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dba-vectordb

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Optimize vector databases for AI search.

Software Engineering#semantic search#vector database#RAG#hybrid search#pgvector#HNSW#embedding
AuthorMassimilianoPili
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill streamlines the design and optimization of vector databases, crucial for efficient semantic search and Retrieval Augmented Generation (RAG) in AI applications.

Core Features & Use Cases

  • Vector Indexing: Configure HNSW and IVFFlat indexes for pgvector.
  • Hybrid Search: Implement combined vector similarity and BM25 search.
  • Embedding Pipelines: Design and optimize the ingestion of embedding data.
  • Use Case: Optimize a pgvector database for a RAG system by configuring an HNSW index for fast semantic search and implementing hybrid search to combine vector results with keyword relevance.

Quick Start

Use the dba-vectordb skill to create a pgvector HNSW index for embeddings in the 'documents' table.

Dependency Matrix

Required Modules

None required

Components

scriptsreferences

💻 Claude Code Installation

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Please help me install this Skill:
Name: dba-vectordb
Download link: https://github.com/MassimilianoPili/agent-framework/archive/main.zip#dba-vectordb

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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