embedding-strategies - Embedding Strategies for Semantic Search and RAG
Select and optimize embedding models, chunking methods, and embedding dimensions for semantic search and RAG applications.
Tags
Updated: 2026-10-05Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Compare embedding models
- Select domain-specific models
- Design chunking strategies
- Optimize embedding quality
- Reduce embedding dimensions
- Handle multilingual content
- Generate embedding code
Inputs
- Documents or text
- Search domain
- Embedding provider credentials
- Chunking parameters
- Target vector dimensions
Outputs
- Embedding model recommendations
- Text chunks
- Embedding vectors
- Embedding code templates
Requirements
- Python environment
- Embedding library dependencies
- Provider API access for hosted models
- Provider credentials for hosted models