Round-1 claude-review findings:
- 🔴 Multi-doc_type search billed N embedding calls as 1. nc_semantic_search
loops search() once per doc_type on one BM25HybridSearchAlgorithm instance,
and each call re-embedded the query, so only the last query_token_count was
recorded. Cache the dense embedding per query on the (per-request) instance
so the query is embedded — and metered — exactly once regardless of how many
doc_types are searched. This also removes the redundant per-type embed work
and avoids billing a user N× for one logical query.
- 🟡 Ollama embed() now delegates to embed_with_usage() so single and batch
embeds use the same /api/embed endpoint (was the legacy /api/embeddings),
keeping _detect_dimension and other embed() callers consistent.
- 🟢 round() instead of truncating int() when coercing provider-reported token
counts (forward-compatible if a provider ever returns a float).
Tests: per-instance query-embedding cache (embedded once across 3 doc_types;
re-embeds on a different query).
Deferred (stated on the PR): mistral/openai single-embed dual path (changes
tested error/request semantics on the cloud-critical path — separate refactor),
bedrock boto3 sync-in-async (pre-existing; no new invoke_model calls per doc).
Deck #67.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
