resolve_thinking now takes an Effort instead of a tri-state bool, and the
four gates become five. The new one sits ahead of the generic tier check
on purpose: asking for `none` on GLM-5.3 used to fall through to "none is
not supported, pick low/high/max", which loses both the fact that the
model cannot stop reasoning and the one tier the caller could switch to
right now. Without that alternative, downstream goes looking for
extra_body — which is how issue #20 happened in the first place.
The return type is a ThinkingResolution rather than the payload alone.
Under fallback="nearest" the tier that goes out is not the tier that was
asked for, and telemetry has to record the one that ran, or task 10 files
a call under a tier it never used. Ties in that mapping go to the weaker
side: a silent medium -> max is a multiple of the bill, and the library
does not raise a caller's price on its own.
Two readings the design left implicit, both settled the way its own
compatibility promise requires:
- `auto` is exempt from the tier list. It means "on, no tier named",
which in the body is the absence of the effort key, not a value of it.
Checking it against the list would break every existing source that
sets ENABLE_THINKING=true against deepseek-v4 or glm-5.3.
- `none` is never a mapping target. Turning "think less" into "do not
think" reverses the decision instead of cheapening it; a switch-only
model maps to `auto` and a model that only has `none` still errors.
Both call sites convert enable_thinking in place for now; task 5 folds
that into effective_effort along with the source- and call-level tiers.
Three of them were the same shape as the bug this branch exists to fix:
something goes wrong, the library swallows it, and the caller is left
with a number that means the opposite of what happened.
The throttle key had no source in it. Five sources on one model is the
normal case here, so the first one to break would warn once and silence
the other four for the life of the process, and the message never said
which gateway to look at.
An unknown verdict in a cached entry threw away the whole response. The
rehydrator tolerates unknown fields but not unknown values of a known
field, so two library versions sharing a Redis would each invalidate
the other's entries: halved hit rate, and the only log line says the
cache rebuild failed. A purely observational field should not be able
to void a response whose content is intact.
Normalising for telemetry now degrades instead of raising, both for a
bare string and for a value outside the domain. Either one used to
reach the same except and cost the whole row, which is exactly how
1.3.0 lost nineteen calls without anyone noticing.
The M3 evidence sat at 08-02 for twenty-three days while nobody could
tell whether it still held. A declaration that goes stale in silence is
the failure this issue is really about, so the library now compares
what it declared against what it just observed and says so when the two
part ways.
Judgement is separated from logging: reconcile_thinking returns the
warning text, so tests assert on the text instead of parsing logs.
Two cases that look alike are kept apart — a model whose capability is
registered gets a drift warning quoting its evidence, an unregistered
one is never told the table said anything, because it never did.
False x UNKNOWN stays silent on purpose. UNKNOWN cannot falsify
anything, and warning on it would fire on every disabled call M3 makes
over the plain endpoint. A warning that always fires is not a warning.
Both assembly paths fill it, streaming and non-streaming alike. Filling
only one is exactly the divergence this issue exposed: M3 returns
reasoning prose over SSE and nothing at all over the plain endpoint, so
a verdict computed on one path says nothing about the other.
The field defaults to UNKNOWN on both TransportResult and LLMResponse.
A transport that does not judge should not get to declare absence on
the provider's behalf, and a default that stays silent is the only one
that cannot lie.
providers.py had been holding two jobs: the registry of what each
provider looks like, and the decisions made from those declarations.
Adding response-side judgement would have made it the module for
everything about reasoning, so the decisions move to thinking.py and
the registry keeps only profiles and their lookup.
Moving a module breaks any deep-path import of what moved, so the six
public symbols are promoted to the package root at the same time. The
top level is this library's stated API surface; giving downstream a
stable name to import is what makes the next reorganisation harmless.
observe_thinking stays unexported — downstream reads the verdict off
LLMResponse, and exporting it would be a permanent promise for nothing.
Issue #10 Task 3: five branches each built their own message, so adding
the summary would have meant five copies. Table-driven classification
composes it in one place instead, and the 429 split still parses the
untruncated body - reading the summary would demote an oversized
insufficient_quota to a plain rate limit and stop force_open.
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.
enable_thinking=False was a no-op for minimax and openai sources: both
profiles had empty dicts on each side, so the payload update injected
nothing while the caller believed reasoning had been turned off. A
downstream project was blocked on exactly this.
The root cause is that an empty dict meant two different things -- "no
injection needed" and "we do not know how this provider spells it" --
and that a provider-level table cannot express what turned out to be a
per-model property. Live testing showed MiniMax-M3 can disable
reasoning via reasoning_effort while M2.7 and M2.5 cannot be disabled
at all, which two external registries independently confirm.
So the shape stays at provider level and a capability table joins it at
model level. Unknown, unsupported and no-opinion are now three distinct
values, and resolve_thinking is the single place they meet: it raises at
assembly time when a model cannot honour the request, warns and injects
for unregistered models, and injects silently otherwise. Every registered
capability carries the evidence it was derived from.
enable_thinking also joins the cache fingerprint, since it now really
does change the request body.
Reasoning tokens are already counted inside completion_tokens, so the
cost total was never wrong -- what was missing is the attribution: how
much of a call was spent thinking rather than answering.
LLMResponse and TransportResult each gain a trailing reasoning_tokens
field, and the telemetry port grows from 21 to 22 columns with the new
column appended in both backends so fresh and migrated schemas keep the
same physical order.
None means this particular call did not report the field, not that the
source never reports it: a relay that falls back to a local tokenizer
replaces the whole usage object and drops completion_tokens_details.
Downstream checks must therefore read "in (None, 0)"; no provider was
observed reporting a literal zero.
Classify empty completions as transient per human ruling (fixes flaky
real-gateway smoke and prevents caching empty responses), rename the
factory injection parameter gate to breaker per the frozen design,
rewrite the probe-entry cleanup without except BaseException, declare
python-dotenv explicitly, add a mid-backoff cancellation test, and
record all implementation errata in the design and architecture docs.
Includes config aggregation for multi-source env keys, from_env and
from_settings factories with explicit shared-backend injection,
gather_bounded, top-level exports, tightened import-linter layers with
the gate removed from the Makefile, and the finalized .env.example.
iomgaa