The harness already built a production-shaped 600-action adventure and then
threw it away with the temp file. The one open gap in plan/13 is that nothing
has ever driven the scroll in a browser, and part of why is that there was
never a long adventure to drive it with.
--keep PATH writes the fixture somewhere durable and makes the app able to
serve it. Two edits are needed for that, both of which cost an hour to
rediscover:
- create_all() builds the current schema but leaves the version stamp at its
default, and bootstrap() reads a populated-but-unstamped database as
ancient — it replays every migration against a schema that already has the
columns, and fails on the first.
- the fixture's user is a registered one, but local mode looks for the row
with email IS NULL and is_guest false, so without clearing the email the
app opens on an empty library.
--keep is read before argparse exists, because where the database lives has to
be settled before app.database is imported. That is the same constraint the
AIDND_STRESS_DATABASE_URL block already lives under. SQLite only; combining it
with a Postgres target is rejected rather than half-honoured.
Verified end to end: the fixture boots with no manual step, action_count 600,
a 60-action first payload, and before_id walks back nine more pages to the
start. Nothing about the default path changed; 259 tests pass.
Claude-Session: https://claude.ai/code/session_017Dvvqn9ZDR4ixeFPHNbww7
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
18 KiB
Where things stand
Read this first when picking the project back up. Updated at the end of a working session; the per-phase plan files hold the detail, this holds the thread.
Last updated: 2026-08-17.
The live URL is not the one in render.yaml
Production is https://ai-dnd-1gmp.onrender.com. Render appended a suffix to the
ai-dnd service name in render.yaml, and plain ai-dnd.onrender.com belongs to a
different, suspended service that answers 503 with "suspended by its owner" — which is
easy to mistake for this deploy being down. The authoritative link is the one the
project page points at (docs/index.html), not the service name in the blueprint.
GET /api/health on the real host returns {"ok":true}.
Shipped and live, 2026-08-17
PRs #1 and #2 are merged and deployed. Verified against the running service:
/api/health 200, the adventure payload carries action_count, /actions returns
{actions, total, has_more} and accepts before_id. The app booting at all is proof
migrations 42–45 ran — bootstrap() executes at import, so a failed migration means no
service. The deployed JS bundle hashes to index-4vjcKxkv.js, which is what this tree
builds, so the frontend live is exactly this code.
Measured 2026-08-17, and then vacuumed again. The earlier VACUUM FULL actions;
predated migrations 42–45, which rewrote every row — so by the time anyone looked, the
database was 144.2 MB, well above the 99.6 MB it started from and nowhere near the
~53 MB projection. Nothing was wrong with the compression. Nothing had reclaimed the
space it freed.
before: database 144.2 MB, actions 131.4 MB
VACUUM (FULL, ANALYZE) actions -- 5.5s
after: database 65.0 MB, actions 52.1 MB
79.2 MB reclaimed in 5.5 seconds, against a 512 MB tier. actions now occupies
52.1 MB holding 50.4 MB of live column bytes, so there is essentially no bloat left.
/api/health answered {"ok":true} immediately after. The projection was right all
along.
Read the sizes from the column sums, not from n_live_tup. The chunk count on the
TOAST relation said ~88 MB live and implied ~40 MB was reclaimable; the actual figure was
double that. n_live_tup is an estimate left over from the last ANALYZE, and after a
migration rewrites the table it is stale in the direction that makes bloat look smaller.
sum(octet_length(col)) per column is the honest number.
Where the bytes are in actions — one column, and it is not close:
| column | rows | live bytes | per row |
|---|---|---|---|
context_snapshot |
467 | 47.5 MB | 104.1 kB |
variants |
91 | 1.1 MB | 12.9 kB |
text |
945 | 0.8 MB | 0.9 kB |
world_state_before |
787 | 0.7 MB | 1.0 kB |
world_delta + reasoning + state_before |
— | 0.2 MB | — |
| total | 50.4 MB |
context_snapshot is 94% of the table. The per-action state columns a tree would touch
are rounding errors, which is the useful thing to know before phase 14 adds more of them:
adding columns beside state_before is cheap; adding anything shaped like a context
snapshot is not.
VACUUM FULL takes an ACCESS EXCLUSIVE lock — the app blocks on actions for the
duration. 5.5 s at this size, but it grows with the table. Run it on the direct
endpoint, not -pooler: through transaction pooling it is unreliable.
Aggregates only, and ask first. Real users are on this database. Counts,
octet_length sums and catalog sizes answer every sizing question this project has
needed; nothing requires reading a row of anyone's story.
Pick up here
plan/14-phase-story-tree.md — the tree itself. plan/13 is finished. Its design
is settled in plan/14 and nothing about it has been built.
Two things from the egress work are worth carrying into it:
- Paging already anticipates the tree.
action_windowinrouters/adventures.pyanchors on an action id and orders by comparingAction.index, never by treating index as a position. A branch changes which actions are on the path, not how two of them order, so the anchor survives; anything counting offsets would not. - Weigh new columns in bytes. A tree adds parent/branch columns to
actions, which is already the table that fills the disk.tests/test_egress.pyhas byte ceilings now — they will tell you.
After any migration that rewrites actions: one VACUUM FULL actions;. That is the
lesson of the 144 MB above — a rewrite doubles the table and only a VACUUM FULL gives
it back. Phase 14's migration rewrites every row.
There is a 600-action adventure to test against now — --keep, below. The tree's
frontend work lands on the same scroll path that has still never been driven by hand, so
drive it before rewriting it.
What happened on 2026-08-17, part three
No behaviour change. A way to get a long adventure in front of a browser, because the one open gap needed a subject and there wasn't one.
tools.stress_session --keep PATH. The harness already built a production-shaped
600-action adventure and then threw it away with the temp file; --keep writes it
somewhere durable and makes the app able to serve it. Two edits are needed for that, and
both are the kind of thing that costs an hour to rediscover:
create_all()does not stamp the schema version.bootstrap()reads a populated-but-unstamped database as ancient and replays every migration against a schema that already has the columns.--keepstampsPRAGMA user_versiontoLATEST_VERSION.- The fixture's user is a registered one. In local mode
get_current_user()looks for the row withemail IS NULLandis_guestfalse, so without clearing the email the app opens on an empty library and nothing owns the 600 actions.
--keep is read before argparse exists (_early_keep), because where the database
lives has to be settled before app.database is imported — the same constraint the
AIDND_STRESS_DATABASE_URL block at the top of the module already lives under. SQLite
only; combining it with a Postgres target is rejected rather than half-honoured.
Verified: the fixture boots with no manual step, action_count 600, the first payload
carries 60 actions, and before_id walks back through 9 more pages to the start — 600
seen, has_more false at the end. 259 tests pass.
Snapshots can be shrunk for this. --snapshot-bytes 2000 keeps the file at ~2.5 MB
instead of ~140 MB. context_snapshot is deferred and never reaches the browser, so it
changes nothing about what scrolling exercises — but do not shrink it when measuring,
where it is most of the point.
Port 8010, not 8000. Covered below, and now printed by --keep itself.
What happened on 2026-08-16
Four commits, all on the egress work that has to land before the tree.
1. A byte meter, in the repo this time — 7ee5cee
backend/tools/dbmeter.py + backend/tools/stress_session.py.
cd backend
.venv/Scripts/python.exe -m tools.stress_session
.venv/Scripts/python.exe -m tools.stress_session --shapes turn --repeat 2
.venv/Scripts/python.exe -m tools.stress_session --no-embeddings # the old blind spot
It counts bytes at the DBAPI cursor, not queries — both egress blowouts this project has had were one query fetching a column nobody read, and a statement count showed nothing wrong in either. It drives a production-shaped synthetic adventure through the real routes with only the LLM and the embedding endpoint faked.
The memory bank is ON by default and that is the whole point. The previous harness
ran without an embedding model configured; embedding providers are BYOK-only by
construction, so retrieve_memories returned early every time and the heaviest read in
a turn never happened. --no-embeddings reproduces that deliberately — the gap is 29x.
It calibrates against the two figures measured directly on production: 426.7 kB for a 200-action page load against 423 KB, and 3,258.7 kB for one turn against 3,153 kB. It runs on SQLite, so treat absolutes as production-shaped and compare before/after.
2. Packed float32 embeddings — c568648
Migration 38 + app/vectors.py. A 1536-dimension vector as a JSON list is ~31 KB; the
same numbers as float32 are 6,144 bytes. Not a precision trade — the endpoints
compute in float32 and render that into JSON, so converting back is bit-exact. Nothing
re-embeds, no API calls.
The backfill is the one in migrations.py that cannot be portable SQL, so it comes
through Python, batched. Migration SQL can now be a {dialect: sql} map (BLOB vs BYTEA
have no common spelling).
3. Ranking the bank without reading the bank — b7e53ae
retrieve_memories walked adventure.memories, loading every row with its vector. It
now asks SQL which memories are in play (an id and a flag per row), ranks against
vectors held in process, and fetches text only for the top-K it picks.
Two more callers were doing the same thing, and the production SQL could not see either:
_evict_over_capacity walked the bank to count it, _embed_pending walked it to find
rows with no vector. A played turn cost 6.4 MB, not the 3.2 the plan assumed.
| shape | before | cold | warm |
|---|---|---|---|
| one turn | 3,258.7 kB | 723.4 kB | 122.3 kB |
run_post_turn |
3,139.1 kB | 0.7 kB | 0.7 kB |
| Insights | 3,223.7 kB | 117.9 kB | 117.9 kB |
| Memories drawer | ~3.1 MB | 23.7 kB | 23.7 kB |
A played turn is turn + post-turn: 6.4 MB → 123 kB, 52x.
Migrations 39/40 add memories.embedded, migration 41 drops the capacity default
200 → 80 for rows still on the old default.
What happened on 2026-08-17, part two
Everything left open in plan/13 closed, plus two bugs that fell out of doing it.
| shape | before today | after |
|---|---|---|
| page load, 600 actions | 606.0 kB | 62.6 kB — and no longer grows with the story |
| adventures index, 6 fat adventures | 469.7 kB | 0.3 kB |
context_snapshot on disk |
~89 MB | 47.5 MB measured (3.2x) |
| database total | 99.6 MB | 65.0 MB measured, after the second vacuum |
One follow-up after the merge (PR #2). Prepending older actions changes actions,
and the bottom-pinning effect watches actions — so unless a scroll had already
un-pinned the view, loading earlier turns jumped to the newest one instead. A prepend
now clears the pin explicitly. Found by re-reading the path, not by running it.
The story is a window now. GET /adventures/{id} returns the newest 60 actions and
action_count; older pages come from GET /{id}/actions?before_id=. Anchored on an
action, never an offset — an offset counted back from the newest shifts every older
position the moment a turn lands, which is exactly when someone is scrolling. Play.jsx
prepends and restores scroll position in a useLayoutEffect, before paint.
context_snapshot is compressed (migrations 43–45, app/compression.py) via a
TypeDecorator, so every call site still reads and writes a dict. Verified end to end on
a throwaway Neon database: 720,864 B of JSON to 204,293 B of bytea, every row equal.
The JSON vector column is gone (migration 42) — and dropping it exposed that
changing your embedding model had silently stopped re-embedding the bank since
migration 38. The settings route cleared the dead column and left embedded true, so
_embed_pending never saw those rows and retrieval kept ranking against the old
model's vectors. Nothing reported it: cosine returns 0.0 on a width mismatch.
tests/test_embedding_model_switch.py.
Byte ceilings exist (tests/test_egress.py), including one test whose only job is
to prove the ceilings would catch something.
List responses name their columns. The index was loading whole Adventure entities — seven text and JSON columns, ~15 kB a row — to render a title and a snippet.
What happened on 2026-08-17, part one
No new behaviour — a verification pass on what shipped the day before, because every
number in the section above had been measured on SQLite against a synthetic fixture.
Full write-up in plan/13 under "Verified on production".
It holds. schema_version is 41 on the live Postgres with embedding_blob bytea
and embedded boolean present, so migration 38's dialect map is correct against a real
server. The backfill is complete (134/134). The packed vectors are 5.04x smaller
than the JSON on real data — 30,971 → 6,144 bytes a memory, as predicted.
SQLite was not lying. tools.stress_session can now target Postgres via
AIDND_STRESS_DATABASE_URL, and every shape agrees within 0.5% — the warm turn is
121.1 kB on Postgres against 122.3 kB on SQLite, with memories down to 1.7 kB of it.
Run it against a throwaway database only; the harness writes, so it refuses any
target whose name does not contain stress or scratch.
Two corrections came out of it, both above: the page-load model has the wrong shape (too heavy per action, far too short), and the storage ceiling was never costed.
Things worth remembering
The vector cache needs no invalidation callbacks, and that is why it is safe. A
stored vector can only change through memorybank.set_vector, which drops that one
entry. Anything that removes a memory from play — eviction, deletion, pruning, an edit
clearing the vector — falls out of the catalogue query, and entries missing from the
catalogue are dropped on the next read. So there is no hook anyone can forget to call.
It is in-process and assumes one worker, which is what the deploy runs.
Weigh new columns in bytes, not rows. The comment on Memory.embedding said "fine
at bank sizes of a few hundred" and was wrong by the only measure that mattered: a few
hundred JSON vectors is ten megabytes, fetched fresh every turn.
A deferred column needs a cheap flag beside it. memories.embedded exists because
once the vector is deferred, every "is this embedded?" check becomes a 6 KB lazy load,
once per row down the Memories drawer. Exactly the same shape as actions.variant_count
beside actions.variants. Expect to need this for any future heavy column.
Any egress measurement must run with an embedding model set. This is the second time that omission has hidden the biggest number in the room.
Production has real users on it now. Measure it without reading it. Counts,
sum(octet_length(...)) and pg_total_relation_size answer every sizing question
asked so far, and none of them return anyone's story, memory text or email. When a
real Postgres is needed for a write path, create a throwaway database beside the real
one and drop it after — never point a harness at the production database.
octet_length is the egress number, not the on-disk number. Postgres TOAST
compresses big JSON — context_snapshot is 150.8 MB uncompressed but ~89 MB stored —
and decompresses before sending. Size reads with octet_length, size the storage bill
with pg_total_relation_size, and do not mix them up.
plan/13 is closed
All six of its open items landed on 2026-08-17, and are live. What is left is not from that plan:
- Nothing has ever exercised the scroll in a browser — still true, but there is now
something to exercise it on:
--keepbuilds a 600-action adventure the app will serve (see 2026-08-17 part three). The subject is no longer the excuse; only the looking is left. This is the one real gap, and it has already cost something: re-reading that path after shipping turned up a bug where loading earlier turns scrolled past them to the end of the story, worst on the short-window case the button exists for (fixed, PR #2). One bug found by reading means reading is not a substitute. Either scroll a long adventure by hand, or add a vitest + jsdom harness — that would have caught this one. jsdom has no layout, so the scroll-position arithmetic still needs eyes. ACTION_PAGE = 60is a guess. It should be a page or two of reading. If loading older turns feels like it interrupts, that is the number to move (routers/adventures.py). One data point: at 600 actions it takes the window plus nine more pages to reach the start, which is a lot of button presses for anyone going back to the beginning.Post-vacuum sizes unmeasured— measured 2026-08-17, and the vacuum that mattered was run then too. 65.0 MB. See the top of this file.- Anyone who switched embedding models has a stale bank. The bug is fixed, but those memories only re-embed as the post-turn pass reaches them, which costs an embedding call each. Nothing forces it; playing does.
Deliberately not taken: moving context_snapshot out of the database entirely
(compressing it bought the same runway for a much smaller change), and pgvector (breaks
the SQLite dev parity this codebase protects on purpose).
Running things
cd backend
.venv/Scripts/python.exe -m pytest tests/ # 259 tests
.venv/Scripts/python.exe -m tools.stress_session # egress report (SQLite)
# Same harness against a real Postgres. The target must be a THROWAWAY database
# — this writes a synthetic adventure, and it refuses any name without
# 'stress'/'scratch' in it.
AIDND_STRESS_DATABASE_URL=postgresql://…/stress_scratch \
.venv/Scripts/python.exe -m tools.stress_session
A long adventure to scroll, instead of a temp file the report discards. The
snapshots are shrunk because they never reach the browser — 2.5 MB rather than 140 MB —
and --shapes list skips the measurement work the fixture does not need:
cd backend
.venv/Scripts/python.exe -m tools.stress_session \
--keep ./scroll_fixture.db --snapshot-bytes 2000 --shapes list
AIDND_DB_PATH=$PWD/scroll_fixture.db \
.venv/Scripts/python.exe -m uvicorn app.main:app --port 8010
cd ../frontend && AIDND_API_PORT=8010 npm run dev # → localhost:5173
Everything in it is synthetic and no real adventure is read. *.db is gitignored, so
the fixture never lands in a commit.
On Windows the report's box-drawing characters crash the default cp1252 console;
prefix with PYTHONIOENCODING=utf-8.
Port 8000 is shared with the job-pipeline app, which will squat it and silently shadow
the AI-DnD API — free it before running the backend, or move the vite proxy with
AIDND_API_PORT, which is what the --keep recipe above does.