mem0ai/mem0 ts-v3.0.7 on GitHub

Mem0 Node SDK (v3.0.7)

New Features:

Embeddings: Add LMStudioEmbedding provider for local embeddings via the LM Studio server (#5377)
Memory: Add opt-in explain: true option to Memory.search(). When enabled, each result includes a scoreBreakdown object with semantic, keyword, entityBoost, and temporalBoost fields so callers can inspect and tune retrieval ranking (#5102)

Bug Fixes:

Memory: Parallelize entity boost searches in Memory.search(). All entity embed + store lookups now run concurrently instead of sequentially, eliminating multi-second latency on entity-rich queries with remote embedding providers (#5377)
Vector Stores: Normalize similarity scores to [0, 1] (higher = better) — fixed score inversion in the Redis vector store adapter (#5391)
Embeddings: Request encoding_format: "float" from the OpenAI embedder in both embed() and embedBatch(). Fixes incorrect vector dimensions when using OpenAI-compatible proxies that default to base64 encoding (#5170)