Files
FabledCurator/Dockerfile
T
bvandeusenandClaude Opus 5 ffcd13096a
CI / lint (push) Successful in 2s
CI / extension-version (push) Successful in 2s
Build images / sign-extension (push) Successful in 3s
Build images / build-agent (push) Successful in 6s
CI / frontend-build (push) Successful in 20s
extension / lint (push) Successful in 23s
CI / backend-lint-and-test (push) Failing after 31s
CI / integration (push) Successful in 2m16s
Build images / build-ml (push) Successful in 3m8s
Build images / build-web (push) Successful in 3m16s
Build images / smoke-web (push) Skipped
Build images / promote (push) Skipped
feat: one image for every lane, with the model fetch gated on enabling (4296)
Milestone 422 step 6. Dockerfile.ml is gone; the main image carries torch,
torchvision, transformers, onnxruntime and opencv, and serves every lane.

WHY IT HAD TO MERGE: step 5 runs every lane in one process tree, so a second
image would mean the `ml` lane could never be enabled from the UI — there
would be no worker in that container to enable. The switch needs something to
switch.

THE MODEL NO LONGER DOWNLOADS AT BOOT. `entrypoint.sh`'s ml-worker role ran
download_models before celery started, so every boot of that role reached
HuggingFace for ~3.5GB — a startup dependency on a third party for a feature
the operator may never use. Rule 164 permits a runtime fetch only for
something "optional and clearly off", so the fetch is now a TASK, enqueued
the moment the lane is ENABLED.

Being a task is what makes it visible: it gets a TaskRun row, so the download
shows in Activity with a duration and a status, and a failure is something an
operator can see and retry rather than a container that quietly never became
useful. Idempotent, so re-enabling a provisioned lane costs one no-op.

Enqueued only when the lane actually came ON (`enabled is True`, not the
resolved value) so re-saving slots does not re-fetch, and only when the
consumer change landed — a task queued onto a queue nothing consumes would
sit pending with no explanation.

`fabledcurator-ml` KEEPS PUBLISHING, from the merged Dockerfile. The
operator's Swarm stack references that name and lives outside this repo;
dropping it would not break their deploy, it would freeze it silently at the
last publish — the exact failure class this milestone keeps finding. Retiring
the NAME is its own task, gated on that stack moving. Same two-phase shape
#406 used for pixiv.

THREE LIVE BREAKAGES from deleting the file, found by grepping for it rather
than assuming the build was the only consumer:

- `docker-compose.override.yml` built the ml service from it (contributor
  path would have failed at `docker compose build`).
- `tests/test_artifact_paths.py` pins the ml path set.
- `scripts/artifacts.sh` ML_PATHS named it. A path set naming a deleted file
  silently stops contributing to the derived revision — which the reuse check
  and the version string both read. That is #3202's recorded shape.

The `--with-ml` flag is gone from the generator and the healthcheck rather
than left defaulting to true. One image carries every lane now, so a flag
that can only be passed one way is a branch pretending to be a choice.

The advisory shipped in ecbd325 is what makes this honest to an adopter: the
lane says it is optional, names the model, and gives its download and
per-slot RAM before the switch is thrown.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR
2026-09-22 08:51:44 -04:00

115 lines
4.6 KiB
Docker

# syntax=docker/dockerfile:1.25
FROM node:24-alpine AS frontend-builder
WORKDIR /build
COPY frontend/package.json frontend/package-lock.json* ./
# No package-lock.json is tracked yet (we don't run npm locally per
# feedback-no-local-runs), so `npm install` instead of `npm ci`. Flip to
# `npm ci` once a lockfile is committed.
RUN npm install --no-audit --no-fund
COPY frontend/ ./
RUN npm run build
FROM python:3.14-slim AS runtime
ENV PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
PIP_NO_CACHE_DIR=1 \
PIP_DISABLE_PIP_VERSION_CHECK=1
# System deps: ffmpeg (transcode + thumbnails, FC-2), unar (archives, FC-2),
# libpq for psycopg, postgresql-client + zstd for FC-5 backup/restore
# (pg_dump + tar --zstd), image libs, megatools (mega.nz public-link downloads
# for off-platform file-host links, #830 — `megatools dl`; Debian-native, no
# external MEGA apt repo needed).
RUN apt-get update && apt-get install -y --no-install-recommends \
ffmpeg \
unar \
libpq5 \
postgresql-client \
zstd \
megatools \
libjpeg62-turbo \
libwebp7 \
libpng16-16 \
ca-certificates \
# opencv-python-headless (via requirements-ml.txt) links these even in its
# headless build. Came from Dockerfile.ml when the images merged
# (milestone 422 step 6).
libgl1 \
libglib2.0-0 \
&& rm -rf /var/lib/apt/lists/*
WORKDIR /app
COPY requirements.txt requirements-ml.txt ./
RUN pip install -r requirements.txt
# --- ML, merged from Dockerfile.ml (milestone 422 step 6) --------------------
#
# ONE image now serves every lane. It was two because the ML lane ran in its
# own container; with the single-container layout (step 5) running every lane
# in one process tree, a second image would mean the `ml` lane could never be
# enabled from the UI — there would be no worker in this container to enable.
#
# The COST, stated because it is real and falls on every adopter: this adds
# torch, torchvision, transformers, onnxruntime and opencv to an image that
# previously carried none of them. Everyone pulls it, including the many who
# will never turn tagging on. That is the trade the milestone accepted for
# being able to offer the lane as a switch rather than a second deployment.
# What it buys back is that nothing downloads a MODEL until the switch is
# thrown — the weights are not baked in, and rule 164 permits that only
# because the feature is optional and clearly off.
#
# CPU-only torch from the PyTorch CPU index. The default PyPI wheel bundles
# the NVIDIA CUDA runtime (~5.6GB of layer) and nothing here uses a GPU — the
# GPU agent is a separate service with its own image. `--index-url`, not
# `--extra-index-url`: the latter would let pip resolve a +cu wheel anyway.
RUN pip install --index-url https://download.pytorch.org/whl/cpu \
"torch>=2.12,<3.0" "torchvision>=0.27,<0.28"
RUN pip install -r requirements-ml.txt
# Where the model lands. Deliberately NOT a VOLUME instruction: that mints an
# anonymous volume when nobody mounts one, which survives `docker rm` and
# accumulates 3.5GB copies nobody can find. The compose files mount it
# explicitly instead, so an unmounted run simply re-downloads — visible, and
# recoverable.
ENV HF_HOME=/models/.huggingface \
TRANSFORMERS_CACHE=/models/.huggingface \
ML_MODEL_DIR=/models
COPY backend/ ./backend/
COPY alembic/ ./alembic/
COPY alembic.ini ./
COPY entrypoint.sh ./
RUN chmod +x entrypoint.sh
COPY --from=frontend-builder /build/dist ./frontend/dist
# Which channel this image belongs to — `dev` or `main` (milestone 271 step 7).
# build.yml passes it; /api/extension/manifest reports it beside the version so
# an operator can tell which channel an install came from without the channel
# ever touching the version string.
#
# Empty by default, deliberately: a locally-built image then reports NO channel
# rather than claiming to be one, and the manifest omits the field entirely —
# indistinguishable from an image built before the field existed, which is
# exactly the shape every reader already has to handle.
#
# Declared LAST on purpose. An ARG/ENV invalidates every layer below it, and
# these are the values that differ between builds of otherwise identical
# source — put them any earlier and the two channels could never share a
# cached pip install.
#
# FC_VERSION is what the instance reports about itself in the UI. Since
# milestone 318 stopped publishing version image tags, that self-report is
# the only answer to "which build is this?" — nothing else names it.
ARG FC_CHANNEL=""
ENV FC_CHANNEL=${FC_CHANNEL}
ARG FC_VERSION=""
ENV FC_VERSION=${FC_VERSION}
EXPOSE 8080
ENTRYPOINT ["./entrypoint.sh"]
CMD ["web"]