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.
Typed pydantic-settings config, structlog JSON logging with request/trace id
propagation and redaction of phone numbers, tokens and face keys, the unified
response envelope and error-code table from 架构文档 §9.2, async SQLAlchemy
session management, ORM models for the eight foundation tables, and the
OpenTelemetry/Prometheus wiring.
packages/domain stays pure logic -- snowflake ids, the quota three-phase
protocol and the tk_task state machine -- so it can be tested without a
database and is held to mypy strict.
xsl