chaim
1441a41d45
Single-shot search ranks the source whose title literally contains the query terms way above everything else, so "מהי תקנה 37" returns 6 hits from the תקנה 37 circular + 2 from the law and zero from ספר הליקויים — even though the latter is the canonical medical reference for that regulation. The ask agent already worked around this by issuing several search_insurance_kb calls with different phrasings; that intelligence is now also available to the public /kb/search endpoint. Implementation: - _retrieve_rrf extracts vector + lexical retrieval (RRF fused, no rerank) into a reusable async helper. Each candidate now carries chunk_id so callers can dedup when merging multiple sub-searches. - _expand_query asks the configured Claude model (via ai-gateway) for up to 3 alternative phrasings, with a 12s timeout. On any failure the caller silently falls back to single-query mode. - search() gains an `expand: bool` parameter. When true, runs the original query plus all variants through _retrieve_rrf in parallel, merges by chunk_id keeping the best RRF score, and reranks the union against the ORIGINAL query so the final order reflects what the user asked, not the variants. - /kb/search defaults to expand=true. Cost per call: 1 extra LLM round-trip (~1-2s on Sonnet) and 3 extra Voyage embeds (~150ms each, parallel). Latency budget grows from ~700ms to ~3s, acceptable for a search the user explicitly triggered. Refs Task Master #1