The >500-video threshold was too aggressive — it skipped tiebreaking
for legitimate large channels (1a-auto, forgotten-weapons, etc.) where
channel context correctly resolves ties. Replace with an explicit
MEGA_CHANNEL_SKIP_LIST in recon_domains.py. Only known non-topical
catch-alls (currently just "Transcript") skip the tiebreaker.
Removed _channel_video_count() helper and MEGA_CHANNEL_THRESHOLD
constant (no longer used).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace on-disk concept file reads with Qdrant payload queries for
domain assignment. This unlocks assignment for ~10,120 items that had
missing or legacy-only concept files on disk while Qdrant held the
correct 18-domain taxonomy data.
Changes:
- domain_assigner.py: Replace _count_concept_domains (disk) with
_count_domains_from_qdrant and _count_domains_from_qdrant_batch
(Qdrant scroll queries). Add _get_qdrant_client helper. Remove
pass 3 defensive re-run (Qdrant reads are consistent). Add
no_concepts terminal status for zero-vector documents.
- embedder.py: Post-embed hook passes existing qdrant client to
compute_assignment, avoiding a second connection.
- recon.py: Backfill creates one QdrantClient for the batch. SQL
filter includes existing needs_reprocess items. Dry-run reports
no_concepts as separate bucket. --reprocess-missing removes
concept-dir deletion step (no longer reads from disk).
- docs/domain-assignment.md: Algorithm references Qdrant, documents
no_concepts status, removes pass 3 description.
Dry-run results: 20,453 assigned, 1,392 tied, 298 no_concepts,
0 needs_reprocess, 0 errors (previously 10,416 needs_reprocess).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
