Milestone 422 step 5. `docker compose -f docker-compose.single.yml up -d`
gives three containers — FabledCurator, Postgres, Redis — where the stack
previously needed seven.
THE MULTI-SERVICE STACK IS KEPT. docker-compose.yml still runs the five app
services separately and remains the right shape for a Swarm deployment spread
across hosts, where per-service rolling rollback and placement constraints
matter. This adds a compose file; it deletes none.
`entrypoint.sh all` GENERATES the supervisord config from worker_lanes.LANES
and execs it as PID 1. Generated rather than checked in because a static
.conf would spell out each lane's -Q list, making a FIFTH hand-kept copy of
the queue names — after celery_app.task_routes and the three collapsed in
steps 1, 2 and 4. Every one of those had already drifted when found.
Generating gives a stronger guarantee than "they match today": a lane added
to LANES gets a process, and a queue cannot end up with no consumer because
someone missed a file.
supervisord over s6-overlay: one pip dependency on an image already Python,
with per-program stop timeouts and stopasgroup. The process-group part is not
a detail — celery's prefork pool forks children, and a TERM reaching only the
parent leaves them orphaned holding tasks. s6's advantage (PID-1 signal and
zombie handling) comes from `init: true` instead. Nothing in FC talks to the
supervisor, so the choice is reversible without touching product code.
FOUR LANES, NOT FIVE. The ml lane is skipped: torch and the ML requirements
live only in Dockerfile.ml until step 6 merges the images, so an `ml` program
here would fail to import on every restart forever. `--with-ml` is the flag
step 6 turns on.
THREE BUGS FOUND BY READING IT BACK, none of which the first tests caught:
1. `environment=CELERY_QUEUES=default,import,thumbnail,download` — supervisord
parses that key as a COMMA-separated list, so it reads as
CELERY_QUEUES=default plus three malformed entries and the worker lane
would have consumed only `default`. Silent: the worker starts, reports
healthy, never picks up an import. Now quoted, and the test asserts the
quoted form rather than the bare substring, which passed either way.
2. The generator emitted `entrypoint.sh <lane.name>`, but `maintenance_long`
is not a role — compose runs it as the plain `worker` role with different
queues. Lane now carries `entrypoint_role`, and a test reads entrypoint.sh
to assert every role a lane names actually exists.
3. The `scheduler` role hardcoded --concurrency=1, ignoring CELERY_CONCURRENCY.
Harmless while only compose started it and set none; with a generated value
being passed, the lane would have sat at 1 until the reconcile noticed,
with nothing saying why.
The healthcheck asserts BOTH halves — hypercorn answers and every configured
lane is answering the broker. That is the failure mode consolidation creates:
docker can no longer see the lanes as separate services, so a web-only check
would report a healthy container with every lane inside it dead. It
deliberately ignores the `enabled` flag: a disabled lane still has a running
process with its consumers cancelled, and marking the container unhealthy for
turning tagging off would be wrong.
stop_grace_period 200s, sized to the slowest lane (maintenance_long at 180s)
rather than the average, with a test asserting no program's stopwaitsecs can
exceed what compose allows.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR
The image library is on a CIFS/SMB share (mounted rsize=4 MiB, actimeo=1), and
Quart's FileBody streams in 8 KiB chunks — so serving one large original was
~19k network round-trips to the storage server, i.e. 30–58s per download
(operator-flagged). That's what starved the GPU agent (constant "curator
unreachable" backoff) AND slowed the browser: every byte is read off CIFS and
streamed through the Python app (no reverse-proxy sendfile), and only 2 hypercorn
workers meant the agent + the browser's thumbnail grid queued behind each other.
In-container fix, no new service:
- Raise FileBody.buffer_size 8 KiB → 4 MiB in create_app, matching the mount's
read size: one round-trip per read, ~500× fewer. buffer_size is the MAX read so
small thumbnails still read in one gulp, and Range/mime/ETag/conditional
handling lives on Response — all preserved. Guarded so a Quart-internal change
can't break boot.
- HYPERCORN_WORKERS default 2 → 4 so concurrent /images requests stop queuing.
Expected: large-file transfers drop from ~40s toward link speed (a few seconds)
for the agent and the browser. See issue #1223.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
import_media_file now enqueues tag_and_embed alongside generate_thumbnail
after a successful import. scripts/download_models.py snapshots Camie +
SigLIP into /models, idempotent (skips when present). The ml-worker
entrypoint runs it before starting the Celery worker so a fresh /models
volume self-heals on first boot. Downloader tests are pure-logic (no
network in CI).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Multi-stage build: node:20 builds the SPA, python:3.12-slim runs the app.
Same image handles web, worker, scheduler roles via entrypoint.sh's first
arg. ffmpeg + unar are baked in for FC-2's transcode + archive paths.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
bvandeusenandClaude Opus 5