record_message_usage

Record usage attached to one streamed model message.

A request is entered in recorded_requests only once usable token metadata has been recorded for it. Callers retain that ledger across stream rounds so one API call stays one row, however its usage arrives.

A streamed chunk and a completed message report usage differently, so they are handled differently. A completed AIMessage carries the request's whole usage and is idempotent: replaying it must not count twice. A chunk carries whatever the provider chose to emit at that point in the stream -- Anthropic and OpenAI attach the full usage to one chunk, while Google emits an incremental delta on every chunk, which the consumer is expected to sum. Skipping a chunk whose ID was already seen would drop every Google chunk after the first, losing most of the request's output tokens and cost.

Summing them as separate requests would be wrong in the other direction, so a later chunk instead revises the request already recorded: its earlier contribution is retracted and re-recorded with the running totals. One API call therefore counts once, with one per-model row, no matter how many chunks carried its usage. Google also names the model only on its final chunk, so the model is upgraded when a message supplies one and otherwise left alone -- without that, one call would straddle a fallback-model row and a real-model row.