refactor: make capability a tier list, since "can it be off" is one entry

The boolean could say a model reasons or does not. It could not say what
GLM-5.3 and Gemini 3 Pro actually do: refuse to stop reasoning while
still letting you ask for less. So capability becomes the list of tiers a
model serves, and `none`'s presence in it is what "can_disable" now reads.

Effort carries `auto` alongside the strength tiers. Nine of the models on
our gateway are pure switches with no tier to name, and without `auto`
they would have to borrow a strength tier to mean "on" — which is the
exact bug this work exists to remove.

Tiers land as documented guesses from four registries that agree; every
entry says so in its evidence, and task 10 replaces them with measurements.

src/polygateway/__init__.py

@@ -32,6 +32,8 @@ from polygateway.thinking import (
     resolve_thinking,
 )
 from polygateway.types import (
+    EFFORT_ORDER,
+    Effort,
     EmbeddingResponse,
     LLMResponse,
     OcrLayoutElement,
@@ -46,6 +48,8 @@ __version__ = "1.3.2"
 
 __all__ = [
     "DEFAULT_PROFILES",
+    "EFFORT_ORDER",
+    "Effort",
     "AllSourcesExhausted",
     "CircuitOpenError",
     "EmbeddingClient",

src/polygateway/thinking.py

@@ -15,7 +15,7 @@ from typing import Any
 from loguru import logger
 
 from polygateway.providers import ProviderProfile
-from polygateway.types import ThinkingObservation
+from polygateway.types import EFFORT_ORDER, Effort, ThinkingObservation
 
 
 def observe_thinking(*, thinking: str, reasoning_tokens: int | None) -> ThinkingObservation:
@@ -54,50 +54,214 @@ class ThinkingUnsupportedError(ValueError):
 
 @dataclass(frozen=True)
 class ThinkingCapability:
-    """某个**具体模型**能否关闭推理(issue #5);登记必须附实测证据与日期。
+    """某个**具体模型**支持哪些推理档位(设计 §3.2);登记必须附证据与日期。
 
     与 `ProviderProfile` 的分工: 后者声明**形态**(参数长什么样,按 provider 变,
     数年不变一次),本类声明**能力**(按 model 变,同一 provider 每代都变)。二者
     合一在 provider 级表达不了代际差异——实测 MiniMax-M3 可关闭推理,而同厂的
     M2.7/M2.5 三种参数形态全部无效(findings §2.3),profile 一格管不住三个模型。
 
+    **档位清单而非布尔**(2026-09-04): 旧版是 `can_disable: bool`,表达不了
+    "关不掉但能调到最低档"这第三种情况——而 GLM-5.3 系与 Gemini 3 Pro 都是它。
+    现在"能不能关"就是 `Effort.NONE` 在不在清单里,是派生量而非独立字段;三个
+    派生量一律不存字段,存了必与清单漂移。
+
     `evidence` 不是装饰: 能力表过期是必然事件,没有出处就无从判断该不该信它。
+    文档推定与实测必须在 evidence 里说清楚是哪种——前者会被 new-api 中转改写
+    (LiteLLM 里同一个 kimi-k3 在 `moonshot/` 下三档、`perplexity/` 下六档)。
     """
 
-    can_disable: bool
+    supported_efforts: tuple[Effort, ...]
     evidence: str
 
+    def __post_init__(self) -> None:
+        """构造期校验: 空清单与重复档都是登记错误,不能等到请求期才炸。"""
+        if not self.supported_efforts:
+            raise ValueError("supported_efforts 至少要有一档: 空清单表达不了任何能力")
+        if len(set(self.supported_efforts)) != len(self.supported_efforts):
+            raise ValueError(f"supported_efforts 有重复档: {self.supported_efforts}")
+
+    @property
+    def can_disable(self) -> bool:
+        """能否关闭推理 = `none` 在不在清单里(旧 `can_disable` 字段的等价物)。"""
+        return Effort.NONE in self.supported_efforts
+
+    @property
+    def cheapest_effort(self) -> Effort | None:
+        """除 `none` 外最省的一档;关不掉时作为**可执行替代**推荐给调用方。
+
+        `AUTO` 参与候选(纯开关型模型只有它可推荐),但因不在 `EFFORT_ORDER` 中,
+        仅当没有任何强度档时才被选中。全清单只有 `none` 时返回 None——那种模型
+        没有"最省的开启档"可言。
+        """
+        tiers = [e for e in EFFORT_ORDER if e is not Effort.NONE and e in self.supported_efforts]
+        if tiers:
+            return tiers[0]
+        return Effort.AUTO if Effort.AUTO in self.supported_efforts else None
+
+    @property
+    def is_tiered(self) -> bool:
+        """是否档位型(除 `none`/`auto` 外仍有强度档)。
+
+        用途是**告警文案**: 对纯开关型模型说"可选档位: ..."是错的,它没有档位。
+        """
+        return any(e not in (Effort.NONE, Effort.AUTO) for e in self.supported_efforts)
+
+
+# 证据分两类,evidence 里必须自报家门:
+#   实测 = 经 new-api 中转打过真实请求(最硬,不得被文档推定覆盖);
+#   文档推定 = 官方文档 / OpenRouter / cherry-studio / LiteLLM 四方交叉(待实测校正)。
+_MEASURED = "2026-08-02 经 new-api 中转实测"
+_DOC = "2026-09-04 文档推定(官方文档 + OpenRouter + cherry-studio + LiteLLM 四方交叉),待经 new-api 实测"
 
 DEFAULT_CAPABILITIES: Mapping[str, ThinkingCapability] = MappingProxyType(
     {
+        # —— 实测条目(2026-08-02/08-25),证据原文保留 ——
         "MiniMax-M3": ThinkingCapability(
-            can_disable=True,
+            supported_efforts=(Effort.NONE, Effort.AUTO),
             evidence=(
                 "2026-08-02 经 new-api 中转实测 N=10: reasoning_effort=none 稳定关闭,零跳变;"
                 "2026-08-25 复测依然成立(prompt 194 = 基线、completion 3、无推理正文)。"
                 "两条限制(findings 2026-08-25-thinking-observability-regression §3.1/§5): "
                 "① 非流式路径观测不到推理信号——推理已计费,但正文与 usage 明细都不回传;"
-                "② enable_thinking / thinking:{type:enabled} 对本模型无效,仅 reasoning_effort 是真开关"
+                "② enable_thinking / thinking:{type:enabled} 对本模型无效,仅 reasoning_effort 是真开关。"
+                "无强度档: 官方只有开/关两态(thinking.type disabled/adaptive)"
             ),
         ),
         "MiniMax-M2.7": ThinkingCapability(
-            can_disable=False,
+            supported_efforts=(Effort.AUTO,),
             evidence=(
                 "2026-08-02 实测 reasoning_effort=none / thinking:{disabled} / thinking:{adaptive} "
-                "各 N=3 全部无效;OpenRouter 注册表登记 mandatory:true,models.dev 登记无控制手段"
+                "各 N=3 全部无效;OpenRouter 注册表登记 mandatory:true,models.dev 登记无控制手段。"
+                "MiniMax 官方亦承认 M2.x 接受 disabled 但推理仍开着"
             ),
         ),
         "MiniMax-M2.5": ThinkingCapability(
-            can_disable=False,
+            supported_efforts=(Effort.AUTO,),
             evidence="2026-08-02 实测同 M2.7: 三种形态各 N=3 全部无效;外部注册表同样登记为强制推理",
         ),
         "qwen3.7-plus": ThinkingCapability(
-            can_disable=True,
-            evidence="2026-08-02 实测 enable_thinking=false 关闭(completion 5 token,无推理)",
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=(
+                "2026-08-02 实测 enable_thinking=false 关闭(completion 5 token,无推理)。"
+                "无强度档: OpenRouter 登记本型号只支持 reasoning 开关,不支持 reasoning_effort"
+            ),
         ),
         "deepseek-v4-pro": ThinkingCapability(
-            can_disable=True,
-            evidence="2026-08-02 实测 thinking:{type:disabled} 关闭(completion 3 token,无推理)",
+            supported_efforts=(Effort.NONE, Effort.HIGH, Effort.MAX),
+            evidence=(
+                "关闭档为 2026-08-02 实测(thinking:{type:disabled},completion 3 token,无推理);"
+                f"强度档为{_DOC}: 官方 thinking_mode 文档列 Non-think/Think High/Think Max 三态,默认 high"
+            ),
+        ),
+        # —— 文档推定条目(2026-09-04),待 T10 经 new-api 实测校正 ——
+        "deepseek-v4-flash": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.HIGH, Effort.MAX),
+            evidence=f"{_DOC}: 官方文档「deepseek-v4-flash 与 deepseek-v4-pro 一致」,默认 high",
+        ),
+        "deepseek-v4-flash-vision-exp": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.HIGH, Effort.MAX),
+            evidence=f"{_DOC}: 同 v4-flash 一档(OpenRouter 登记支持 reasoning_effort)",
+        ),
+        "glm-5.3": ThinkingCapability(
+            supported_efforts=(Effort.LOW, Effort.HIGH, Effort.MAX),
+            evidence=(
+                f"{_DOC}: **推理不可关闭**——智谱官方文档明确 thinking.type 只接受 enabled,"
+                "官方迁移建议是改用 enabled + reasoning_effort=low;cherry-studio 标 toggle:false、"
+                "OpenRouter 标 mandatory:true,三源一致。默认 max。"
+                "注: issue #20 实测的 reasoning_effort=none 是**未定义值**,短提示词下 rt≈1.2 像是关了,"
+                "5552 token 长上下文下跳到 0/54/167 即露馅"
+            ),
+        ),
+        "glm-5.3-flash": ThinkingCapability(
+            supported_efforts=(Effort.LOW, Effort.HIGH, Effort.MAX),
+            evidence=f"{_DOC}: 同 glm-5.3(cherry-studio 的 pattern 'glm-5[.-]3' 覆盖两者),默认 max",
+        ),
+        "glm-5.2": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.HIGH, Effort.MAX),
+            evidence=(
+                f"{_DOC}: cherry-studio 登记 none/high/max(官方端点默认 max,百炼上默认 high)。"
+                "注意: issue #20 记录本渠道对 glm-5.2 的请求 6/6 回报 model=glm-5.3,疑被路由,实测时须核对 model_reported"
+            ),
+        ),
+        "glm-5": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: OpenRouter 登记只支持 reasoning 开关、无 reasoning_effort;cherry-studio 标 toggle:true",
+        ),
+        "glm-5.1": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: 同 glm-5(OpenRouter reasoning.mandatory=false 且无 supported_efforts)",
+        ),
+        "glm-4.6v": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: OpenRouter 登记无 reasoning_effort;VLM,推理控制同 glm-4.x 系开关型",
+        ),
+        "kimi-k3": ThinkingCapability(
+            supported_efforts=(Effort.LOW, Effort.HIGH, Effort.MAX),
+            evidence=(
+                f"{_DOC}: 官方 reasoning_effort 三档 low/high/max,默认 max。"
+                "**保守登记为不可关**——官方档位表无 none,而 OpenRouter 标 mandatory:false,两源分歧待实测;"
+                "保守方向的代价是下游配 none 会报错并被指向 low,反方向的代价是静默失效(issue #20 的病)。"
+                "另: 官方提示切换档位会使 prefix cache 失效,不宜在会话中途改档"
+            ),
+        ),
+        "gpt-5.4": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.LOW, Effort.MEDIUM, Effort.HIGH, Effort.XHIGH),
+            evidence=f"{_DOC}: OpenRouter 登记 none/low/medium/high/xhigh,默认 medium;LiteLLM 登记 minimal 不支持",
+        ),
+        "gpt-5.5": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.LOW, Effort.MEDIUM, Effort.HIGH, Effort.XHIGH),
+            evidence=f"{_DOC}: 同 gpt-5.4(OpenRouter supported_efforts 一致,默认 medium)",
+        ),
+        "claude-opus-5": ThinkingCapability(
+            supported_efforts=(
+                Effort.NONE,
+                Effort.LOW,
+                Effort.MEDIUM,
+                Effort.HIGH,
+                Effort.XHIGH,
+                Effort.MAX,
+            ),
+            evidence=(
+                f"{_DOC}: Anthropic 官方 adaptive thinking + output_config.effort 五档(low/medium/high/"
+                "xhigh/max),默认 high;OpenRouter 标 mandatory:false 故可关。"
+                "关闭档依赖 new-api 把 reasoning_effort=none 转成 thinking 关闭形态,待实测确认"
+            ),
+        ),
+        "claude-sonnet-5": ThinkingCapability(
+            supported_efforts=(
+                Effort.NONE,
+                Effort.LOW,
+                Effort.MEDIUM,
+                Effort.HIGH,
+                Effort.XHIGH,
+                Effort.MAX,
+            ),
+            evidence=f"{_DOC}: 同 claude-opus-5(OpenRouter supported_efforts 与默认档一致)",
+        ),
+        "gemini-3.1-pro": ThinkingCapability(
+            supported_efforts=(Effort.LOW, Effort.MEDIUM, Effort.HIGH),
+            evidence=(
+                f"{_DOC}: **推理不可关闭**——Google 官方文档明确 Gemini 3 Pro / 3.1 Pro 无法关闭思考,"
+                "OpenRouter 亦标 mandatory:true。thinking_level 三档;默认档两源打架"
+                "(官方文档说 HIGH,OpenRouter 说 medium),待实测"
+            ),
+        ),
+        "qwen-plus-latest": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: 百炼 enable_thinking 开关型(thinking_budget 是 token 预算,本库不支持预算型)",
+        ),
+        "qwen3.5-flash": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: 同 qwen-plus-latest(OpenRouter 登记无 reasoning_effort)",
+        ),
+        "qwen3.6-plus": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: 同 qwen-plus-latest(OpenRouter 登记无 reasoning_effort)",
+        ),
+        "qwen3.7-max": ThinkingCapability(
+            supported_efforts=(Effort.NONE, Effort.AUTO),
+            evidence=f"{_DOC}: 同 qwen3.7-plus 一代(OpenRouter 登记无 reasoning_effort)",
         ),
     }
 )

src/polygateway/types.py

@@ -167,6 +167,53 @@ def canonical_sampling_json(merged: Mapping[str, Any]) -> str | None:
     return json.dumps(dict(merged), sort_keys=True, ensure_ascii=False)
 
 
+class Effort(StrEnum):
+    """推理强度档位的封闭词汇(设计 §3.1)。
+
+    取值直接写进请求体(`reasoning_effort` 等键),**改名即改变发出去的字节**,
+    且会进缓存 key 与遥测落库,历史数据会断层。
+
+    八档而非六档: `none`(不推理)与 `auto`(推理,档位由模型自定)必须同时存在。
+    `auto` 不可省——newapi 上 26 个可调用模型里有 9 个是**纯开关型**(qwen 五个、
+    MiniMax-M3、glm-5/5.1/4.6v),它们能开推理却没有强度档可填;没有 `auto` 就只
+    能拿某个强度档冒充"开",而那正是本次要修的病根(旧 `thinking_on` 硬编码
+    `medium`,可 `medium` 在 GLM/kimi/deepseek 的档位表里根本不存在)。
+
+    词汇取四家参考实现共同收敛的一套(cherry-studio 的 canonical selection、
+    OpenRouter 的 `supported_efforts`、LiteLLM 的 `reasoning_effort_levels`、
+    new-api 的 `relayconvert/reasoning`),不自创。
+
+    **枚举定义在最内层而非决策层**: 它是 `SourceConfig`/`ChatRequest`/
+    `LLMResponse` 的字段类型,放进 `thinking.py` 会让 `types.py` 反向 import
+    决策模块(P7 依赖铁律),与 `ThinkingObservation` 同一理由。
+    """
+
+    NONE = "none"
+    AUTO = "auto"
+    MINIMAL = "minimal"
+    LOW = "low"
+    MEDIUM = "medium"
+    HIGH = "high"
+    XHIGH = "xhigh"
+    MAX = "max"
+
+
+EFFORT_ORDER: tuple[Effort, ...] = (
+    Effort.NONE,
+    Effort.MINIMAL,
+    Effort.LOW,
+    Effort.MEDIUM,
+    Effort.HIGH,
+    Effort.XHIGH,
+    Effort.MAX,
+)
+"""由弱到强的强度序;`AUTO` **不在其中**——它是"由模型自定",在强弱轴上没有位置。
+
+供能力表求"最省的开启档"与 `nearest` 映射取最近档。公开(非 `_` 前缀)是因为
+`thinking.py` 要跨模块消费它,跨模块引用私有名是坏味道。
+"""
+
+
 class ThinkingObservation(StrEnum):
     """一次调用中"推理是否真的发生"的裁定结果(issue #16/#17)。
 

tests/unit/test_thinking.py

@@ -18,7 +18,7 @@ from polygateway.thinking import (
     register_capability,
     resolve_thinking,
 )
-from polygateway.types import ThinkingObservation
+from polygateway.types import Effort, ThinkingObservation
 
 
 def _warnings():
@@ -125,7 +125,7 @@ class TestThinkingCapability:
         assert get_capability("some-brand-new-model") is None
 
     def test_register_capability_is_pure(self):
-        table = register_capability("x-1", ThinkingCapability(True, "实测"))
+        table = register_capability("x-1", ThinkingCapability((Effort.NONE, Effort.AUTO), "实测"))
         assert get_capability("x-1", table=table) is not None
         assert get_capability("x-1") is None  # 默认表未被污染
 
@@ -175,7 +175,7 @@ class TestResolveThinking:
 
     def test_unknown_shape_beats_capability_check(self):
         """第 2 步先于第 4 步: 形态未知时无从注入,能力如何无关紧要。"""
-        cap = ThinkingCapability(can_disable=False, evidence="构造")
+        cap = ThinkingCapability((Effort.AUTO,), "构造")
         with pytest.raises(ValueError, match="register_provider"):
             resolve_thinking(get_provider("openai"), cap, False, model="whatever")
 
@@ -188,7 +188,7 @@ class TestReconcileThinking:
     """
 
     _CAP = ThinkingCapability(
-        can_disable=True, evidence="2026-08-02 实测 reasoning_effort=none 可关闭"
+        (Effort.NONE, Effort.AUTO), "2026-08-02 实测 reasoning_effort=none 可关闭"
     )
 
     def test_off_but_observed_with_a_registered_capability_blames_the_table(self):
@@ -311,3 +311,80 @@ class TestReconcileThinking:
             )
             is None
         )
+
+
+class TestEffortVocabulary:
+    """八档封闭词汇(设计 §3.1);`auto` 不可省——9 个纯开关型模型无强度档可填。"""
+
+    def test_none_and_auto_are_distinct_members(self):
+        assert Effort.NONE != Effort.AUTO
+        assert Effort("none") is Effort.NONE
+        assert Effort("auto") is Effort.AUTO
+
+    def test_vocabulary_is_exactly_eight(self):
+        assert len(list(Effort)) == 8
+
+    def test_values_are_wire_literals(self):
+        # 档位值直接写进请求体,改名即改变发出去的字节
+        assert [e.value for e in Effort] == [
+            "none",
+            "auto",
+            "minimal",
+            "low",
+            "medium",
+            "high",
+            "xhigh",
+            "max",
+        ]
+
+
+class TestCapabilityTierList:
+    """能力表从 bool 变成档位清单(设计 §3.2);三个派生量不存字段,存了必漂移。"""
+
+    def test_capability_derives_can_disable(self):
+        assert ThinkingCapability((Effort.NONE, Effort.AUTO), "实测").can_disable is True
+        assert ThinkingCapability((Effort.LOW, Effort.MAX), "实测").can_disable is False
+
+    def test_cheapest_effort_skips_none(self):
+        # 「关不掉时的可执行替代」取的是除 none 外最弱的一档
+        assert (
+            ThinkingCapability((Effort.LOW, Effort.HIGH, Effort.MAX), "实测").cheapest_effort
+            is Effort.LOW
+        )
+        assert (
+            ThinkingCapability((Effort.NONE, Effort.HIGH, Effort.MAX), "实测").cheapest_effort
+            is Effort.HIGH
+        )
+        assert ThinkingCapability((Effort.NONE, Effort.AUTO), "实测").cheapest_effort is Effort.AUTO
+        assert ThinkingCapability((Effort.AUTO,), "实测").cheapest_effort is Effort.AUTO
+
+    def test_cheapest_effort_is_none_when_only_none(self):
+        # 只能关不能开: 没有可推荐的「最省的开启档」
+        assert ThinkingCapability((Effort.NONE,), "实测").cheapest_effort is None
+
+    def test_is_tiered_excludes_none_and_auto(self):
+        # 纯开关型模型不该被告知「可选档位」——它没有档位
+        assert ThinkingCapability((Effort.NONE, Effort.AUTO), "实测").is_tiered is False
+        assert ThinkingCapability((Effort.AUTO,), "实测").is_tiered is False
+        assert ThinkingCapability((Effort.LOW, Effort.MAX), "实测").is_tiered is True
+
+    def test_empty_efforts_rejected(self):
+        with pytest.raises(ValueError, match="至少"):
+            ThinkingCapability((), "实测")
+
+    def test_duplicate_efforts_rejected(self):
+        with pytest.raises(ValueError, match="重复"):
+            ThinkingCapability((Effort.LOW, Effort.LOW), "实测")
+
+    def test_glm53_cannot_be_disabled(self):
+        # 三源一致(智谱官方文档/cherry-studio/OpenRouter): thinking.type 只接受 enabled
+        cap = get_capability("glm-5.3")
+        assert cap is not None
+        assert cap.can_disable is False
+        assert cap.cheapest_effort is Effort.LOW
+
+    def test_m2_series_still_cannot_be_disabled(self):
+        # 迁移回归: 旧表用 can_disable=False 表达的事实,新表用「none 不在清单里」表达
+        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