Any database can be used to extend the memory of LLMs. What a database does is store stuff and lets you search/retrieve stuff. Embeddings are differet form of data that are in many (but not all) cases superior to searching through text.
You do not need a fancy cloud hosted service to use an embeddings database like you do not need one to use a regular databse (although you could).
Check https://github.com/kagisearch/vectordb for a simple implementation of a vector search database that uses local, on-premise open source tools and lets you use an embeddings database in 3 lines of code.
You do not need a fancy cloud hosted service to use an embeddings database like you do not need one to use a regular databse (although you could).
Check https://github.com/kagisearch/vectordb for a simple implementation of a vector search database that uses local, on-premise open source tools and lets you use an embeddings database in 3 lines of code.