Files
FabledCurator/backend/app/api/__init__.py
T
bvandeusen 22c3b54746
CI / lint (push) Failing after 3s
CI / frontend-build (push) Successful in 19s
CI / backend-lint-and-test (push) Successful in 26s
CI / integration (push) Failing after 3m26s
feat(heads): production per-concept heads — train + score backend (#114 A)
The eval (#1130) proved the frozen-embedding + trained-head spine; this lands
its production form (the first of three slices that make heads the suggestion
source, replacing Camie + centroid).

- tag_head: one logistic-regression head per general/character concept with
  enough labelled positives. Weights (pgvector), honest CV-derived suggest
  threshold + earned-auto-apply point, and per-concept quality metrics.
- head_training_run: persisted batch lifecycle (mirrors tag_eval_run) so the
  admin card shows live + historical status across navigation.
- services/ml/heads.py: TRAIN (sync, ml worker, reuses tag_eval's proven data
  loaders + metric math so production heads match measured eval numbers) and
  SCORE (async, API worker — numpy via pgvector, no scikit-learn): score one
  image's embedding against all heads → the rail's suggestions, cached on
  (count, max trained_at) so a retrain invalidates without per-request loads.
- tasks.ml.train_heads (ml queue, commits per head so a kill leaves progress)
  + recover_stalled_head_training_runs sweep + retention(20) + 5-min beat
  (rule 89).
- api/heads.py: POST /api/heads/train (one run at a time, 409 guard) + GET
  /api/heads (count, graduated, last-trained, running, per-concept table,
  recent runs).
- ml_settings: head_min_positives + head_auto_apply_precision, tunable via
  /api/ml/settings.

Scoring isn't wired into the rail yet (slice C) and the admin UI is slice B —
this slice makes training + scoring exist and CI-verifiable. 'precision' column
stored as precision_cv (SQL reserved word). Migration 0058.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
2026-06-28 10:36:25 -04:00

72 lines
2.0 KiB
Python

"""API blueprint registration.
This module is imported by the Quart app factory; it just exposes the
top-level `api_bp` for backward compatibility with FC-1's health route,
and ALL_BLUEPRINTS for the factory to register sibling blueprints.
"""
from quart import Blueprint
from . import health
api_bp = Blueprint("api", __name__, url_prefix="/api")
api_bp.add_url_rule("/health", view_func=health.get_health, methods=["GET"])
def all_blueprints() -> list[Blueprint]:
from .admin import admin_bp
from .aliases import aliases_bp
from .allowlist import allowlist_bp
from .artist import artist_bp
from .artists import artists_bp
from .attachments import attachments_bp
from .cleanup import cleanup_bp
from .credentials import credentials_bp
from .downloads import downloads_bp
from .extension import extension_bp
from .gallery import gallery_bp
from .heads import heads_bp
from .import_admin import import_admin_bp
from .ml_admin import ml_admin_bp
from .platforms import platforms_bp
from .posts import posts_bp
from .provenance import provenance_bp
from .settings import settings_bp
from .showcase import showcase_bp
from .sources import sources_bp
from .suggestions import suggestions_bp
from .system_activity import system_activity_bp
from .system_backup import system_backup_bp
from .tag_eval import tag_eval_bp
from .tags import tags_bp
from .thumbnails import thumbnails_bp
return [
api_bp,
attachments_bp,
gallery_bp,
provenance_bp,
tags_bp,
artist_bp,
artists_bp,
showcase_bp,
settings_bp,
system_activity_bp,
system_backup_bp,
admin_bp,
cleanup_bp,
import_admin_bp,
suggestions_bp,
allowlist_bp,
aliases_bp,
tag_eval_bp,
heads_bp,
ml_admin_bp,
thumbnails_bp,
sources_bp,
platforms_bp,
posts_bp,
credentials_bp,
extension_bp,
downloads_bp,
]