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zhuyongxin f035538531 feat(rag): dense+BM25 hybrid on MilvusClientV2, drop SDK path

Replace legacy MilvusServiceClient knowledge search/write with a single
MilvusClientV2 hybrid store (BM25 function + dense ANN + RRFRanker).
Use collection biz_hybrid and require knowledge reindex.

2026-07-27 18:49:20 +08:00

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rag-bm25-hybrid Specification

Purpose

TBD - created by archiving change rag-bm25-hybrid-drop-sdk. Update Purpose after archive.

Requirements

Requirement: Knowledge vector backend SHALL be a single Milvus V2 store

Knowledge indexing and retrieval SHALL use one MilvusClientV2-backed store. Legacy MilvusServiceClient SDK search modes (sdk, auto fallback to SDK) SHALL NOT be used for lookup_knowledge.

Scenario: No SDK search mode

WHEN knowledge retrieval executes
THEN it SHALL NOT call legacy SDK search APIs for candidate generation

Requirement: Hybrid mode SHALL fuse dense ANN and BM25 sparse ANN

When search mode is hybrid, the store SHALL query dense vectors and BM25 sparse vectors and fuse results with RRF (or equivalent ranker) before returning hits.

Scenario: Hybrid uses BM25 text query

WHEN hybrid search runs with a text query
THEN one search leg SHALL use the BM25/sparse field with the raw query text
AND another leg SHALL use the dense embedding of the query

Requirement: Write path SHALL populate BM25 input text and dense vectors

Document chunk indexing SHALL write original content, BM25 input text, dense embedding, and metadata required for chunk identity.

Scenario: Index writes search_text and vector

WHEN a chunk is indexed
THEN the store row SHALL include searchable text for BM25 and a dense vector field

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