feat: enhance extract_cache_creation_tokens function to support three formats[#41] (#42)

- Updated the function to prioritize nested format, followed by flat new format, and finally old format for cache creation tokens.
- Added fallback logic for cases where the preferred formats return zero.
- Expanded unit tests to cover new format scenarios and ensure proper functionality across all formats.

Co-authored-by: heweimin <heweimin@retaileye.ai>
This commit is contained in:
Hwwwww-dev
2025-12-24 01:31:45 +08:00
committed by GitHub
parent 03eb7203ec
commit 15a9b88fc8
2 changed files with 140 additions and 56 deletions

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@@ -4,17 +4,28 @@ Handler 基础工具函数
from typing import Any, Dict, Optional
from src.core.logger import logger
def extract_cache_creation_tokens(usage: Dict[str, Any]) -> int:
"""
提取缓存创建 tokens兼容新旧格式)
提取缓存创建 tokens兼容三种格式)
Claude API 在不同版本中使用了不同的字段名来表示缓存创建 tokens
- 新格式2024年后使用 claude_cache_creation_5_m_tokens 和
claude_cache_creation_1_h_tokens 分别表示 5 分钟和 1 小时缓存
- 旧格式:使用 cache_creation_input_tokens 表示总的缓存创建 tokens
根据 Anthropic API 文档,支持三种格式(按优先级)
此函数自动检测并适配两种格式优先使用新格式。
1. **嵌套格式优先级最高)**
usage.cache_creation.ephemeral_5m_input_tokens
usage.cache_creation.ephemeral_1h_input_tokens
2. **扁平新格式(优先级第二)**
usage.claude_cache_creation_5_m_tokens
usage.claude_cache_creation_1_h_tokens
3. **旧格式(优先级第三)**
usage.cache_creation_input_tokens
优先使用嵌套格式,如果嵌套格式字段存在但值为 0则智能 fallback 到旧格式。
扁平格式和嵌套格式互斥,按顺序检查。
Args:
usage: API 响应中的 usage 字典
@@ -22,20 +33,63 @@ def extract_cache_creation_tokens(usage: Dict[str, Any]) -> int:
Returns:
缓存创建 tokens 总数
"""
# 检查新格式字段是否存在(而非值是否为 0
# 如果字段存在,即使值为 0 也是合法的,不应 fallback 到旧格式
has_new_format = (
# 1. 检查嵌套格式(最新格式
cache_creation = usage.get("cache_creation")
if isinstance(cache_creation, dict):
cache_5m = int(cache_creation.get("ephemeral_5m_input_tokens", 0))
cache_1h = int(cache_creation.get("ephemeral_1h_input_tokens", 0))
total = cache_5m + cache_1h
if total > 0:
logger.debug(
f"Using nested cache_creation: 5m={cache_5m}, 1h={cache_1h}, total={total}"
)
return total
# 嵌套格式存在但为 0fallback 到旧格式
old_format = int(usage.get("cache_creation_input_tokens", 0))
if old_format > 0:
logger.debug(
f"Nested cache_creation is 0, using old format: {old_format}"
)
return old_format
# 都是 0返回 0
return 0
# 2. 检查扁平新格式
has_flat_format = (
"claude_cache_creation_5_m_tokens" in usage
or "claude_cache_creation_1_h_tokens" in usage
)
if has_new_format:
cache_5m = usage.get("claude_cache_creation_5_m_tokens", 0)
cache_1h = usage.get("claude_cache_creation_1_h_tokens", 0)
return int(cache_5m) + int(cache_1h)
if has_flat_format:
cache_5m = int(usage.get("claude_cache_creation_5_m_tokens", 0))
cache_1h = int(usage.get("claude_cache_creation_1_h_tokens", 0))
total = cache_5m + cache_1h
# 回退到旧格式
return int(usage.get("cache_creation_input_tokens", 0))
if total > 0:
logger.debug(
f"Using flat new format: 5m={cache_5m}, 1h={cache_1h}, total={total}"
)
return total
# 扁平格式存在但为 0fallback 到旧格式
old_format = int(usage.get("cache_creation_input_tokens", 0))
if old_format > 0:
logger.debug(
f"Flat cache_creation is 0, using old format: {old_format}"
)
return old_format
# 都是 0返回 0
return 0
# 3. 回退到旧格式
old_format = int(usage.get("cache_creation_input_tokens", 0))
if old_format > 0:
logger.debug(f"Using old format: cache_creation_input_tokens={old_format}")
return old_format
def build_sse_headers(extra_headers: Optional[Dict[str, str]] = None) -> Dict[str, str]:

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@@ -8,86 +8,116 @@ from src.api.handlers.base.utils import build_sse_headers, extract_cache_creatio
class TestExtractCacheCreationTokens:
"""测试 extract_cache_creation_tokens 函数"""
def test_new_format_only(self) -> None:
"""测试只有新格式字段"""
# === 嵌套格式测试(优先级最高)===
def test_nested_cache_creation_format(self) -> None:
"""测试嵌套格式正常情况"""
usage = {
"cache_creation": {
"ephemeral_5m_input_tokens": 456,
"ephemeral_1h_input_tokens": 100,
}
}
assert extract_cache_creation_tokens(usage) == 556
def test_nested_cache_creation_with_old_format_fallback(self) -> None:
"""测试嵌套格式为 0 时回退到旧格式"""
usage = {
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 0,
},
"cache_creation_input_tokens": 549,
}
assert extract_cache_creation_tokens(usage) == 549
def test_nested_has_priority_over_flat(self) -> None:
"""测试嵌套格式优先于扁平格式"""
usage = {
"cache_creation": {
"ephemeral_5m_input_tokens": 100,
"ephemeral_1h_input_tokens": 200,
},
"claude_cache_creation_5_m_tokens": 999, # 应该被忽略
"claude_cache_creation_1_h_tokens": 888, # 应该被忽略
"cache_creation_input_tokens": 777, # 应该被忽略
}
assert extract_cache_creation_tokens(usage) == 300
# === 扁平格式测试(优先级第二)===
def test_flat_new_format_still_works(self) -> None:
"""测试扁平新格式兼容性"""
usage = {
"claude_cache_creation_5_m_tokens": 100,
"claude_cache_creation_1_h_tokens": 200,
}
assert extract_cache_creation_tokens(usage) == 300
def test_new_format_5m_only(self) -> None:
"""测试只有 5 分钟缓存"""
def test_flat_new_format_with_old_format_fallback(self) -> None:
"""测试扁平格式为 0 时回退到旧格式"""
usage = {
"claude_cache_creation_5_m_tokens": 0,
"claude_cache_creation_1_h_tokens": 0,
"cache_creation_input_tokens": 549,
}
assert extract_cache_creation_tokens(usage) == 549
def test_flat_new_format_5m_only(self) -> None:
"""测试只有 5 分钟扁平缓存"""
usage = {
"claude_cache_creation_5_m_tokens": 150,
"claude_cache_creation_1_h_tokens": 0,
}
assert extract_cache_creation_tokens(usage) == 150
def test_new_format_1h_only(self) -> None:
"""测试只有 1 小时缓存"""
def test_flat_new_format_1h_only(self) -> None:
"""测试只有 1 小时扁平缓存"""
usage = {
"claude_cache_creation_5_m_tokens": 0,
"claude_cache_creation_1_h_tokens": 250,
}
assert extract_cache_creation_tokens(usage) == 250
# === 旧格式测试(优先级第三)===
def test_old_format_only(self) -> None:
"""测试只有旧格式字段"""
"""测试只有旧格式"""
usage = {
"cache_creation_input_tokens": 500,
"cache_creation_input_tokens": 549,
}
assert extract_cache_creation_tokens(usage) == 500
assert extract_cache_creation_tokens(usage) == 549
def test_both_formats_prefers_new(self) -> None:
"""测试同时存在时优先使用新格式"""
usage = {
"claude_cache_creation_5_m_tokens": 100,
"claude_cache_creation_1_h_tokens": 200,
"cache_creation_input_tokens": 999, # 应该被忽略
}
assert extract_cache_creation_tokens(usage) == 300
# === 边界情况测试 ===
def test_empty_usage(self) -> None:
"""测试空字典"""
def test_no_cache_creation_tokens(self) -> None:
"""测试没有任何缓存字段"""
usage = {}
assert extract_cache_creation_tokens(usage) == 0
def test_all_zeros(self) -> None:
"""测试所有字段都为 0"""
def test_all_formats_zero(self) -> None:
"""测试所有格式都为 0"""
usage = {
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 0,
},
"claude_cache_creation_5_m_tokens": 0,
"claude_cache_creation_1_h_tokens": 0,
"cache_creation_input_tokens": 0,
}
assert extract_cache_creation_tokens(usage) == 0
def test_partial_new_format_with_old_format_fallback(self) -> None:
"""测试新格式字段不存在时回退到旧格式"""
usage = {
"cache_creation_input_tokens": 123,
}
assert extract_cache_creation_tokens(usage) == 123
def test_new_format_zero_should_not_fallback(self) -> None:
"""测试新格式字段存在但为 0 时,不应 fallback 到旧格式"""
usage = {
"claude_cache_creation_5_m_tokens": 0,
"claude_cache_creation_1_h_tokens": 0,
"cache_creation_input_tokens": 456,
}
# 新格式字段存在,即使值为 0 也应该使用新格式(返回 0
# 而不是 fallback 到旧格式(返回 456
assert extract_cache_creation_tokens(usage) == 0
def test_unrelated_fields_ignored(self) -> None:
"""测试忽略无关字段"""
usage = {
"input_tokens": 1000,
"output_tokens": 2000,
"cache_read_input_tokens": 300,
"claude_cache_creation_5_m_tokens": 50,
"claude_cache_creation_1_h_tokens": 75,
"cache_creation": {
"ephemeral_5m_input_tokens": 50,
"ephemeral_1h_input_tokens": 75,
},
}
assert extract_cache_creation_tokens(usage) == 125