get_sparse_vector was accidentally inserted between get_embedding's
signature and its body, disconnecting the embedding call and leaving
module-level code referencing undefined variables. Moved to standalone
function before get_embedding.
V2.07 (A01): Replace subprocess.run(['arq', ...]) with programmatic
arq.worker.run_worker(WorkerSettings). Fixes signal handling,
graceful shutdown, and logging unification.
V2.10 (D11): Fix filename → file_path in backfill_decay_metadata.py
resolve_timestamp() now reads payload.file_path (consistent with
what bulk_wiki_ingest.py writes). Replaced VAULT_ROOT path
reconstruction with direct Path(file_path).
V2.11 (D05): Auto-create Qdrant collection in bulk_wiki_ingest.py
If collection doesn't exist, creates it with hybrid schema
(dense 4096d Cosine + sparse BM25) instead of sys.exit(1).
V2.12 (D27): Add sparse vector generation to bulk_wiki_ingest.py
Optional fastembed BM25 sparse vectors alongside dense embeddings.
Falls back to dense-only if fastembed not installed. Vectors stored
as Qdrant named vectors: {'dense': ..., 'sparse': ...}
- Silent removal (empty string) left grammatically broken sentences
and no audit trail. [REDACTED] preserves context structure.
- Control chars and zero-width Unicode keep empty string replacement
(invisible characters, removal is correct).
- Updated 4 test assertions in _test_sanitize.py.
fix(context_enhancer): refactor embed_query_sparse to use stdin instead of f-string interpolation
- Eliminates shlex.quote() crash with apostrophes (SyntaxError in subprocess)
- Eliminates user text interpolation into Python code string
- Hardcodes BM25 model name (was already hardcoded module-level)
- Corrects FastEmbed API usage: model.embed([query]) instead of model.embed(string)
ClaudioDrews
David Soff