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.
Chat rows stored full message and response text with no upper bound, so
downstream contracts and tenders lived in llm_calls indefinitely. Add
_cap_text/_cap_messages in the single telemetry exit (_record), applied
after digest_messages and before json.dumps, plus to response/thinking.
Capping is per text, not over the serialized JSON: cutting the whole
string would emit invalid JSON into an unvalidated TEXT column. The cap
builds new dicts and never mutates in place — digest_messages passes
non-list content straight through as the same object, so an in-place cut
would silently poison the caller's messages and the cache key.
text_cap is required on TelemetryEmitter (internal class, three known
construction sites) and defaults to None on the three public clients, so
the default behaviour stays byte-for-byte identical. Settings wiring
lands separately.
Verifier mutation test: flipping _translate_429 to parse the summary
left all 824 tests green. The padding was one long string value, so the
cut landed inside it - and head-and-tail retention kept the trailing
error object, leaving the summary parseable. Many keys put the cut
between structural tokens, where the summary stops being valid JSON.
Mutation now fails as it should. Also splits OCR 429 out on its own.
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.