Treat Embeddings as a Contract
Explain why embedding model, text preparation, and distance metric must be treated as one retrieval contract.
The move: write down the retrieval contract before you tune the database. A vector database stores vectors and retrieves nearby vectors. The hard part is not storing floats; it is deciding what those floats are allowed to mean. The embedding model creates the coordinate space. The chunking rule decides what unit of knowledge gets a coordinate. The distance metric decides how closeness is measured. The metadata filters decide which neighbors are even eligible. Contract Piece 1: Model Use the same embedding model family for ingestion and query. If the model changes, treat it as a migration, not a harmless dependency…
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