AI Agent Vector Search Optimization 2026
The user asks a question, and it takes 3 seconds to get a result—500ms of that is spent on vector retrieval. After optimization, retrieval is done in 10ms.
💡 What You Will Learn
The user asks a question, and it takes 3 seconds to get a result—500ms of that is spent on vector retrieval. After optimization, retrieval is done in 10ms.
|:----|:----:|:--------:| || 2x | 0% | || 3-4x | <2% | || 3x | <1% | || 10-20x | <3% |
Summary
import chromadb
from chromadb.config import Settings
# TuningHNSWParameter
client = chromadb.PersistentClient(
path="./chroma_db",
settings=Settings(
hnsw_construction_ef=200, # 100
hnsw_search_ef=100, # 50
hnsw_m=32, # 16
)
)
Related Articles
2026-07-27
Document RAG Pipeline Tutorial 2026: PDFs to QA System
2026-07-19
DeepSeek V4 vs Qwen 2.5: In-depth Comparison of Two Major Open-Source Models in 2026
2026-08-01
Vector Database Comparison Table 2026: Full Feature Matrix (8 Databases)
Written by our editorial team; tools listed here are tested or verified against public sources. Links point to official sites or GitHub repos for reference only — no paid placements.
