embedding-strategies - Select and optimize embeddings for search
Select embedding models, chunk documents, preprocess text, and optimize embeddings for semantic search and RAG applications.
Tags
Updated: 2026-09-29Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Select embedding models
- Optimize chunking strategies
- Preprocess embedding text
- Generate text embeddings
- Reduce embedding dimensions
- Compare model performance
- Handle multilingual content
- Process documents for storage
Inputs
- Source text or documents
- Embedding model configuration
- Chunking parameters
- Preprocessing function
- Metadata field configuration
Outputs
- Text embeddings
- Document chunks
- Processed vector records
Requirements
- Python environment
- OpenAI API access for OpenAI models
- Sentence Transformers for local models
- Model access for local embeddings
- tiktoken for token chunking
- NLTK data for sentence chunking