ob_ai_call is the only input to V2 pricing, and it was dropping the two
numbers needed to interpret its own cost column.
tokens_reasoning was captured from the provider response but never written to
the table, so the cost of thinking mode was invisible once it left the
process. Folding it into tokens_out was not an option either -- it is billed
at the output rate, and mixing the two hides exactly the difference we now
have to watch.
rate_tier records which price list applied. Without it a row's cost_cents
cannot be rechecked: DeepSeek's peak rate is double off-peak from 2026-08-17,
so recomputing an old row at "the current rate" silently produces a different
answer than what was actually billed.
Migration 0002 adds both columns. tokens_reasoning defaults to 0 rather than
NULL so cost aggregates do not collapse to NULL on historical rows;
rate_tier stays nullable because rows written before this change genuinely
have an unknown tier, and NULL says that more honestly than a guessed 'flat'.
The smoke script now asserts both: reasoning tokens must be 0 (a non-zero
value means a provider default re-enabled thinking mode behind our backs) and
rate_tier must be present. Verified against the real API -- tokens_reasoning=0,
rate_tier=off_peak, 3.9s round trip.
DeepSeek (OpenAI-compatible) as primary with a 智谱 GLM slot that is a real
routing path but raises until the 算法备案 model list is confirmed. Adds scene
routing, failover, a per-provider circuit breaker, structured output with
retry-on-validation-failure, prompts loaded by id+version from prompts/, and
cost attribution written to ob_ai_call for every attempt -- successes,
retries and failures alike.
Two controls exist because they are cheap now and expensive later: a
cache-prefix validator that rejects timestamps, uuids and nicknames in the
cached system prefix (a volatile prefix silently multiplies input cost), and
a hard platform-wide daily budget that rejects non-critical scenes instead of
merely alerting, since a retry storm outruns any human on-call.
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