feat(heads): earned auto-apply — sweep mechanism, off by default (#114 auto-apply A)

Graduated heads can now apply their tag without a human — gated so it's safe:
- FIRING GATE: a head fires only when the master switch (head_auto_apply_enabled,
  default OFF) is on AND it has >= head_auto_apply_min_positives (default 30)
  clean labels. A precise-looking but under-supported low-N head can't spray tags.
- auto_apply_sweep (heads.py): streams every embedded image in chunks, scores
  against the eligible heads (numpy, no sklearn), applies each head's tag where
  score >= its auto_apply_threshold and the tag isn't already applied/rejected,
  with source='head_auto' (distinguishable + reversible). dry_run counts only.
- HeadAutoApplyRun (migration 0059) tracks each sweep / preview; apply_head_tags
  task (ml queue) + scheduled_apply_head_tags daily beat (no-op unless enabled)
  + recovery sweep + retention(20).
- API: POST /api/heads/auto-apply {dry_run} (202 / 409 running / 400 disabled),
  GET /api/heads/auto-apply (recent runs + per-concept report). Settings
  head_auto_apply_enabled + min_positives via /api/ml/settings.

Tests: sweep applies above threshold, dry-run writes nothing, skips under-
supported + ungraduated heads; API disabled/dry-run/conflict guards.

NEXT (slice 2): the observability the operator asked for — per-concept misfire
(auto-applied-then-removed) + under-fire tracking, time-series snapshots, and a
reporting API to tune. Slice 3: the UI (enable, preview, trends).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa

alembic/versions/0059_head_auto_apply.py

@@ -0,0 +1,70 @@
+"""head_auto_apply_run + earned-auto-apply settings (#114)
+
+A graduated head can apply its tag without a human, gated by a master switch +
+a support floor. head_auto_apply_run tracks each sweep / dry-run preview.
+
+Revision ID: 0059
+Revises: 0058
+Create Date: 2026-06-29
+"""
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects.postgresql import JSONB
+
+revision: str = "0059"
+down_revision: Union[str, None] = "0058"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "head_auto_apply_run",
+        sa.Column("id", sa.Integer(), primary_key=True),
+        sa.Column(
+            "dry_run", sa.Boolean(), nullable=False, server_default=sa.false()
+        ),
+        sa.Column("params", JSONB(), nullable=False),
+        sa.Column(
+            "status", sa.String(length=16), nullable=False,
+            server_default="running",
+        ),
+        sa.Column(
+            "started_at", sa.DateTime(timezone=True), nullable=False,
+            server_default=sa.func.now(),
+        ),
+        sa.Column("finished_at", sa.DateTime(timezone=True), nullable=True),
+        sa.Column("n_applied", sa.Integer(), nullable=True),
+        sa.Column("report", JSONB(), nullable=True),
+        sa.Column("error", sa.Text(), nullable=True),
+        sa.Column("last_progress_at", sa.DateTime(timezone=True), nullable=True),
+    )
+    op.create_index(
+        "ix_head_auto_apply_run_status", "head_auto_apply_run", ["status"],
+    )
+
+    op.add_column(
+        "ml_settings",
+        sa.Column(
+            "head_auto_apply_enabled", sa.Boolean(), nullable=False,
+            server_default=sa.false(),
+        ),
+    )
+    op.add_column(
+        "ml_settings",
+        sa.Column(
+            "head_auto_apply_min_positives", sa.Integer(), nullable=False,
+            server_default="30",
+        ),
+    )
+
+
+def downgrade() -> None:
+    op.drop_column("ml_settings", "head_auto_apply_min_positives")
+    op.drop_column("ml_settings", "head_auto_apply_enabled")
+    op.drop_index(
+        "ix_head_auto_apply_run_status", table_name="head_auto_apply_run"
+    )
+    op.drop_table("head_auto_apply_run")