feat: 引入统一的端点检查器以重构适配器并改进错误处理和用量统计。

This commit is contained in:
hoping
2025-12-25 00:02:56 +08:00
parent 9dad194130
commit 26b4a37323
23 changed files with 2282 additions and 119 deletions

View File

@@ -8,116 +8,86 @@ from src.api.handlers.base.utils import build_sse_headers, extract_cache_creatio
class TestExtractCacheCreationTokens:
"""测试 extract_cache_creation_tokens 函数"""
# === 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"""
def test_new_format_only(self) -> None:
"""测试只有新格式字段"""
usage = {
"claude_cache_creation_5_m_tokens": 100,
"claude_cache_creation_1_h_tokens": 200,
}
assert extract_cache_creation_tokens(usage) == 300
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"""
def test_new_format_5m_only(self) -> None:
"""测试只有 5 分钟缓存"""
usage = {
"claude_cache_creation_5_m_tokens": 150,
"claude_cache_creation_1_h_tokens": 0,
}
assert extract_cache_creation_tokens(usage) == 150
def test_flat_new_format_1h_only(self) -> None:
"""测试只有 1 小时扁平缓存"""
def test_new_format_1h_only(self) -> None:
"""测试只有 1 小时缓存"""
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"""
"""测试只有旧格式字段"""
usage = {
"cache_creation_input_tokens": 549,
"cache_creation_input_tokens": 500,
}
assert extract_cache_creation_tokens(usage) == 549
assert extract_cache_creation_tokens(usage) == 500
# === 边界情况测试 ===
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
def test_no_cache_creation_tokens(self) -> None:
"""测试没有任何缓存字段"""
def test_empty_usage(self) -> None:
"""测试空字典"""
usage = {}
assert extract_cache_creation_tokens(usage) == 0
def test_all_formats_zero(self) -> None:
"""测试所有格式都为 0"""
def test_all_zeros(self) -> None:
"""测试所有字段都为 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,
"cache_creation": {
"ephemeral_5m_input_tokens": 50,
"ephemeral_1h_input_tokens": 75,
},
"claude_cache_creation_5_m_tokens": 50,
"claude_cache_creation_1_h_tokens": 75,
}
assert extract_cache_creation_tokens(usage) == 125