The free-tier 5 GB/month network transfer allowance ran out, which blocks
connections outright. The database is only ~55 MB, so 5 GB meant the whole
thing was being pulled roughly 90 times over.
Cause: actions is 39 MB of that 55 MB -- 541 rows at ~74 KB each, almost
entirely context_snapshot, which stores the whole assembled prompt for a
turn. Every adventure load and every turn fetched all of it in order to
read two small things out of it: the world-change chips under an AI
message (Action.world_changes) and the emit block re-attached when
replaying history to the model (_history_text). The Insights viewer is
the only consumer that wants the whole snapshot, and it asks for one
action at a time.
Lifts that slice into its own small actions.world_delta column
(migration 36) and marks context_snapshot, state_before and
world_state_before deferred, so they load only when something touches
the attribute -- Insights, undo and retry, all single-action paths.
The backfill runs server-side, dialect-specific (json_extract on SQLite,
#> on Postgres), because pulling 39 MB of snapshots into Python to
rewrite a slice of each would defeat the purpose.
Measured at production shape (541 actions, 72 KB snapshots), one
adventure load goes from 38.46 MB to 0.20 MB. The traffic that consumed
5 GB would now be about 27 MB.
Deliberately not included: limiting the history query to recent actions,
and removing the redundant db.refresh(adventure) calls. Both were sized
against the old numbers; against a 0.20 MB load they would take ~27 MB a
month down to ~10 MB, which is not worth the complexity.
tests/test_egress.py hooks before_cursor_execute and asserts the emitted
SQL never names the deferred columns during a bulk load, so this cannot
regress silently. 123 tests pass.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UeQVy5bEjLhfgWNc27Efet
