fix: address the independent verification findings (issue #5, #6)

The verifier caught that the disable-direction evidence only proved "no
regression", not "actually took effect": on M3 the disabled runs and the
no-opinion baseline are identically distributed, because that model does
not reason by default anyway. So the disable runs alone cannot rule out
the very failure mode issue #5 is about -- the parameter being silently
dropped upstream. The bogus-value experiment that does rule it out was
sitting in the findings document instead of the test suite; it is now
case L3b, and the L3 assertion that could never fail is gone.

Also from the review: the e2e helper caught bare Exception, which would
have disguised a library bug as an unavailable source, exactly the
silence the reporting discipline exists to prevent; the unregistered
model warning fired on every request instead of once per source; and the
transport caught ValueError broadly enough to mislabel unrelated errors,
now narrowed to a dedicated ThinkingUnsupportedError.

The design and plan still described the original judgement criteria,
which the measurements had already overturned. Both now match what the
tests actually do, and the design no longer claims the only new failure
surface is the openai one -- dissect configures MiniMax-M2.7 with
ENABLE_THINKING=false and will fail at assembly, which has to be
coordinated before this merges.
This commit is contained in:
2026-08-02 07:40:06 -04:00
parent 4c135075b3
commit 48805cb9fb
7 changed files with 155 additions and 26 deletions
@@ -71,6 +71,10 @@ date: 2026-08-02
**结论:M2.x 的推理是模型固有属性,不是参数没找对。** 任何库层改动都无法让它关闭;唯一诚实的做法是如实报错。
### 2.4 M3 的稳定性
同一请求打 10 次,`(prompt_tokens, 是否上报 ctd)` 全部为 `(194, False)`,零跳变——`enable_thinking=False` 的修复可以建立在 M3 上。
### 2.5 输出长度不是有效判别量(2026-08-02 e2e 补测,各 15 轮)
初版判据用 `completion_tokens` 阈值区分推理开关,被自己的数据证伪:
@@ -86,10 +90,6 @@ date: 2026-08-02
另有一个不含魔数的确定性锚点:同一模型上关闭档的 `prompt_tokens` 严格小于开启档(实测 194 < 207),因为供应商在开启时向模板注入了推理指令。这是相对比较,供应商改模板也不会失效。
### 2.4 M3 的稳定性
同一请求打 10 次,`(prompt_tokens, 是否上报 ctd)` 全部为 `(194, False)`,零跳变——`enable_thinking=False` 的修复可以建立在 M3 上。
## 3. qwen / deepseek:现有 profile 正确
| 模型 | `enable_thinking=false` | `thinking:{disabled}` | `reasoning_effort=none` | 现有 profile |