feat: cap-aware autoscaler + token-gated whole-instance tag reset (operator feedback)
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Autoscaler (agent 2026-07-02.5): the buffer-occupancy signal alone would peg
downloaders at DL_MAX while the bandwidth CAP — not concurrency — is the real
constraint (8 streams sharing 8 MB/s move no more data than 4). Growth is now
gated on the pipe having headroom (net < 85% of cap) and a pipe pinned at the
cap (>= 95%) sheds streams down to 3; dead band prevents flapping. The UI hint
says 'holding at the bandwidth cap' and /status reports bw_capped, so the
behavior is legible without tests that need the ML stack.

Reset content tagging: stays a FULL-instance reset (operator's call), but now
lives in a fenced 'Danger zone' section on Cleanup and the apply is gated by a
preview-derived confirm token (mirrors the Tier-C bulk-delete pattern — stale
counts are rejected server-side). Copy no longer claims suggestions repopulate:
it says plainly the heads' training examples are deleted and re-tagging starts
fresh. Moved out of TagMaintenanceCard into DangerZoneCard.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
This commit is contained in:
2026-07-02 16:14:48 -04:00
parent eaea4308fc
commit 7c19ad91ed
9 changed files with 257 additions and 78 deletions
+38 -8
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@@ -276,18 +276,48 @@ async def posts_reconcile_duplicates():
return await _run_dry_run_op(reconcile_duplicate_posts, source_id=source_id)
def _reset_content_confirm_token(projection: dict) -> str:
"""Stable 8-hex token derived from the live counts (mirrors the Tier-C
bulk-delete token): it changes whenever the data changes, so the apply can
only ever run against numbers the operator just previewed."""
canon = f"reset-content:{projection.get('count')}:{projection.get('applications')}"
return hashlib.sha256(canon.encode("utf-8")).hexdigest()[:8]
@admin_bp.route("/tags/reset-content", methods=["POST"])
async def tags_reset_content():
"""Tier-A: delete ALL general + character tags (the Camie-suggestable
content vocabulary) so the operator can re-tag from scratch via
auto-suggest. fandom + series tags + series_page ordering are preserved,
and image_prediction rows are untouched so suggestions repopulate.
dry-run preview returns per-kind counts + applications + a sample so the
UI shows exactly what'll go before the operator confirms (dry_run=false).
Irreversible except via DB backup restore."""
"""Full-instance reset of the CONTENT vocabulary: deletes ALL general +
character tags and their image applications — INCLUDING the examples the
tagging heads learned from. Suggestions do NOT repopulate on their own
(the Camie predictions that once did are long retired): the operator
re-tags from scratch and the heads retrain from the new signal. fandom +
series tags + series_page ordering are preserved.
Deliberately Tier-C-gated despite the Tier-A shape (operator 2026-07-02:
the full reset stays, but behind extra steps): dry_run returns the
projection + a `confirm` token derived from the live counts; the apply
must echo that token back or it is rejected."""
from ..services.cleanup_service import reset_content_tagging
return await _run_dry_run_op(reset_content_tagging)
body = await request.get_json(silent=True) or {}
dry_run = bool(body.get("dry_run", False))
async with get_session() as session:
projection = await session.run_sync(
lambda s: reset_content_tagging(s, dry_run=True)
)
token = _reset_content_confirm_token(projection)
if dry_run:
projection["confirm"] = token
return jsonify(projection)
if str(body.get("confirm", "")) != token:
return _bad(
"confirm_mismatch",
detail="run a fresh preview and echo its confirm token",
)
result = await session.run_sync(
lambda s: reset_content_tagging(s, dry_run=False)
)
return jsonify(result)
@admin_bp.route("/tags/normalize", methods=["POST"])
+4 -1
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@@ -726,7 +726,10 @@ RESETTABLE_TAG_KINDS = ("general", "character")
def reset_content_tagging(session: Session, *, dry_run: bool = False) -> dict:
"""Count (dry_run) or DELETE every general + character tag so the operator
can re-tag from scratch (heads/CCIP repopulate suggestions).
can re-tag from scratch. NB: the deleted applications include the tagging
heads' training positives — suggestions do NOT repopulate on their own; the
heads retrain from whatever the operator re-tags. (The API route gates the
live run behind a preview-derived confirm token for exactly this reason.)
PRESERVED: fandom + series tags and their series_page ordering. CASCADE on
image_tag / tag_alias / tag_suggestion_rejection clears each deleted tag's