AgentDB Vector Search
CommunityFast semantic vector search for knowledge bases.
Authorbjpl
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Implements vector-based semantic search using AgentDB's high-performance vector database to enable fast document retrieval, similarity matching, and context-aware querying for RAG and knowledge bases.
Core Features & Use Cases
- Vector Storage: Store documents with embeddings for fast retrieval.
- Similarity Search: Retrieve top-k similar results quickly.
- Hybrid Search: Combine vector similarity with metadata filters for refined results.
- RAG Pipelines: Build Retrieval Augmented Generation workflows with contextual results.
Quick Start
Initialize the AgentDB vector store, index documents with embeddings, and run a query to retrieve relevant results.
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: AgentDB Vector Search Download link: https://github.com/bjpl/hablas/archive/main.zip#agentdb-vector-search Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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