feat(retrieval): add LLM query expansion with multi-query fusion#159
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Salomondiei08 wants to merge 1 commit intoEverMind-AI:mainfrom
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feat(retrieval): add LLM query expansion with multi-query fusion#159Salomondiei08 wants to merge 1 commit intoEverMind-AI:mainfrom
Salomondiei08 wants to merge 1 commit intoEverMind-AI:mainfrom
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Addresses vocabulary mismatch failure mode in hybrid retrieval where stored memories use different terms than the query (e.g. 'rescue inhaler protocol' stored vs 'gym bag' queried). Changes: - src/memory_layer/query_expansion.py: new module implementing expand_query() which generates 2-3 LLM paraphrase variants of a query using a structured prompt. Falls back silently (returns []) on any LLM failure. Also provides merge_hits_by_id() for union-dedup of per-query result sets. - src/agentic_layer/memory_manager.py: retrieve_mem_hybrid() now routes through _search_hybrid_with_query_expansion() instead of _search_hybrid(). This runs keyword+vector search in parallel for the original query and each variant, merges results by memory id (original-query scores preserved), then reranks the union against the original query for consistent scoring. Falls back to plain hybrid search when expansion produces no variants. Inspired by RAG-Fusion / HyDE. Recall improvement is measurable via Recall@K with single-query vs expanded-query baselines.
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Additional Notes
_search_hybridis unchanged and still used by the AGENTIC and RRF retrieval paths — only the HYBRID path is affectedBreaking Changes
None.
_search_hybridis preserved as-is. The new routing inretrieve_mem_hybridis fully backward compatible and falls back to the original behavior on any failure.