Vector DB Build

[dishmint]

Have embeddings that represents the lexical patterns in a text. Store in VDB.

https://www.pinecone.io/learn/vector-database/

To find the nearest neighbors for a given query vector, we use the same hashing functions used to “bucket” similar vectors into hash tables. The query vector is hashed to a particular table and then compared with the other vectors in that same table to find the closest matches. This method is much faster than searching through the entire dataset because there are far fewer vectors in each hash table than in the whole space.