707,7 @@ pub fn admin_usage_aggregation_by_api_format_json(
"request_count": request_count,
"total_tokens": total_tokens,
"effective_input_tokens": effective_input_tokens,
"total_input_context": input_tokens
.saturating_add(cache_creation_tokens)
.saturating_add(cache_read_tokens),
"total_input_context": total_input_context,
"output_tokens": output_tokens,
"total_cost": round_to(total_cost, 6),
"actual_cost": round_to(actual_cost, 6),
@@ -684,9 +717,7 @@ pub fn admin_usage_aggregation_by_api_format_json(
"cache_creation_ephemeral_1h_tokens": cache_creation_ephemeral_1h_tokens,
"cache_read_tokens": cache_read_tokens,
"cache_hit_rate": admin_usage_token_cache_hit_rate(
input_tokens
.saturating_add(cache_creation_tokens)
.saturating_add(cache_read_tokens),
total_input_context,
cache_read_tokens,
),
})