* fix: omit temperature for OpenAI reasoning models (o1/o3/o4/gpt-5)
These models only accept the default temperature; sending any explicit
value (even 0.0) returns HTTP 400 "Only the default (1) value is
supported". This broke two paths:
- Endpoint probing in _probe_single_model hardcodes temperature: 0.0, so
a perfectly valid o3/gpt-5 endpoint is reported as failing in the
Model Endpoints health check.
- Chat/stream payloads send temperature unconditionally, so a non-default
temperature preset 400s on these models.
The code already special-cases the same model family for
max_completion_tokens, so this adds a sibling _restricts_temperature()
helper and omits the field for those models, letting the API use its
required default. gpt-4.5 is intentionally excluded (not a reasoning
model; accepts temperature normally).
Adds tests/test_llm_core_temperature.py covering the predicate and the
synchronous payload builder.
* fix: also omit temperature for reasoning models on the direct-POST paths
The first commit only covered llm_call/llm_call_async/stream_llm and the
endpoint probe. Email auto-summary, urgency-less spam classification, the
email reply-summary endpoint, and gallery vision tagging build their
OpenAI payloads inline and POST them directly (requests/httpx), bypassing
llm_core — so a reasoning model configured there would still 400 on the
temperature field. These sites already branch on _uses_max_completion_tokens,
so they're the same class; added the matching _restricts_temperature guard.
gallery_routes also gains the max_completion_tokens branch it was missing,
so gpt-5 vision tagging works end to end.
Note: email_pollers urgency scoring goes through llm_call_async and was
already covered.
934bca9e48