vector-hybrid-search
CommunityMaster vector search with Elastic and RAG
Authorkevinsweet
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Enables engineers to design and implement end-to-end vector and hybrid search workflows in Elasticsearch, powering semantic queries, RAG, and vector storage for AI pipelines.
Core Features & Use Cases
- Comprehensive decision tree from deployment options through production optimization and RAG extension.
- Supports semantic search, hybrid BM25+vector retrieval, kNN indexing, and embeddings with LangChain/LlamaIndex integrations.
- Practical guidance for planning, mapping, ingestion, monitoring, and iteration in real-world apps.
Quick Start
Configure a new vector search project by selecting deployment type, embedding strategy, and start building a hybrid search flow in Elasticsearch.
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: vector-hybrid-search Download link: https://github.com/kevinsweet/elastic-ide-context/archive/main.zip#vector-hybrid-search Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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