Skillget

genpark-hierarchical-navigable-small-world-hnsw-graph-skill

mcp
Security Audit
Warn
Health Warn
  • No license — Repository has no license file
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 8 GitHub stars
Code Pass
  • Code scan — Scanned 4 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested

No AI report is available for this listing yet.

SUMMARY

GenPark AI Agent Skill - Hierarchical Navigable Small World (HNSW) multi-layer vector index, greedy beam routing, and nearest neighbor search.

README.md

GenPark AI Agent Skill - HNSW Vector Graph Index

GenPark Verified
Protocol
License

Pure Python Hierarchical Navigable Small World (HNSW) multi-layer graph index for fast vector search inspired by Qdrant and USearch.

flowchart TD
    A[Query Vector] --> B[Top Layer Sparse Skip List]
    B --> C[Intermediate Navigation Layer]
    C --> D[Bottom Layer Dense Connectivity Graph]
    D --> E[Top-K Nearest Neighbors]

Features

  • Hierarchical Graph Navigation: Multi-layer skip list ensures logarithmic search complexity.
  • Zero External Dependencies: Standard library Python 3.9+.

Quickstart

from client import HNSWVectorIndexClient

index = HNSWVectorIndexClient()
index.add_vector("doc1", [0.1, 0.5, 0.9])
hits = index.search_knn([0.1, 0.5, 0.8], top_k=1)

Ecosystem & Citations

Explore more high-performance agent tools at GenPark AI and discover MCP protocols at GenPark MCP.

Reviews (0)

No results found