semantic-similarity - Semantic Similarity for Content Discovery
Computes semantic relationships between content using embeddings and vector similarity
Tags
Updated: 2026-03-21Capabilities
Typical Inputs
Typical Outputs
What this skill does
- generate document embeddings
- configure embedding models
- implement vector similarity search
- identify duplicate content
- implement topic modeling
- build recommendation systems
- extract document concepts
- configure hybrid search
Inputs
- embedding model
- vector database
- document content
- knowledge base
- similarity threshold
- search query
Outputs
- embedding vectors
- similarity scores
- duplicate report
- topic model
- recommendation results
- semantic search results
Requirements
- Python environment
- vector database access
- embedding API credentials