feat: let one call ask for a different tier than its source defaults to

The three-layer priority (call > source > enable_thinking sugar > silence)
now lives in one pure function, thinking.effective_effort(). The assembly
guard and the request hot path used to each carry their own inline copy of
the sugar conversion; two copies of the same judgement drift into the worst
shape there is - passes at assembly, raises at runtime.

The guard now also honours effort_fallback, so a source that opted into
nearest is no longer sentenced at assembly for a tier it could have mapped.
This commit is contained in:
2026-09-05 02:15:25 -04:00
parent 603a835f60
commit 1f13eb18ab
5 changed files with 177 additions and 7 deletions
+17 -7
View File
@@ -34,7 +34,7 @@ from polygateway.sources import (
RoundRobinSelector,
SourceCooldownMemo,
)
from polygateway.thinking import get_capability, resolve_thinking
from polygateway.thinking import effective_effort, get_capability, resolve_thinking
from polygateway.transports.openai_compat import OpenAICompatTransport
from polygateway.types import (
ChatRequest,
@@ -81,16 +81,20 @@ def _guard_thinking(
就带着指路信息炸掉。`get_provider` 现在就是同一形态的双点调用。
"""
for source, profile in zip(sources, profiles, strict=True):
# `enable_thinking` 的档位语法糖(True → auto,False → none,None 不表态);
# 两个调用点各自就地转换是过渡形态,T5 起由 thinking.effective_effort()
# 统一收口并接上源级/请求级档位(设计 §4.2)
enabled = source.enable_thinking
effort = None if enabled is None else (Effort.AUTO if enabled else Effort.NONE)
resolve_thinking(
profile,
get_capability(source.model, table=capabilities),
effort,
# 装配期看不见请求级档位(它逐次调用才产生),故只解源级两层;请求级
# 只能在运行期由 transport 校验(设计 §10 的装配期/运行期分工)
effective_effort(
request_effort=None,
source_effort=source.reasoning_effort,
enable_thinking=source.enable_thinking,
),
model=source.model,
# 与 transport 用同一个 fallback,否则配了 nearest 的源会在装配期就被
# 判死,而它在运行期本来是能映射到最近档跑起来的
fallback=source.effort_fallback,
)
@@ -295,6 +299,7 @@ class GatewayClient:
structured: type[BaseModel] | Literal["json"] | None = None,
stream: bool = True,
overlay: Mapping[str, Any] | None = None,
reasoning_effort: Effort | None = None,
tenant_id: str | None = None,
meta: Mapping[str, Any] | None = None,
) -> LLMResponse:
@@ -304,6 +309,10 @@ class GatewayClient:
高于源级 `extra_body`、低于结构化输出的注入。带默认值的 keyword-only
参数不影响既有调用点(issue #4)。
`reasoning_effort` 是本次调用的推理档位,优先级高于源级 `REASONING_EFFORT`
与 `ENABLE_THINKING`(设计 §4.2)。`None` 是**不表态**(随源级配置),与
`Effort.NONE`("要求不推理")严格区分。
`tenant_id` 与 `meta` 是调用方自定义维度,只进遥测、**不进缓存 key**
(租户隔离由 `cache_namespace` 负责,ARCH §7.5);前者享有真实列待遇
(可挂 RLS、可进复合索引),后者是任意 KV 容器(issue #11)。
@@ -333,6 +342,7 @@ class GatewayClient:
stream=stream,
overlay=sampling,
sampling=sampling,
reasoning_effort=reasoning_effort,
tenant_id=dimension_tenant_id,
meta=dimensions,
)
+33
View File
@@ -308,6 +308,39 @@ class ThinkingResolution:
applied_effort: Effort | None
def effective_effort(
*,
request_effort: Effort | None,
source_effort: Effort | None,
enable_thinking: bool | None,
) -> Effort | None:
"""求本次生效的档位: 请求级 > 源级 > `enable_thinking` 语法糖 > 不表态(设计 §4.2)。
**收口成一个纯函数**是本函数存在的全部理由: 装配守卫(`client._guard_thinking`)
与请求热路径(`openai_compat._build_payload`)必须给出**同一个**判定,两处各写
一份就地转换迟早会分叉,而分叉的形态是"装配期放行、运行期报错"——最难查的那种。
**一律用 `is None` 判有没有表态,不靠真值性**: `Effort.NONE`(要求不推理)与
`enable_thinking=False` 都是**表态**而非缺省,`x or y` 式的回落会把后者当成没配
从而跳到下一层——那正是本次要消灭的静默失效。
语法糖排在最末且 `True → AUTO`(开启但不指定强度,不依赖能力表),不是旧版那个
硬编码的 `medium`: 那是库替下游做的档位判断,而 `medium` 在 GLM/kimi/deepseek 的
档位表里根本不存在(设计 §4.2 声明过的有意变更)。
同源同时配 `enable_thinking` 与 `reasoning_effort` 且语义矛盾,已由
`SourceConfig.__post_init__` 在构造期报错,故这里不再判——两个字段说同一件事时,
矛盾是配置错误,不是优先级问题。
"""
if request_effort is not None:
return request_effort
if source_effort is not None:
return source_effort
if enable_thinking is None:
return None
return Effort.AUTO if enable_thinking else Effort.NONE
def resolve_thinking(
profile: ProviderProfile,
capability: ThinkingCapability | None,
+11
View File
@@ -325,6 +325,17 @@ class ChatRequest:
再进一次既重复又会让存量缓存全量冷启动;且 `meta` 承载的是审计维度而非
语义维度,同 messages 同 namespace 下换个 batch_id 不应导致 miss。"""
# —— 请求级推理档位(issue #20;追加在末尾,不扰动既有字段的位置构造)——
reasoning_effort: Effort | None = None
"""本次调用要求的推理档位,压过源级默认(设计 §4.2 的最高优先级层)。
`None` 是**不表态**(随源级配置),与 `Effort.NONE`("要求不推理")严格区分:
把前者读成后者会让一次没写档位的调用悄悄关掉源上配好的推理。
独立成字段而非塞进 `overlay`: `overlay` 是采样参数的直通层,库不解释其内容,
而档位要经能力表校验、要进缓存 key、要落遥测——混进直通层等于放弃这三样,
正是 issue #20 里下游手写 `extra_body` 绕过全部治理的那条路。"""
@dataclass(frozen=True)
class Usage:
+51
View File
@@ -198,6 +198,57 @@ class TestSamplingOverlay:
assert [c["seed"] for c in captured] == [1, 2]
class TestReasoningEffortPriority:
"""三层优先级: 请求级 > 源级 > `enable_thinking` 语法糖 > 不表态(设计 §4.2)。
一律抓**真实请求体**而非只查 `ChatRequest` 字段: 档位的价值全在发出去的那几个
字节上,只断言中间态会让"字段填了但一路没人读"这种缺口继续通过测试——issue #20
的 `extra_body` 绕行正是这么长出来的。
"""
def _capturing_client(self, captured, **overrides):
def handler(request):
captured.append(json.loads(request.content))
return _sse()
return _client(handler=handler, **overrides)
def _zhipu(self, **overrides):
# glm-5.3 的档位是 low/high/max(能力表已登记),zhipu 的 wire 三样俱全,
# 是唯一能同时看清"开启形态"与"档位键"的组合
overrides.setdefault("model", "glm-5.3")
return _source(provider="zhipu", **overrides)
@pytest.mark.parametrize(
("provider", "model", "fragment"),
[
("qwen", "qwen-max", {"enable_thinking": True}),
("deepseek", "deepseek-v4-pro", {"thinking": {"type": "enabled"}}),
("zhipu", "glm-5.3", {"thinking": {"type": "enabled"}}),
("moonshot", "kimi-k3", {"thinking": {"type": "enabled"}}),
],
)
async def test_legacy_on_tier_matches_old_fragment(self, provider, model, fragment):
"""存量 `ENABLE_THINKING=true` 的回归门: 发出去的字节逐字不变。
**只覆盖 `on_base` 自己就说全了""的四段**。minimax/openai/anthropic/google
的开档旧版硬编码 `{"reasoning_effort": "medium"}`,新版不注入任何档位——那是
设计 §4.2 声明过的**有意变更**(medium 在 GLM/kimi/deepseek 的档位表里根本
不存在,是库替下游做的档位判断),不是本门要守的不变量。
qwen/deepseek 两条字面量逐字取自升级前的 `ProviderProfile.thinking_on`;
zhipu/moonshot 升级前没有对应段,断言的是它们 2026-09-04 登记的形态。
"""
captured = []
source = _source(provider=provider, model=model, enable_thinking=True)
async with self._capturing_client(captured, sources=[source]) as client:
await client.chat([{"role": "user", "content": "hi"}])
body = captured[0]
assert {k: body[k] for k in fragment} == fragment
# `auto` = 开启但不指定强度: 语法糖不得替调用方挑一个档
assert "reasoning_effort" not in body
class _MemoryRecorder:
"""收下遥测行原样存起来;断言"哪些行被写了"必须能看到零行的情形。"""
+65
View File
@@ -13,6 +13,7 @@ from polygateway.thinking import (
DEFAULT_CAPABILITIES,
ThinkingCapability,
ThinkingUnsupportedError,
effective_effort,
get_capability,
observe_thinking,
reconcile_thinking,
@@ -616,3 +617,67 @@ class TestCapabilityTierList:
assert get_capability("MiniMax-M2.7").can_disable is False
assert get_capability("MiniMax-M2.5").can_disable is False
assert get_capability("MiniMax-M3").can_disable is True
class TestEffectiveEffort:
"""三层优先级的**唯一**判定处(设计 §4.2): 请求级 > 源级 > 语法糖 > 不表态。
收口成一个纯函数,是因为它此前在装配守卫与 transport 里各写了一份就地转换:
两份各自演化的判定,迟早会在"装配期放行、运行期报错"这种最难查的形态上分叉。
"""
def test_request_beats_source(self):
assert (
effective_effort(
request_effort=Effort.MAX, source_effort=Effort.LOW, enable_thinking=None
)
is Effort.MAX
)
def test_source_beats_sugar(self):
assert (
effective_effort(request_effort=None, source_effort=Effort.HIGH, enable_thinking=None)
is Effort.HIGH
)
def test_none_request_does_not_clear_source(self):
"""请求级"没表态"绝不能被读成"要求关闭"——那会静默改掉源级的默认档。"""
assert (
effective_effort(request_effort=None, source_effort=Effort.LOW, enable_thinking=None)
is Effort.LOW
)
def test_request_none_tier_is_an_opinion(self):
"""`Effort.NONE` 是一次明确的表态,必须压过源级档位而不是被当成缺省。"""
assert (
effective_effort(
request_effort=Effort.NONE, source_effort=Effort.MAX, enable_thinking=None
)
is Effort.NONE
)
def test_enable_thinking_true_is_auto(self):
"""`True` → `auto`(开启但不指定强度),而**不是**旧版硬编码的 medium。"""
assert (
effective_effort(request_effort=None, source_effort=None, enable_thinking=True)
is Effort.AUTO
)
def test_enable_thinking_false_is_the_none_tier(self):
assert (
effective_effort(request_effort=None, source_effort=None, enable_thinking=False)
is Effort.NONE
)
def test_sugar_is_the_last_word_only(self):
"""语法糖排在最末: 显式配了档位就以档位为准(矛盾组合已被构造期挡下)。"""
assert (
effective_effort(request_effort=None, source_effort=Effort.LOW, enable_thinking=True)
is Effort.LOW
)
def test_all_absent_is_no_opinion(self):
"""三层都不表态 → None(随模型默认),与 `Effort.NONE` 严格区分。"""
assert (
effective_effort(request_effort=None, source_effort=None, enable_thinking=None) is None
)