Files
interactive-story/plan/STATUS.md
T
parththakkar106andClaude Opus 5 c7b6a46a8a Write down what SP2 found, and what it measured
Trust the statement count, not the stopwatch: this machine's suite timings
drift about 20% between runs, so the branch-read regression is recorded as
201 SELECTs -> 2 rather than as seconds.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017Dvvqn9ZDR4ixeFPHNbww7
2026-08-18 19:14:07 +05:30

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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, SP3 — memories and the summary attach to nodes. SP0 (the regression contract and the --rich fixture), SP1 (schema, migration, and the writer that keeps new rows on the tree) and SP2 (the branch clause: every action read now selects on (branch_id, depth) through app/context/lineage.py) are done and green; nothing is deployed yet. SP3 turns memory_cursor/summary_cursor from positions in a shifting list into node anchors, and deletes the cursor-position machinery that goes with them — position_of_index, note_action_removed, _rewind_cursors_to_index, prune_dangling_memories. settled_story_actions and the holdback stay until SP4: they exist because retry mutates a row in place, and retry stops doing that in SP4, not in SP3. Deleting them early reopens the exact bug they were written for.

The schema is live in code but not on production. When SP1 ships, the deploy needs one VACUUM FULL actions; on the direct (non--pooler) endpoint afterwards — it rewrites every row. See the 144 MB lesson at the top of this file.

Two things to carry into it:

  • Every action read goes through context/lineage.py. A memory read has to as well — the same Path builds a clause over Memory — and it reads the full lineage, not a window: retrieval is long-range recall and cannot be windowed. It stays affordable because memories are sparse, so assert the byte cost on a deep fork.
  • Weigh new columns in bytes. actions is already the table that fills the disk. tests/test_egress.py has 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 five — the tree, SP2

Every read of an action now goes through one module. app/context/lineage.py turns a branch's stored lineage into the OR-of-ranges that is "this story", and history, paging, the newest-action lookups, the index screen and the scripting history API all select through it. Ordering moved from index to depth. 317 tests green, and the SP0 baseline still passes unmodified, which was the pass condition. Branch sp2-branch-clause.

Three things to carry forward:

  • A read-side invariant needs a write-side floor. From SP2 a row without a branch is a row no read can see, and it fails by disappearing. Wiring every writer was not enough, because the SP0 baseline and eleven other fixtures write actions straight to the database and never call place_action — and the baseline may not be edited. tree.place_new_nodes now runs from Session.before_flush, so nothing can be written unplaced. That is a better invariant than the one SP1 shipped, and it was the contract that forced it.
  • The SQLAlchemy identity map is weak, and that is a performance cliff. Resolving the head branch once per node re-read the row from the database for every node in a flush — 201 SELECTs to write 200 actions, and a 25 % slower suite (36 s → 45 s, back to back). Nothing about the results changed; only a stopwatch could see it. Hoist the lookup out of the loop and hold the reference for the length of the call: 2 SELECTs, and the suite back within noise of SP1. Pinned by a test that counts the reads rather than the seconds — this machine's timings drift ~20 % between runs.
  • Clause count is bounded by the window, and it is now measured. A story forked 20 times reads its newest 32 actions naming one branch, for 1.07× what an unforked story of the same length costs. Reading the tail widens the lineage only when a deleted action leaves the estimate short.

The 600-action --keep fixture — a genuine pre-tree database — was migrated and then driven over HTTP: index 1,840 B, page load 64,149 B (both unchanged), and scrolling to the start took 9 pages and saw every action exactly once.

What happened on 2026-08-17, part four — the tree, SP0 and SP1

No behaviour change, and none intended: a linear story is a tree with one branch, so every adventure reads exactly as it did. 297 tests green (259 before the phase started, 283 with SP0's contract, 297 with SP1's migration tests).

SP0 built tests/test_story_tree_baseline.py — 24 tests driving the product over HTTP, asserting only on API responses — and tools.stress_session --rich, a correctness fixture beside the scale one. Both on branch phase-14-story-tree.

SP1 put the tree in the schema, on branch sp1-tree-schema: a branches table, branch_id/depth on actions and memories, head_branch_id/head_depth on adventures, migrations 46–52 with a server-side backfill, and app/tree.py for the write side. Nothing reads any of it yet. Four things worth not rediscovering:

  • A schema needs its writer in the same subphase. No migration will ever visit a row written after it ran, so columns backfilled today and populated-on-write next week leave a hole exactly the width of one deploy. app/tree.py stamps every new node, including the ones seed_demo.py and the stress fixture write — a fixture built by create_all is stamped LATEST and no migration ever touches it.
  • SQLite will not drop a column a foreign key names. Two tests simulated an old database by rewinding the stamp while create_all left the new columns in place; that works until the next ADD COLUMN lands, and then it fails on a duplicate column. Every ADD COLUMN migration is now idempotent (migrations._column_already_there), which is the IF NOT EXISTS SQLite has no syntax for. A true pre-migration fixture has to drop and rebuild the tables from frozen DDL, which is what test_tree_migration.py does.
  • Two mutually-referencing tables cannot both carry the foreign key. create_all refuses to order the cycle, and its escape hatch (use_alter) needs an ALTER SQLite does not have. adventures.head_branch_id is a plain integer and a documented cache.
  • The suite went 20 s → 38 s, and it is not the app. One new table plus one index adds ~47 ms to a create_all/drop_all pair on SQLite (DDL fsync), and nearly every test does one. Measured, not guessed. Egress is unmoved: branches is 0.1 kB of a 733.5 kB turn, and the page-load and index shapes are byte-identical to the numbers above.

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. --keep stamps PRAGMA user_version to LATEST_VERSION.
  • The fixture's user is a registered one. In local mode get_current_user() looks for the row with email IS NULL and is_guest false, 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: --keep builds 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 = 60 is 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/          # 297 tests (~38s)
.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.

A fixture to check correctness against, rather than bytes. The measuring fixture leaves every column it does not weigh at its default, which turns out to be exactly the set a story tree has to migrate — state_before/world_state_before NULL on all 600 rows, no RPG scenario, no adventure scripts, both cursors 0, and retry attempts whose text is byte-identical with variant_index always 0. --rich fills in those and only those:

cd backend
.venv/Scripts/python.exe -m tools.stress_session --rich --actions 30 --memories 12

Prefer it small — it exists for variety per row, not for rows. Its byte figures are not comparable to a plain run, and it does not replace the scale fixture, which still holds the egress ceilings.

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.