This release includes breaking changes for platform teams planning a safe upgrade.
✓ No known CVEs patched in this version
Topics
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Summary
AI summaryFixed wRRF weight bug so keyword_weight, graph_weight, and embedding_weight now apply correctly.
Full changelog
Bug Fixes
- wRRF 가중치 버그 수정 —
keyword_weight,graph_weight,embedding_weight가 실제로 적용되지 않고 모두 1.0으로 하드코딩되어 있던 버그 수정. embedding 활성화 시 설정값(keyword=0.2, graph=0.5, embedding=0.3)이 정상 반영됨 - poetry.lock 동기화 — CI 실패 원인이던 lock 파일 갱신
New Features
- Embedding 범용 어댑터 (
wrap_embedding()) — LLM 어댑터(wrap_llm())와 동일한 패턴:"openai/text-embedding-3-large"— OpenAI Embeddings API"ollama/nomic-embed-text"— Ollama local embeddings"sentence-transformers/all-MiniLM-L6-v2"— local sentence-transformers"litellm/..."— litellm gatewaycallable(list[str]) -> list[list[float]]— custom function
- Corpus 기반 자동 stopword — DF 50% 이상 토큰을 자동 감지하여 BM25 query에서 제거. 하드코딩 제거, API마다 적응
set_weights()API — wRRF fusion 가중치를 사용자가 조절 가능:tg.set_weights(keyword=0.1, embedding=0.5) # embedding 비중 증가
Search Quality Improvements
x2bee 1077 tools 기준:
- "search products": ❌
getDeliveryMgmtList→ ✅getDisplayGoodsList(정확 매칭) - "회원 정보 수정": ⚠️
saveMemberDelivery→ ✅getMemberInfo(1위 개선) - "주문 취소": ✅
cancelOrder(유지)
322 tests passing, 6 skipped
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About SonAIengine/graph-tool-call
When tool count exceeds LLM context limits, accuracy collapses (248 tools → 12%). graph-tool-call builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy to 82% with 79% fewer tokens. Zero dependencies. Also works as an MCP Proxy — aggregate multiple MCP servers behind 3 meta-tools.
Related context
Beta — feedback welcome: [email protected]