bvandeusen
ca1c17446c
The rail's Suggestions now come from the trained per-concept heads. SuggestionService.for_image scores the image's frozen SigLIP embedding against every head (heads.score_image) and surfaces concepts above each head's own suggest threshold; the typed-dropdown's min=0 "show everything" mode maps to a flat floor so any head-scored concept can still be picked. Already-applied tags drop; rejected tags stay flagged + reversible (unchanged). REMOVED from the suggestion path (rule 22, no fallback): the Camie ImagePrediction candidate/alias/merge pipeline and the per-tag centroid augmentation, plus the now-dead SuggestionService internals (_load_predictions, _threshold_for, _settings, self.aliases, self.centroids). Head suggestions are always canonical tags, so raw_name/via_alias are null/false and the rail's alias kebab is inert by data (its removal + the Camie ingest-tagger rip are the flagged follow-up). for_selection (bulk consensus) now aggregates head suggestions unchanged. Tests rewritten to the head path: test_ml_suggestions (surfaces/applied/ rejected-reversible/override/no-embedding/no-heads), test_suggestions_bulk (consensus), test_api_suggestions (get + dropped the Camie-alias roundtrip), and test_ml_artist_retired (artist not head-eligible via _HEAD_KINDS). DEPLOY NOTE: after this lands, the rail is empty until you run Train heads (Settings → Tagging → Concept heads) — deploy, train, then the rail populates. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
FabledCurator
Self-hosted media curation — gallery, ML tagging, and subscription-driven downloading in one app. Part of the FabledSword family.
Combines what was ImageRepo (gallery, ML, importer) and GallerySubscriber (gallery-dl wrapper, subscriptions, credential capture) into a single product.
Status
Pre-v1. Not yet functional.
Quick start
For local development and testing, just:
docker compose up -d
# UI: http://localhost:8080
That uses sane dev defaults baked into docker-compose.yml and the dev
override (docker-compose.override.yml, auto-merged) — local builds, DEBUG
logging, exposed Postgres + Redis ports on the host. No .env required.
For a production-like deployment, override the dev defaults via shell env
or a .env file (see .env.example for the variable names) and use:
docker compose -f docker-compose.yml up -d
# (skips the override so containers pull registry images)
Deployment posture
FabledCurator is designed to run inside a self-hosted homelab environment over plain HTTP. If you want TLS, terminate it at your reverse proxy. The app does not generate certificates, redirect to HTTPS, or set HSTS.
CI / Forgejo setup
The repo's workflows expect:
-
Runner label
python-ci— a Forgejo runner with Python 3.14, ruff, and Node 22 pre-installed. Bothci.ymlandbuild.ymluse this label. The runner image (runner-base:python-ci) is built fromCI-Runner/CI-python/in the operator's workspace;make pushfrom that directory builds and pushes a new image when toolchain pins change. -
Repo secret
RELEASE_TOKEN— a Forgejo PAT with the following scopes:write:package+read:package— fordocker pushtogit.fabledsword.comwrite:release— for future release-cutting workflowswrite:issue— for future issue-management automation
Generate at https://git.fabledsword.com/user/settings/applications. The injected
GITHUB_TOKENcannot be used because it lackswrite:package.
License
Personal project; use at your own discretion.