f8d401029f12c4a9205c5a0cb90083ce79da74b3
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Commits
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f8d401029f |
Stop a turn locking out its own memory bank, and let the long run notice
The first M01 trial with the memory bank on was 26 turns on a GPU host. It
accepted every turn and reported "complete". It also wrote two memories and
no summary, and logged 180 `database is locked` errors, while derived status
still read `idle`.
The cause was a single uncommitted UPDATE. Retrieval bumped each used
memory's counter before the model call, and the turn commits only after the
reply has streamed. SQLite has one writer, so the turn held the write lock for
the whole reply. Every post-turn memory, summary and status write in that
window waited out the five-second timeout and failed. Recording the failure
needed a write as well, and without a rollback first it raised
PendingRollbackError. The loss therefore reached the log and never reached
the status the Insights panel reads, which F08 forbids. The draco run never
hit this because the bank was off there.
- `retrieve_memories` now only reads. `record_use` writes the counters in the
turn's single commit, so a turn that never lands counts nothing.
- The post-turn task's outer handler rolls back before it records a failure.
The harness could not have caught any of this. It read three prompt sections
under names the builder does not use: `memories` (really `used_memories`),
`story_history` (really `history`/`recent_history`), and a `knowledge` prefix
that matched the fixed instruction section instead of the imported passages.
Memory tokens read 0 whatever the prompt held, and the in-history and
in-memories recall checks could never come out true. The labels are now
constants, pinned by a test against a prompt the real builder assembled.
The harness also stops at the first sign of failed post-turn work. It checks
/derived and new server.log lines after every turn, keeps its log position
across --resume, and waits for background work to settle before its final
checks. A run with no memories or no summaries now ends "failed", not
"complete".
Both new application tests fail on
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8c65ae99de |
M2: cut the hosted product away from the local one
94 files, +1,395 -6,578. Three files are new; twenty-four are gone. The milestone is subtraction, and what is left is the single-user local storyteller the specification describes. Removed in full: campaign scripting and its QuickJS sandbox; multi-user accounts, guest sessions, login, registration and the shared demo key; the visitor-analytics tables, dashboard and page beacon; the access log of sign-ins, addresses and devices; per-IP and per-user rate limiting and quotas; Render deployment config; Postgres and psycopg; cloud inference providers, the API-key field and the key encryption that existed to store it; session-cookie signing. None of it was hidden behind a flag — the routes are gone and answer 404. Two things were kept that the brief allowed keeping. The `users` table and its foreign keys stay as an internal ownership detail, because rewriting them out means a migration across most of the schema to delete a column that costs nothing; nothing creates a second user and no request carries an identity. Five inert tables and four inert columns stay for the same reason, so an M1 campaign database opens unchanged. The one addition is app/endpoints.py, which decides where a story may be sent. Loopback, RFC1918, link-local, unique-local and CGNAT — an explicit allowlist of networks, not a guess at what `ipaddress` means by "private", which calls the documentation ranges private and IPv6 loopback reserved. Every address a hostname resolves to must be in it, so a split answer does not squeak through, and the rule runs both when the endpoint is saved and before every outbound request, because a name that resolved to the LAN this morning can resolve elsewhere this afternoon. Known cloud hosts are named in the refusal so the error says why rather than looking like broken DNS. TLS is never traded against it: M1's shared trust context is intact on all four clients and there is no way to skip verification. The hardcoded 120-second model timeout is now a setting. That was not theoretical — on this GPU-less four-core host a cold load of qwen2.5:3b-instruct took 648.9 seconds to produce the first turn, while turns 2 to 5 of the same campaign took 3.6 to 13.1. Connect stays short at 10s so a wrong address still fails fast; the read timeout defaults to 300s and is bounded at 3600, because "wait longer" must stay a number. Two defects found while testing and fixed here. An unknown /api path fell through the SPA catch-all and came back as HTML with status 200, so a client asking for JSON parsed a web page instead of learning the route was gone. And AIDND_CORS_ORIGINS accepted "*", which on an unauthenticated loopback API would hand every page on the Internet a write handle on the campaign database; it now refuses to start. Verified rather than assumed. Offline, on a network with no route out and no DNS: five turns, retry with both takes retained, restart with an identical transcript digest, a failed model call leaving the accepted AI-turn count untouched, and a capture with zero non-loopback unicast packets. Against a real second machine on the LAN over HTTPS with a private CA: four turns, restart, and a capture showing 289 packets to the approved host, 344 loopback, zero anywhere else, zero DNS queries. Cloud and public endpoints refused with their reasons; no API key settable; every removed route 404. 604 backend tests pass, down from 648 by the fifteen retired with the subsystems they tested and up by the twenty-nine added for the endpoint policy and the removed surface. The scripting tests were not deleted: eight files used a JavaScript counter as instrumentation for the state snapshot and rollback machinery, which M2 does not touch, so the counter moved to the world-state engine and those tests still assert what they always did. Frontend lint and build are clean; the image builds, and its wheel-building stage is gone with quickjs. No M3 work. Undo is still destructive and there is still no Redo. |
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32cd7c1077 |
Give the tests one setup instead of thirty-five
Every test module carried the same eight-line prologue redirecting the database to a temp file. Only the first one to be imported ever took effect: `app.database` reads `AIDND_DB_PATH` at import and builds `engine` from it once, so by the time the second module ran the engine already existed. The other 34 copies created a temp file that nothing opened and nothing deleted, and leaked one per module per run. `conftest.py` now does it once, which is early enough because pytest imports conftest before any test module. It also deletes the file when the run ends. The tests still share one database, exactly as they already did: each `client` fixture calls `create_all` on setup and `drop_all` on teardown, so no test sees another test's rows. `tests/fakes.py` holds the one `ScriptedProvider`. Nine modules each had a copy, and the copies had drifted into four feature sets, so a test that needed to raise a provider error had to be written in one of the files whose copy supported that. The shared one is the superset. The two `FakeProvider` copies were the same class with a fixed reply, so they use it too. `test_chat.py` keeps its own, which implements `chat` rather than `generate` and records what it was constructed with. An autouse fixture resets the fake's class state between tests, so a stale reply list can no longer reach the next test. 435 lines out of the suite. 549 tests pass. Verified live by sabotage: breaking the shared fake fails 13 tests across four modules. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014Dix4oGV3njgWRdu7P9t6r |
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e7d75c3b05 |
Rewrite Python comments in Google developer documentation style (#12)
* Rewrite comments in Google developer documentation style Rewrite the comments and docstrings across the backend core modules so they read plainly. The previous prose was accurate but dense and figurative, which made it slow to skim. Applies the Google developer documentation style guide: short sentences, active voice, present tense, American spelling, and no metaphors, idioms, or rhetorical asides. Replaces em-dash chains with separate sentences. |
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2c5909a268 |
Drop the JSON vector column, and fix what was hiding behind it
Migration 38 left memories.embedding in place so a rollback could still find the vectors. Production has since been verified reading from embedding_blob, so migration 42 drops it: 4 MB of a 99.6 MB database holding nothing anyone reads. Removing it surfaced a live bug. Changing your embedding model is supposed to throw the bank's vectors away and let the post-turn pass rebuild them, because two models' vectors are not comparable. The settings route did that by nulling memories.embedding -- correct until 38 moved the vectors, after which it cleared the dead column and left the blob intact with `embedded` still true. _embed_pending filters on `embedded IS FALSE`, so it never saw those rows and the bank went on ranking against the old model's vectors permanently. Nothing would have reported it. cosine returns 0.0 on a width mismatch, so a different-width model scores every memory zero and retrieval returns whichever rows happen to sort first; a same-width model scores plausible garbage. The bulk clear now sets both columns. It stays a bulk UPDATE rather than going through set_vector -- loading the rows is the cost that whole path exists to avoid -- so set_vector's docstring now names it as the one caller that legitimately writes those columns by hand. No cache invalidation is added: clearing `embedded` drops the rows out of the catalogue query, and set_vector evicts each entry as the re-embed puts it back. test_embedding_blob.py now rebuilds the pre-38 schema by hand where it tests the backfill, since create_all no longer produces the column it converts from, and asserts 42 removes it at the end of a full bootstrap -- 38 reads that column and 42 drops it, so an upgrade that reordered them would arrive with an empty bank. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017Dvvqn9ZDR4ixeFPHNbww7 |