How to Create Vector Embeddings in Python

This site does not allow itself to be embedded. You can still read it on the original site — the toolbar below keeps your place in the directory.

When you’re building a retrieval-augmented generation (RAG) app, the first thing you need to do is prepare your data. You need to: collect your unstructured data split it into chunks turn those chunks into vector embeddings store the embeddings in a vector database There are many ways that you can create vector embeddings in Python. In this post, we’ll take a look at four ways to generate vector…

Read on philna.sh ↗