similarity▌

Efficient similarity search patterns for vector databases and semantic retrieval systems. \n \n Covers four major vector database implementations: Pinecone, Qdrant, pgvector with PostgreSQL, and Weaviate, each with production-ready code templates \n Explains three index types (Flat, HNSW, IVF+PQ) with trade-offs between search speed, recall accuracy, and data scale \n Includes four distance metrics (Cosine, Euclidean, Dot Product, Manhattan) and guidance on when to use each \n Demonstrates hybri

Similarity Search Patterns \n Patterns for implementing efficient similarity search in production systems. \n Use this skill when \n \n Building semantic search systems \n Implementing RAG retrieval \n Creating recommendation engines \n Optimizing search latency \n Scaling to millions of vectors \n Combining semantic and keyword search \n \n Do not use this skill when \n \n The task is unrelated to similarity search patterns \n You need a different domain or tool outside this scope \n \n Instruc