Files
FabledCurator/docker-compose.single.yml
T
bvandeusenandClaude Opus 5.5 7a09dc3cda
CI and images / lint (push) Successful in 3s
CI and images / extension-version (push) Successful in 3s
extension / lint (push) Successful in 16s
CI and images / frontend-build (push) Successful in 19s
CI and images / backend-lint-and-test (push) Successful in 31s
CI and images / integration (push) Successful in 2m22s
CI and images / sign-extension (push) Successful in 3s
CI and images / build-web (push) Successful in 3m7s
CI and images / smoke-web (push) Successful in 59s
CI and images / build-agent (push) Successful in 6m41s
CI and images / promote (push) Successful in 2s
build: the agent installs one CUDA-13 stack instead of two, the web image drops ML packages it never imported, and Redis moves to 8 (1451, 1452)
Agent:
- The image ran PyPI's CUDA-13 torch 2.14 and onnxruntime-gpu 1.30 on a
  CUDA 12.9 cudnn-runtime base. requirements.txt had silently replaced the
  Dockerfile's torch 2.6+cu124, because ultralytics pulls torchvision, which
  pulls its own torch. That left ~3 GB of base libraries and a ~3 GB torch
  nothing loaded: 10 GB compressed.
- Now: an nvidia/cuda 13.0.3 `base` image, with torch and torchvision
  installed together from cu130. CUDA and cuDNN come from the nvidia-* pip
  packages; onnxruntime-gpu declares its [cuda,cudnn] extras.
- fc_agent/accel.py preloads those libraries for onnxruntime. It then logs,
  and reports in /status, whether torch and the ONNX CUDA provider actually
  got the GPU, since both fall back to the CPU silently.

Web image:
- Drop opencv-python-headless and onnxruntime, plus the opencv-only apt libs.
  Both have been listed since the scaffold and nothing in backend/ imports
  them.
- torch/torchvision move to 2.14/0.29, and the unexplained caps are lifted
  (rule 154).

Redis: 8-alpine in both compose files and both CI service containers. That
gives an AGPLv3 licence option, where 7.4 was RSAL/SSPL only. The client
moves to >=8.1.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR
2026-09-24 17:45:39 -04:00

105 lines
4.3 KiB
YAML

# FabledCurator in three containers — the install path.
#
# docker compose -f docker-compose.single.yml up -d
#
# Milestone 422 step 5. FabledCurator runs web and every worker lane inside
# ONE container, with Postgres and Redis beside it. How much work each lane
# does is then a dial in the web UI (Settings -> Activity -> Worker lanes),
# live, with no compose edit and no restart.
#
# THE MULTI-SERVICE STACK IS NOT REPLACED. `docker-compose.yml` still runs the
# five app services separately and is the right shape for a Swarm deployment
# spread across hosts, where per-service rolling rollback and placement
# constraints matter. This file is the adopter path: one box, one command.
#
# What consolidating costs, stated here rather than discovered later:
# - Everything shares one host, so there is no spreading work across nodes.
# - Rollback is all-or-nothing; there is no rolling back `web` alone.
# - One stop timeout for the whole container, sized to the slowest lane.
#
# NOT a cost, recorded so it is not rediscovered and raised again: the
# multi-service stack mounts /images:ro on ml-worker and one container cannot
# mount one path two ways. Operator ruled that a non-issue (2026-09-22) — it
# is the same codebase either way.
#
# FabledCurator has no authentication. Whatever can reach ${PORT} is an
# administrator, including over the stored platform session cookies. Do not
# publish this port beyond a network you trust — see "Before you expose it"
# in README.md.
services:
redis:
image: redis:8-alpine
volumes:
- redis_data:/data
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 5s
retries: 5
restart: unless-stopped
postgres:
image: pgvector/pgvector:pg16
environment:
POSTGRES_USER: ${DB_USER:-curator}
POSTGRES_PASSWORD: ${DB_PASSWORD:-postgres}
POSTGRES_DB: ${DB_NAME:-curator}
volumes:
- postgres_data:/var/lib/postgresql/data
# pgvector index builds and the gallery's TABLESAMPLE reads both want more
# shared memory than docker's 64MB default.
shm_size: 512m
healthcheck:
test: ["CMD-SHELL", "pg_isready -U ${DB_USER:-curator} -d ${DB_NAME:-curator}"]
interval: 10s
timeout: 5s
retries: 5
restart: unless-stopped
fabledcurator:
image: git.fabledsword.com/bvandeusen/fabledcurator:latest
# No `command:`. Everything — hypercorn plus one celery process per lane
# under supervisord — is what the image does by default, and supervisord's
# config is generated from the application's own lane table so the two
# cannot disagree. `command: ["all"]` still works and means the same thing.
# Sized to the SLOWEST lane, not the average. maintenance_long runs DB
# backups, library audits and translation backfill, and gets 180s to
# finish a chunk; the lanes stop in parallel, so this covers the max
# rather than their sum. Below this, a routine restart becomes a SIGKILL
# mid-backup — which is recoverable (the work is chunked and idempotent)
# but wastes however long it had run.
stop_grace_period: 200s
# No healthcheck here either. The image declares one that reads the role
# it is running, and for this one that means BOTH halves: hypercorn
# answers AND every lane is answering the broker. A web-only check would
# report a healthy container while every lane inside it had crashed —
# the failure mode consolidation creates, since docker can no longer see
# the lanes as separate services.
environment:
DB_USER: ${DB_USER:-curator}
DB_PASSWORD: ${DB_PASSWORD:-postgres}
DB_HOST: postgres
DB_PORT: "5432"
DB_NAME: ${DB_NAME:-curator}
CELERY_BROKER_URL: redis://redis:6379/0
CELERY_RESULT_BACKEND: redis://redis:6379/0
SECRET_KEY: ${SECRET_KEY:-change-me-before-you-expose-this}
EXTENSION_API_KEY: ${EXTENSION_API_KEY:-}
LOG_LEVEL: ${LOG_LEVEL:-INFO}
ports:
- "${PORT:-8080}:8080"
volumes:
- ${IMAGES_DIR:-./images}:/images
# Read-only. The filesystem scan copies out of here and never writes to
# it, so a mistake cannot reach the source library.
- ${IMPORT_DIR:-./import}:/import:ro
depends_on:
postgres: { condition: service_healthy }
redis: { condition: service_healthy }
restart: unless-stopped
volumes:
redis_data:
postgres_data: