parththakkar106andClaude Opus 5
1030a7f234
STATUS was written before the deploy and still asked for a VACUUM that has since been run. Replaces that with what was actually verified against the running service, and with the two things a next session would otherwise have to rediscover. The post-vacuum sizes were never measured, so the projection stays a projection; the query to settle it is in the file. And the scroll gap is promoted from a footnote to the one real open item, because re-reading that path after shipping found a bug in it -- which is the argument that reading it again is not the fix. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017Dvvqn9ZDR4ixeFPHNbww7
269 lines
13 KiB
Markdown
269 lines
13 KiB
Markdown
# Where things stand
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Read this first when picking the project back up. Updated at the end of a working
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session; the per-phase plan files hold the detail, this holds the thread.
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**Last updated: 2026-08-17.**
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---
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## The live URL is not the one in render.yaml
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**Production is `https://ai-dnd-1gmp.onrender.com`.** Render appended a suffix to the
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`ai-dnd` service name in `render.yaml`, and plain `ai-dnd.onrender.com` belongs to a
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different, suspended service that answers 503 with "suspended by its owner" — which is
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easy to mistake for this deploy being down. The authoritative link is the one the
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project page points at (`docs/index.html`), not the service name in the blueprint.
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`GET /api/health` on the real host returns `{"ok":true}`.
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---
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## Shipped and live, 2026-08-17
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PRs #1 and #2 are merged and deployed. Verified against the running service:
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`/api/health` 200, the adventure payload carries `action_count`, `/actions` returns
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`{actions, total, has_more}` and accepts `before_id`. The app booting at all is proof
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migrations 42–45 ran — `bootstrap()` executes at import, so a failed migration means no
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service. The deployed JS bundle hashes to `index-4vjcKxkv.js`, which is what this tree
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builds, so the frontend live is exactly this code.
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`VACUUM FULL actions;` has been run. **The post-vacuum sizes were never measured** —
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worth one query next session, and the only reason to touch production again:
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```sql
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SELECT pg_size_pretty(pg_database_size(current_database())),
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pg_size_pretty(pg_total_relation_size('actions'));
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```
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Projection was ~53 MB total against a 512 MB tier, from 99.6 MB. If it did not land
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near that, the vacuum did not reclaim what it should have and that is worth knowing
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before the tree adds columns to `actions`.
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**Aggregates only, and ask first.** Real users are on this database. Counts,
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`octet_length` sums and catalog sizes answer every sizing question this project has
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needed; nothing requires reading a row of anyone's story.
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---
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## Pick up here
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**`plan/14-phase-story-tree.md` — the tree itself.** `plan/13` is finished. Its design
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is settled in `plan/14` and nothing about it has been built.
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Two things from the egress work are worth carrying into it:
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- **Paging already anticipates the tree.** `action_window` in `routers/adventures.py`
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anchors on an action id and orders by comparing `Action.index`, never by treating
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index as a position. A branch changes which actions are on the path, not how two of
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them order, so the anchor survives; anything counting offsets would not.
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- **Weigh new columns in bytes.** A tree adds parent/branch columns to `actions`, which
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is already the table that fills the disk. `tests/test_egress.py` has byte ceilings
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now — they will tell you.
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**Before the next deploy:** one `VACUUM FULL actions;` — see below.
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---
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## What happened on 2026-08-16
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Four commits, all on the egress work that has to land before the tree.
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### 1. A byte meter, in the repo this time — `7ee5cee`
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`backend/tools/dbmeter.py` + `backend/tools/stress_session.py`.
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```
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cd backend
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.venv/Scripts/python.exe -m tools.stress_session
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.venv/Scripts/python.exe -m tools.stress_session --shapes turn --repeat 2
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.venv/Scripts/python.exe -m tools.stress_session --no-embeddings # the old blind spot
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```
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It counts **bytes at the DBAPI cursor**, not queries — both egress blowouts this project
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has had were one query fetching a column nobody read, and a statement count showed
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nothing wrong in either. It drives a production-shaped synthetic adventure through the
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real routes with only the LLM and the embedding endpoint faked.
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**The memory bank is ON by default and that is the whole point.** The previous harness
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ran without an embedding model configured; embedding providers are BYOK-only by
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construction, so `retrieve_memories` returned early every time and the heaviest read in
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a turn never happened. `--no-embeddings` reproduces that deliberately — the gap is 29x.
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It calibrates against the two figures measured directly on production: 426.7 kB for a
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200-action page load against 423 KB, and 3,258.7 kB for one turn against 3,153 kB.
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It runs on SQLite, so treat absolutes as production-*shaped* and compare before/after.
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### 2. Packed float32 embeddings — `c568648`
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Migration 38 + `app/vectors.py`. A 1536-dimension vector as a JSON list is ~31 KB; the
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same numbers as float32 are 6,144 bytes. **Not a precision trade** — the endpoints
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compute in float32 and render that into JSON, so converting back is bit-exact. Nothing
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re-embeds, no API calls.
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The backfill is the one in `migrations.py` that cannot be portable SQL, so it comes
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through Python, batched. Migration SQL can now be a `{dialect: sql}` map (BLOB vs BYTEA
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have no common spelling).
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### 3. Ranking the bank without reading the bank — `b7e53ae`
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`retrieve_memories` walked `adventure.memories`, loading every row *with its vector*. It
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now asks SQL which memories are in play (an id and a flag per row), ranks against
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vectors held in process, and fetches text only for the top-K it picks.
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Two more callers were doing the same thing, and the production SQL could not see either:
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`_evict_over_capacity` walked the bank to count it, `_embed_pending` walked it to find
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rows with no vector. A played turn cost **6.4 MB**, not the 3.2 the plan assumed.
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| shape | before | cold | warm |
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|---|---|---|---|
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| one turn | 3,258.7 kB | 723.4 kB | **122.3 kB** |
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| `run_post_turn` | 3,139.1 kB | 0.7 kB | 0.7 kB |
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| Insights | 3,223.7 kB | 117.9 kB | 117.9 kB |
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| Memories drawer | ~3.1 MB | 23.7 kB | 23.7 kB |
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A played turn is turn + post-turn: **6.4 MB → 123 kB**, 52x.
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Migrations 39/40 add `memories.embedded`, migration 41 drops the capacity default
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200 → 80 for rows still on the old default.
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---
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## What happened on 2026-08-17, part two
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Everything left open in `plan/13` closed, plus two bugs that fell out of doing it.
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| shape | before today | after |
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|---|---|---|
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| page load, 600 actions | 606.0 kB | **62.6 kB** — and no longer grows with the story |
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| adventures index, 6 fat adventures | 469.7 kB | **0.3 kB** |
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| `context_snapshot` on disk | ~89 MB | ~43 MB (3.5x, after a VACUUM) |
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| database total | 99.6 MB | ~53 MB projected |
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**One follow-up after the merge** (PR #2). Prepending older actions changes `actions`,
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and the bottom-pinning effect watches `actions` — so unless a scroll had already
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un-pinned the view, loading earlier turns jumped to the newest one instead. A prepend
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now clears the pin explicitly. Found by re-reading the path, not by running it.
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**The story is a window now.** `GET /adventures/{id}` returns the newest 60 actions and
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`action_count`; older pages come from `GET /{id}/actions?before_id=`. Anchored on an
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action, never an offset — an offset counted back from the newest shifts every older
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position the moment a turn lands, which is exactly when someone is scrolling. `Play.jsx`
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prepends and restores scroll position in a `useLayoutEffect`, before paint.
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**`context_snapshot` is compressed** (migrations 43–45, `app/compression.py`) via a
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TypeDecorator, so every call site still reads and writes a dict. Verified end to end on
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a throwaway Neon database: 720,864 B of JSON to 204,293 B of bytea, every row equal.
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**The JSON vector column is gone** (migration 42) — and dropping it exposed that
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changing your embedding model had silently stopped re-embedding the bank since
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migration 38. The settings route cleared the dead column and left `embedded` true, so
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`_embed_pending` never saw those rows and retrieval kept ranking against the old
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model's vectors. Nothing reported it: `cosine` returns 0.0 on a width mismatch.
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`tests/test_embedding_model_switch.py`.
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**Byte ceilings exist** (`tests/test_egress.py`), including one test whose only job is
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to prove the ceilings would catch something.
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**List responses name their columns.** The index was loading whole Adventure entities —
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seven text and JSON columns, ~15 kB a row — to render a title and a snippet.
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## What happened on 2026-08-17, part one
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No new behaviour — a verification pass on what shipped the day before, because every
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number in the section above had been measured on SQLite against a synthetic fixture.
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Full write-up in `plan/13` under "Verified on production".
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**It holds.** `schema_version` is 41 on the live Postgres with `embedding_blob bytea`
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and `embedded boolean` present, so migration 38's dialect map is correct against a real
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server. The backfill is complete (134/134). The packed vectors are **5.04x** smaller
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than the JSON on real data — 30,971 → 6,144 bytes a memory, as predicted.
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**SQLite was not lying.** `tools.stress_session` can now target Postgres via
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`AIDND_STRESS_DATABASE_URL`, and every shape agrees within 0.5% — the warm turn is
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121.1 kB on Postgres against 122.3 kB on SQLite, with `memories` down to 1.7 kB of it.
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Run it against a **throwaway** database only; the harness writes, so it refuses any
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target whose name does not contain `stress` or `scratch`.
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**Two corrections came out of it**, both above: the page-load model has the wrong
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shape (too heavy per action, far too short), and the storage ceiling was never costed.
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## Things worth remembering
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**The vector cache needs no invalidation callbacks, and that is why it is safe.** A
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stored vector can only change through `memorybank.set_vector`, which drops that one
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entry. Anything that *removes* a memory from play — eviction, deletion, pruning, an edit
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clearing the vector — falls out of the catalogue query, and entries missing from the
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catalogue are dropped on the next read. So there is no hook anyone can forget to call.
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It is in-process and assumes one worker, which is what the deploy runs.
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**Weigh new columns in bytes, not rows.** The comment on `Memory.embedding` said "fine
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at bank sizes of a few hundred" and was wrong by the only measure that mattered: a few
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hundred JSON vectors is ten megabytes, fetched fresh every turn.
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**A deferred column needs a cheap flag beside it.** `memories.embedded` exists because
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once the vector is deferred, every "is this embedded?" check becomes a 6 KB lazy load,
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once per row down the Memories drawer. Exactly the same shape as `actions.variant_count`
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beside `actions.variants`. Expect to need this for any future heavy column.
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**Any egress measurement must run with an embedding model set.** This is the second
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time that omission has hidden the biggest number in the room.
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**Production has real users on it now. Measure it without reading it.** Counts,
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`sum(octet_length(...))` and `pg_total_relation_size` answer every sizing question
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asked so far, and none of them return anyone's story, memory text or email. When a
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real Postgres is needed for a *write* path, create a throwaway database beside the real
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one and drop it after — never point a harness at the production database.
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**`octet_length` is the egress number, not the on-disk number.** Postgres TOAST
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compresses big JSON — `context_snapshot` is 150.8 MB uncompressed but ~89 MB stored —
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and decompresses before sending. Size reads with `octet_length`, size the storage bill
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with `pg_total_relation_size`, and do not mix them up.
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---
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## `plan/13` is closed
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All six of its open items landed on 2026-08-17, and are live. What is left is not from
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that plan:
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- **Nothing has ever exercised the scroll in a browser.** This is the one real gap, and
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it has already cost something: re-reading that path after shipping turned up a bug
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where loading earlier turns scrolled *past* them to the end of the story, worst on
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the short-window case the button exists for (fixed, PR #2). One bug found by reading
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means reading is not a substitute. Either scroll a long adventure by hand, or add a
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vitest + jsdom harness — that would have caught this one. jsdom has no layout, so the
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scroll-position arithmetic still needs eyes.
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- **`ACTION_PAGE = 60` is a guess.** It should be a page or two of reading. If loading
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older turns feels like it interrupts, that is the number to move
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(`routers/adventures.py`).
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- **Post-vacuum sizes unmeasured**, above.
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- **Anyone who switched embedding models has a stale bank.** The bug is fixed, but
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those memories only re-embed as the post-turn pass reaches them, which costs an
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embedding call each. Nothing forces it; playing does.
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Deliberately not taken: moving `context_snapshot` out of the database entirely
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(compressing it bought the same runway for a much smaller change), and pgvector (breaks
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the SQLite dev parity this codebase protects on purpose).
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---
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## Running things
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```
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cd backend
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.venv/Scripts/python.exe -m pytest tests/ # 259 tests
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.venv/Scripts/python.exe -m tools.stress_session # egress report (SQLite)
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# Same harness against a real Postgres. The target must be a THROWAWAY database
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# — this writes a synthetic adventure, and it refuses any name without
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# 'stress'/'scratch' in it.
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AIDND_STRESS_DATABASE_URL=postgresql://…/stress_scratch \
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.venv/Scripts/python.exe -m tools.stress_session
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```
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On Windows the report's box-drawing characters crash the default cp1252 console;
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prefix with `PYTHONIOENCODING=utf-8`.
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Port 8000 is shared with the job-pipeline app, which will squat it and silently shadow
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the AI-DnD API — free it before running the backend, or move the vite proxy.
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