bvandeusen 5143f4c34f
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feat(tag-eval): auto-apply operating point + server-side top-N concept discovery
Two additions driven by "what's the commit threshold?" + "find more tags":

1. High-precision operating point (Bar 4). Per concept, report the threshold that
   maximizes recall while holding precision >= a target (default 0.97, configurable
   via `precision_target`) — i.e. "could this fire without a human, and how much
   would it catch?" `head.auto_apply` = {target, threshold, precision, recall} or
   null if the target is unreachable. Surfaced on the card.

2. Server-side concept auto-discovery. `auto_top_n` param unions the explicit
   concept list with the N most-tagged general tags (one fast DB query) so the
   eval can broaden itself without hand-listing — replaces the slow HTTP directory
   paging. Card gains "+ auto-add top-N" and precision-target inputs.

No migration; numpy/sklearn stay lazy. Existing _normalize_params test still
holds (new keys additive; None still falls back to DEFAULT_CONCEPTS).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-28 00:50:28 -04:00

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. Both ci.yml and build.yml use this label. The runner image (runner-base:python-ci) is built from CI-Runner/CI-python/ in the operator's workspace; make push from 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 — for docker push to git.fabledsword.com
    • write:release — for future release-cutting workflows
    • write:issue — for future issue-management automation

    Generate at https://git.fabledsword.com/user/settings/applications. The injected GITHUB_TOKEN cannot be used because it lacks write:package.

License

Personal project; use at your own discretion.

S
Description
Self-hosted media curation — gallery, ML tagging, and subscription-driven downloads. Part of the FabledSword family. (Merge of ImageRepo + GallerySubscriber.)
Readme 16 MiB
v26.06.04.0 Latest
2026-06-04 23:21:01 -04:00
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