LangChain Embeddings and Vector Search (Python)

Overview

FAISS.similarity_search_with_score() returns L2 distance — lower is better. Pinecone.similarity_search_with_score() returns cosine similarity — higher is better. Swap your vector store and your if score > 0.8 filter now keeps the garbage and drops the good results, silently. This is pain-catalog entry P12, and it is the single most common reason a "we migrated from FAISS to Pinecone for scale" project loses retrieval quality overnight.

The sibling gotchas: