Create and query vector indexes
OfficialBuild fast vector search with FalkorDB
AuthorFalkorDB
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps developers create efficient approximate nearest neighbor searches in FalkorDB without needing to manually configure vector index settings or query patterns.
Core Features & Use Cases
- HNSW Vector Index Creation: Configure vector indexes with embedding dimensions, similarity functions, and performance tuning parameters.
- Vector Similarity Queries: Run ANN searches against embedded node properties and retrieve ranked results with similarity scores.
- Use Case: Build semantic search applications that find similar products, documents, or entities using stored embeddings in a FalkorDB graph.
Quick Start
Use the vector index skill to create an HNSW index and query similar nodes from my FalkorDB graph embeddings.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Create and query vector indexes Download link: https://github.com/FalkorDB/skills/archive/main.zip#create-and-query-vector-indexes Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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