Optimize AgentDB vector search performance using quantization for 4-32x memory reduction, HNSW indexing for 150x faster search, caching, and batch operations for scaling to millions of vectors.
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AgentDB Vector Search Optimization
Overview
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations for scaling to millions of vectors.
SOP Framework: 5-Phase Optimization
Phase 1: Baseline Performance (1 hour)
Measure current metrics (latency, throughput, memory)
Identify bottlenecks
Set optimization targets
Phase 2: Apply Quantization (1-2 hours)
Configure product quantization
Trai
[Description truncada. Veja o README completo no GitHub.]
